As the Customer Experience Manager at Dr. Squatch, a men's naturally-derived personal care company, I’m constantly looking for ways to craft exceptional experiences for our customers. But the question to ask is: does it actually make a difference to our revenue?

Unearthing the impact of your customer service team starts with evaluation. To do this, it’s essential to track metrics and key performance indicators (KPIs) around customer service.

Evaluating the impact of a customer service team can sometimes be an ambiguous task. That’s why I’m here to outline the most important customer service metrics to watch, so you can effortlessly recognize the ways your customer service team directly moves the needle.

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What is customer support evaluation?

Customer support evaluation is the process of measuring your customer service program's impact on the business.

It requires using metrics and KPIs to understand whether your support team is providing a great customer experience that can generate repeat customers, positive reviews, referrals, and more.

Evaluating your customer support also requires understanding the return on investment (ROI). In other words, do the benefits produced by your support efforts outweigh the cost of your support program?

The benefits of evaluating customer service

In almost every business, a developed support program is worth its weight in gold. Evaluating your program is how you prove it to company leadership, earning you additional budget for tools and team members. 

You can think of a strong customer experience as a rising tide that lifts all ships — the impact is vast but also hard to quantify.

At Dr. Squatch, we’re close with our customers and even closer to the numbers. Once we started employing a data-driven approach to customer support management, it made a huge difference in both customer satisfaction and hitting company targets.

Let’s look at the five incredible benefits you get after you make evaluation a regular part of your customer service program.

1) Detailed insight into your customers’ needs

Customer inquiries are a treasure trove of rich data for you to dig into to create a better experience for future interactions. By evaluating metrics like customer satisfaction (CSAT) or average resolution time, you can identify key trends and issues online shoppers are dealing with and update your customer service strategy.

On Gorgias, your incoming tickets are automatically sorted by AI-powered intent and sentiment detection, giving you a quick overview of which customer issues should be at the top of the list.

2) Identifies which customer service tasks can be automated

It’s not enough to have a talented team replying on behalf of your brand. You need to make sure your team is focusing on the right activities and not wasting their time on the wrong ones.

By measuring metrics related to your team’s performance — like first response time and resolution time — you can identify which tasks can be done with automation. You’ll also be able to figure out which agents on your team may need more training and support.

3) Balances your revenue and expenses

Customer acquisition is becoming more expensive, so keeping track of customer service can give you an idea of how much customer service truly provides within your organization. 

4) Lets you calculate the true customer lifetime value 

True lifetime value is the measure of a customer’s worth over the duration of the customer-business relationship. 

Keep in mind, it’s less expensive to keep current customers than to find new ones. This is increasingly true as customer acquisition costs and social media ad prices soar.

5) Helps to create predictable support quality

Solid customer support quality is predictable. And that’s not a bad thing. That means when anything new, surprising, or daunting happens, you don’t need to call in a special task force. 

Thanks to your stable operations, your whole team will simply need short-term and long-term action plans, like establishing a list of steps to take and point of contacts and to inform.

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Four key indicators that your customer service program needs a makeover

Beyond bad reviews and customer complaints, there are a few quick ways you can tell if your customer service program is not doing well. 

These four key indicators are major signs that your customer service program needs some refining.

1) High contact rate (over 33%)

A contact rate of over 33% means something about your customer journey, communication, or product is not quite right. Your customers aren’t getting the answers they need.

The goal of your customer service team should always be to resolve tickets efficiently. If a customer has to reach out to your brand multiple times, you most likely need to update your support resources.

Leading indicator: Multiple touchpoints per customer

How to fix it: Include more self-service options to give customers quick answers without having to wait to talk to an agent. Add a Help Center, chat widget, or send informative confirmation and post-purchase emails. For example, our chat widget at Dr. Squatch suggests common questions and answers them via an automated quick response flow based on the customers’ reply. 

2) A customer satisfaction score (CSAT) under 4/5

Your customers should be coming away from interactions feeling good about your brand and the support it provides. There’s no acceptable reason for a low CSAT score, so you should always take a closer look when it starts to fall. 

Leading indicator: Friction in customer conversations 

How to fix it: Provide additional training to your support agents to ensure they’re equipped to handle the most pressing customer requests effectively and empathetically. Then, actively seek feedback from customers and use their input to make continuous improvements to your program.

3) Inconsistent first response time and resolution time

Your first response time (FRT) will fluctuate, and most people understand that, but waiting 4 days for an email from support is unacceptable for today’s shoppers. In general, customers want answers within 10 minutes.

Leading indicator: More customer complaints and a low CSAT

How to fix it: Align with your team and identify your customer base’s main complaints. To deflect repeat inquiries, immediately add self-service options like a Help Center or a chat widget to your online store. You can also use automated responses to acknowledge inquiries right away. 

4) Significant percentage of revenue spent on support

Ecommerce companies should aim to spend anywhere from 10% to 15% of revenue on customer service. If you’re spending significantly more than that, it may be a sign that it’s time to reprioritize and take a closer look at how your agents are performing.

Leading indicator: Low agent efficiency

How to fix it: Analyze ticket volume and estimate how many tickets each agent should be able handle and in what set amount of time. When expectations are set within a service level agreement (SLA), align your team and train them on your new methods.

Challenges that impact your customer service program

Managing a customer service program comes with challenges that typically start from the top of the organization and quickly become a domino effect.

Here are the most common challenges a customer service program faces:

• A lack of buy-in from your company. Executive teams may not understand the value in investing in a support team. They often think customer service is there to keep problems away, instead of bringing new value in.
• Under-supported agents. A lack of trust in the customer service team trickles down to agents. It results in insufficient resources and, in turn, overworked and unmotivated support reps.

• Inadequate policies and guidelines. Since agents don’t have the proper resources, the quality of policies take a hit. Whether customer-facing or internal, these policies can suffer from being too broad or unenforced.
• High ticket volumes. An non-cohesive team ultimately affects how customer service runs and the biggest indicator is a workflow that can’t handle a large number of customer inquiries.

These challenges usually exist for one reason: your company hasn’t seen the tangible value your customer service program brings. 

So, how do you prove it? By prioritizing data collection and evaluating your customer service program, of course.

📚 Read more: 12 customer service challenges harming your team and revenue (+ how to solve them)

How to evaluate your customer service program’s success 

Let’s dive into 12 of the most important customer service KPIs to track to help evaluate your customer service program. By doing so, you’ll be able to recognize how the assistance you provide directly impacts your goals, revenue, and customers.

Note: It’s hard to create a one-size-fits-all reporting template — due to the differences between industries and companies — but a solid understanding of these metrics will help you create a plan for tracking the ones that matter most to your business.

1) Customer satisfaction score (CSAT)

The customer satisfaction score tracks how satisfied customers are with your company’s products and services. A high CSAT is a reliable measure of good customer service.

How is it measured?

First, you’ll need to collect customer data through a customer satisfaction survey, typically sent through email. It includes a single question like, “On a scale from 1 to 5, how satisfied are you with your experience today?” 

Once you’ve collected enough responses, use this formula:

CSAT = (Satisfied customers / Total customers surveyed) x 100

Tools for measuring CSAT

There are a ton of tools out there to help you track your organization’s CSAT, but a few to check out include:

• Gorgias
• Nicereply
• Lumoa

Why is it important?

Tracking your company’s CSAT gives you important insight into exactly how satisfied customers are right after an interaction with a member of your team. It can even help identify potential issues before they grow too large. 

2) Net promoter score (NPS)

Net promoter score (NPS) measures how likely a customer is to recommend your brand to another person. It indicates how effective your customer service is as well as how satisfied customers are by gathering data about how likely they are to promote your brand.

How is it measured?

Like measuring CSAT, you can use a survey approach. Through email, you can ask your customers, “How likely are you to recommend our brand to a family member or friend?” 

To determine your NPS, subtract the percentage of detractors (people who say they wouldn’t promote your brand) from the percentage of promoters (those who said they would promote your brand). The resulting score is a whole number between -100 and 100. 

Here’s the formula:

NPS = Percentage of promoters - Percentage of detractors

Similar to tracking CSAT, NPS data can be continuously gathered, but we recommend checking in on a monthly basis. 

Read more about NPS scores and how they’re calculated.

Tools for measuring NPS

• Survicate
• HubSpot Customer Feedback Software
• SurveySparrow
• Survey Kiwi

Check out our guide to how to create an NPS survey that gets responses.

Why is it important?

Your brand’s NPS directly ties to the customer relationship as well as how well your customer success team is doing. Tracking NPS along with CSAT can give you a clearer picture of how customers feel about your brand.

3) Customer retention rate (CRR)

As mentioned previously, retaining customers is always less expensive than finding new customers, that’s why your customer retention rate is a vital metric to keep track of. In particular, ecommerce companies have an average CRR of about 30%, according to Omniconvert, so if your company’s CRR is lower than that, it could be a sign that your customer support isn’t as effective as it could be. 

How is it measured?

To calculate CRR, you’ll need the following information: number of customers at the end of a given time period (E), number of customers gained within that time period (N), number of customers at the beginning of the time period (S). 

Then, plug those numbers into this formula:

CRR = [(E-N)/S] x 100

Tools for measuring CRR

• Mixpanel
• Qualtrics 
• Optimove

Why is it important?

Your company’s ability to retain customers directly relates to its success because when customers disappear, so does revenue.

4) Net retention rate (NRR)

Sometimes known as net dollar retention (NDR) or net revenue rate, NRR is the percentage of recurring revenue retained from your existing customer base over a period of time. This period can be monthly, quarterly, or annually. According to Klipfolio, a good NRR can range between 90% and 125% depending on your brand’s target customer size.

How is it measured?

NRR = [(Monthly recurring revenue (MRR) at the start of a month + expansions + upsells - churn - contractions) / MRR at the start of the month] x 100

Tools for measuring NRR

• ChurnZero
• Mosaic

Why is it important?

Net revenue retention is another extremely valuable metric that helps you understand how your customers are feeling about your brand and products, as well as how your business is doing from a financial standpoint. 

5) First reply time (FRT)

First reply time, or first response time is how long it takes one of your customer service reps to respond to a customer inquiry on average. This could be over email, phone, or chat. Typically, a “good” first reply time is less than 24 hours in a ticketing system, less than 90 seconds for live chat, and three minutes for phone, according to Klipfolio. 

If your brand dedicates a lot of time to live chat, check out these metrics specific to live chat.

How is it measured?

You can calculate your first reply time by measuring the duration of time between when a customer submits a request and the time when a member of your customer support team responds.

FRT = Total first response times during period of time / Total number of tickets resolved in that period

Tools for measuring FRT

• Gorgias
• GeckoBoard
• Observe AI

Why is it important?

First reply times are directly related to your brand’s CSAT. No customer wants to wait days for an email response, or sit on hold for several minutes. Decreasing your first reply times will inevitably increase customer satisfaction.

6) First contact resolution (FCR)

First contact resolution, or first call resolution (FCR), measures an agent’s ability to resolve a customer’s problem or question within the first interaction without requiring a follow up. The average standard benchmark for FCR is 70% to 75%, according to global research.

How is it measured?

You can use this simple formula to calculate FCR:

FCR = Total number of inquiries resolved on the first call / Total number of unique inquiries

Tools for measuring FCR

• TalkDesk
• mySQM
• Akixi

Why is it important?

Your company’s FCR also directly ties to boosting customer satisfaction. According to McKinsey & Company, 83% of customers expect to be able to resolve their complex issues within one interaction. When you meet customer expectations, you encourage brand loyalty and repeat customers, and reduce encountering difficult customers.

7) Average resolution time (ART)

Customers are happier when they don’t have to wait a long time, and average resolution time (ART) is another metric that keeps track of this data. ART shows how customer service team members are performing, and lets you see who may need additional training or support.

How is it measured?

To measure average resolution time, take the total duration of all resolved conversations and divide that by the number of customer conversations that took place over a specific period of time. This metric is also sometimes referred to as the mean time to resolve, or MTTR. 

ART = Total resolution time for all resolved tickets / Total number of tickets solved

Tools for measuring ART

• Gorgias
• AgileCRM
• Kissmetrics

Why is it important?

Your ART is a vital metric that helps keep tabs on how efficient your customer service team is. If your ART is long, or you notice that it’s getting longer, this is a sign that you need to give your processes a closer look and adjust your strategies if needed.

8) Total resolution time

Resolution time is the total time it takes to complete a customer interaction. This is similar to average resolution time, but focuses on the total time spent resolving tickets rather than the average time spent resolving tickets.

How is it measured?

To measure your total resolution time, note the start and end time of each customer conversation over a specific time frame, such as a one-month period. 

Measuring your total resolution time doesn’t require a formula, but is much easier to track with a helpdesk that includes support performance statistics like Gorgias.

Tools for measuring total resolution time

• Olark
• Aircall (specifically for contact center support)

Why is it important?

Total resolution time gives you a deeper look into how long your customer service team spends helping customers solve their issues, which can help inform further strategy and business direction. 

For example, if the total response time steadily increases over several months, you may need to look at hiring additional customer support reps.

9) Customer effort score (CES)

Your customer effort score (CES) tracks how much effort customers feel like they need to put into resolving an issue. The effort customers should have to put into resolving the issue should be minimal, so you want this score to be as low as possible. 

How is it measured?

To measure your brand’s CES, you can use a questionnaire with a scale and ask the question, “On a scale of 1 to 5, how easy was your experience today?” with 1 being “very easy” and 5 being “very hard.” 

Once you have your responses, tally up how many of each score you received — meaning, how many times were you rated a 1, a 2, etc. Then, you can use this formula to determine your CES:

CES = Percentage of “very easy” responses - Percentage of “very hard” responses 

Much like NPS, CES is a whole number between -100 and 100.

Tools for measuring CES

• Typeform
• AskNicely
• Formstack

Why is it important?

CES gives you the opportunity to see how your support team is performing through the eyes of your customers. It can also help identify areas for improvement within your operations if you give customers a place to voice feedback within your questionnaire.

10) Conversation abandonment rate

Your brand’s abandonment rate is a simple, yet highly informational metric. Whether the conversation is happening via email, chat, or phone, if a customer abandons the session, it should be a red flag that there is friction in the process.

How is it measured?

All you need to track is the number of abandoned incidents and the total number of incidents. In this context, “incidents” refers to either calls, emails, or live chat sessions. Once you have those two numbers, you can plug them into the following formula:

Conversation abandonment rate = (Number of abandoned incidents / Total number of incidents) x 100

Tools for measuring conversation abandonment rate

• Hotjar
• Omnisend

Why is it important?

A customer abandoning a conversation they initiated is a bad sign and can lead to poor net promoter scores and high churn rates.

11) Contact rate

Contact rate, also known as customer contact rate, measures the percentage of active customers who ask for help in a given time period — usually a month. 

How is it measured?

To calculate your company’s contact rate, you can divide the number of customers who contact your customer service team for help over the course of a month by the number of total customers. Then, multiply that number by 100. 

Contact rate = (Number of customers who contact you in a month / Total number of customers) x 100

Tools for measuring contact rate

• Mixpanel
• Woopra

Why is it important?

Contact rate is helpful in diagnosing your company’s overall health. For example, a high contact rate may indicate that customers are contacting your support team about everything because you don’t have alternative resources like a Help Center or FAQ page.

12) Backlog

Otherwise known as revenue backlog, backlog is a metric that determines how much revenue will be coming into your business. This metric can be especially helpful if you’re an ecommerce brand that operates on a subscription-based model. 

How is it measured?

The only thing you need to determine your revenue backlog is the sum of the values of your customers’ subscriptions. However, this can be much more complicated in practice if your business model has multiple types of subscriptions, so it’s beneficial to use tools to track this metric.

Tools for measuring backlog

• Y42
• Dataweave

Why is it important?

Keeping tabs on your revenue is vital to ensuring the growth and continued success of your brand. By tracking your revenue backlog, you’ll be able to see if revenue is going to drop before it actually does. 

How to evaluate individual agent performance in 5 steps

Understanding your customer service program at an organizational level is an excellent step. But what about individual employee performance? 

A customer service performance review is key. It gives the agent constructive feedback and provides clear guidance for improvement. The goal of a performance evaluation is to assess their abilities, yes, but also motivate them towards even better performance.

Let’s look at the common performance review phases step by step. 

1) Decide the objective of your review

Lay out the objectives of the review. Is it to assess past performance, set future goals, identify areas of improvement, or all of the above?

2) Analyze relevant data

Take a look at the relevant metrics to gauge agent performance. Make sure you have a record of any previous performance reviews, goals set, training undergone, and feedback received.

Key metrics to pinpoint individual performance:

• First contact response time
• Total resolution time
• Average ticket volume
• Error rate

With Gorgias, it’s easy to keep track of every agent’s performance with Support Performance Statistics. Their intuitive dashboard provides a quick look at the health of your support team and even gives you detailed information on each of your team member’s stats, like their first response time, total closed tickets, and more.

3) Run a soft skills and behavioral assessment 

How effectively does the agent communicate with customers? Are they clear, empathetic, and responsive? Assess the agent’s ability to diagnose customer problems and find solutions. Look at important customer service skills like problem solving, communication skills, as well as teamwork skills.

4) Present your findings to the agent

Share the metrics you’ve collected and any feedback received from customers. Present this so customer service agents understand how customers perceive them. Discuss the agent’s strengths and achievements, where they need improvement. 

5) Set goals and expectations

Discuss immediate and future objectives with the agent. Encourage open dialogue and assure them to come to you with any feedback or concerns.  

At the end of the day, you have to care. Make feedback a regular occurrence. It doesn’t have to be scary. Give feedback whether it's positive, negative, or you just want to tell someone to continue going in the same direction. 

Be prepared to create action plans and reset expectations for bottom performers or people you just want to improve. Having a low performer doesn't necessarily mean that they're tanking, but maybe there's just one area of improvement they can really work on. It's just a matter of having an action plan. 

Do customer service metrics really affect business growth?

Absolutely.

Customer service is the backbone of a business’s success. When you focus on giving outstanding customer service (in addition to product quality, of course), you get customer satisfaction, which turns into new and repeat customers and more revenue.

The customer service metrics outlined in this article are helpful tools to set you on the right path toward building a more successful customer service program. Paying closer attention to the data that matters most can help you identify areas for improvement, which is necessary in order for any business to grow.

Make your customers happy and your business happier with Gorgias

Now that you know which customer service metrics are the best to track to ensure your ecommerce business’s success, you can start evaluating your customer service program. 

Every metric I included above can offer your business better insights into what your current customer service program is doing right, and where there’s room for improvement. You don’t have to track all of these KPIs, but I highly recommend using a platform like Gorgias to keep your customer conversations and metrics in one spot.

If you’re ready to revamp your customer service program and improve your level of service, learn more about what Gorgias can do for ecommerce businesses or sign up today.

Customer service agents are front and center when they provide customers with outstanding support. But once you pull back the curtains, you’ll find the support operations team behind the scenes supporting conversations, tools, and more.

Like backstage managers, a customer support operations team identifies opportunities for your support team to be more efficient while keeping both your company and customers happy.

I’m Bri Christiano, the Director of Customer Support at Gorgias, and I know first-hand how hectic it can be to perfect your customer service processes. We'll go through how a support operation team functions, the benefits, how to build the team including key roles. 

What does customer support operations do? 

Customer support operations oversees the technical, operational, and organizational parts of customer support. As a distinct team, they support the customer service team, including the representatives and managers.

You may think, but isn’t that what customer service managers are for?

Not quite. 

Customer support managers are on the frontline with agents and ensure the operations run smoothly. A support ops team member enables the frontline team to do their best work.

What is a support operations team?

A support operations team constructs the blueprint that makes your company’s customer service processes run more efficiently while hitting your business targets. Some common roles on a support ops team include managers, analysts, developers or product managers, trainers, and specialists.

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A guide to support operations teams

Investing in a support operations team is a step toward improving the customer experience, which can lead to a 2-7% increase in sales revenue. 

Below we'll explore the advantages of establishing a support ops team, show you the tell-tale signs of when it's time to invest, and provide an overview of each role and function.

Benefits of having a support ops team

When you enlist the help of a strategic support ops team, you gain:

1. Predictable, stable operations. A support ops team standardizes your customer service processes, which can help managers and agents stay on the same page and deliver consistent, high-quality service.
2. A better future for the customer service team. CS leads may only forecast a few months or a year ahead. A support ops team can strategize years in advance and plan for more scenarios with their reporting expertise.
3. A louder voice of support across the org. A support ops team aligns customer service with the company’s targets and has the power to bring relevant issues to other teams. This allows the often-isolated customer service team to be better represented across the company.
4. A stronger, alternate perspective to customer service. The support ops team provides a big-picture view that a customer service team doesn’t have the time to look into. You can arrive at a more complete view with the help of support ops.

Every support ops role & responsibility, ranked by budget

A full-fledged support ops team includes a manager, developer, analyst, trainer, and specialist. However, not all organizations have the budget for every support ops role. In that case, you’ll want to find candidates who can take on the responsibilities of multiple roles.

Below, we’ve ranked each support ops role based on your company’s hiring budget. 

1. Support ops specialist

Hiring budget: Low

Customer operations specialists provide support to customer service teams by managing technical aspects, including assisting with setup, analyzing metrics, and reporting, while also lending a hand to enhance customer experience.

Responsibilities:

• Identify when to help customers and note signs of potential issues or opportunities for more sales
• Understand how the product works and know who to ask for help with specific product issues
• Collect important data and make reports about how satisfied customers are, what products they like, and takes note of what competitors are doing

2. Support trainer

Hiring budget: Low 

A customer support operations trainer is responsible for educating and preparing customer service representatives to effectively handle inquiries, issues, and interactions with customers.

Responsibilities:

• Create and update training materials that the customer support team uses
• Deliver onboarding and ongoing training sessions and workshops to keep team members up-to-date with industry best practices
• Assess the effectiveness of training programs through feedback collection, performance metrics analysis, and evaluations

3. Support operations analyst

Hiring budget: Medium 

A customer support operations analyst analyzes data and metrics related to customer interactions and customer service processes to identify trends and improve the overall quality of customer support.

Responsibilities:

• Create a complex staffing model with multiple inputs and considerations
• Create reports based on KPIs and present findings to the customer support team
• Assess support workflows and processes to identify inefficiencies and bottlenecks, and makes recommendations for optimization
• Evaluate and implement tools and automation solutions to streamline tasks

4. Developer or Product Manager

Hiring budget: High 

A customer support operations developer (also known as a product manager) creates and maintains the systems, tools, and processes used to enhance and streamline customer support operations.

Responsibilities:

• Create and maintains tools and applications that enhance the efficiency and functionality of support operations, including self-service tools and chatbots
• Automate repetitive tasks and processes within support operations to reduce the manual work done by agents
• Assist and troubleshoot technical issues for support agents to ensure they can effectively use the necessary tools

5. Support operations manager

Hiring budget: High 

A support ops manager oversees and coordinates the operational aspects of customer support teams.

Responsibilities:

• Oversee the support ops team and recruit, train, and mentors team members
• Analyze data and key performance metrics to identify areas for improvement and make data-driven decisions for customer service
• Develop strategies to align support operations with overall business objectives, including budget management and resource allocation
• Planning for each upcoming quarter and setting key performance metrics
• Working with customer service managers and aligning on goals with them 

When to build a support ops team

There are a few signs that indicate you’re ready to expand and join forces with a support ops team.

1. New roles and duties are popping up

As your business grows, new roles start to emerge to accommodate your team’s size and customer base. This may look like managers and agents finding themselves taking on more operational tasks like leading training sessions, tool workshops, or focusing on data to increase profits.

If these duties are taking away time for you to do your regular customer service responsibilities (like resolving customer issues or supervising your agents), it’s time to invest in support ops.

2. Your support leads are spread across multiple time zones

If support leads are located in various time zones, it’s harder for your team to get on the same page. For instance, one team lead may prioritize using brand voice more than another lead does. This results in inconsistent and confusing brand messaging.

To align your team leads, you’ll need one source of information to standardize your processes — and that can be fulfilled by a support ops manager.

3. Your current workflow can’t keep up with complex tickets

If your workflow fails to cover all your customer inquiries, it may be time to redesign your processes. Unfortunately, building an efficient workflow from scratch takes time that managers typically don’t have. Support ops is exactly the team you need to ideate, test, and deploy these workflows.

Processes, policies, and automation: a framework for optimizing customer support operations

Focus on building a sound hiring process

Rushing to fill positions will only harm your brand and customers in the long run. When hiring for customer service, use a proactive hiring process. This means taking the time to take stock of your needs and resources, and being selective about your candidates.

Here are three ways to be intentional with the hiring process:

1. Determine which specialized support roles are needed. Are new operational duties being delegated to managers or agents? Maybe you need an analyst to make better use of your data or a training specialist for your growing team.
2. Assess the inefficiencies in your current support operations. Certain support ops roles can fill in the gaps that your support team doesn’t have the time for. For example, a support ops developer can improve your tools, while a support ops manager can take care of hitting your business targets.
3. Consider your budget. Your budget will determine the size of your support ops team. Be realistic and adjust your expectations according to your needs. This can mean hiring for one support ops team member or outsourcing.

🧠 Learn more: Why proactive customer service is essential for growing your business

Implement a customer service policy as soon as possible

A customer service policy is a document containing a set of guidelines, rules, and standards for customer service teams. Its goal is to help agents handle day-to-day tasks and set benchmarks for great customer service.

These documents are essentially guides for how the customer service team should work. Agents can use them when they onboard or need a refresher. They can even be adapted into customer-facing policies.

📚 Related reading: How to build an FAQ page + 7 examples

Set realistic SLAs

A service level agreement (SLA) is a contract that outlines the minimum acceptable service between one party and another. In your case, the ops team and the support team. An SLA typically covers topics like SLA best practices, including service availability and average response times.

Here’s how to create one:

1. Define objectives and metrics: Clearly define the objectives and expectations of the support ops team and the customer support team. Identify specific key performance indicators that both teams can stick to.
2. Agree on responsibilities: Specify who’s responsible for what tasks on both teams, including training, reporting, and development to avoid miscommunication.
3. Set performance targets: Establish targets and deadlines for meeting performance metrics. These targets should be realistic and aligned with the organization's goals and customer expectations. 
4. Compose, review, and publish the document: Share your document with all members of the support ops and customer service team. You may even conduct a meeting to align on your new agreement. 
5. Continuously improve: Schedule regular SLA review meetings between the support ops and customer support teams to assess performance, identify areas for improvement, and create new initiatives.

Create a solid training plan for the customer service team

Elevating the quality of training for the support team significantly increases customer satisfaction. Improvement is key: 40% of customers claim that they stop doing business with companies who have poor customer service.

Some ideas for useful training activities:

• Improve customer interactions by reviewing tickets as a team
• Deepen product knowledge with Loom videos
• Drill down empathy by mapping the customer journey together
• Refine soft skills with workshops dedicated to active listening, empathy, and effective communication
• Practice responding to public social media reviews and comments

When you put these strategies together, you empower your ops team with the expertise and resources needed to excel in their roles, allowing them to pass the knowledge on to your customer service reps.

Write templates that your agents can use in various circumstances

Agents shouldn’t have to spend their time crafting templates — that’s a job for the support ops team. With templates, agents can speed up resolution times and increase customer satisfaction scores (CSAT). 

Here are the key templates to prep for customer service agents:

• Where is my order? (WISMO) response 
• Order shipment update
• Returned/refunded order
• Abandoned cart recovery
• Complaint acknowledgment
• Follow-up emails for prior tickets
• Feedback/survey requests

On Gorgias, you can quickly create a library of templates with Macros. Whenever you need to send a canned response, just click the template or Macro you need and you’re done — no need to type anything out.

🧠 Learn more: 25+ customer service scripts inspired by top ecommerce brands

Use tagging to organize and prioritize tickets

An unorganized inbox can ruin customer experience and risk your highest-value customers. By implementing a system that strategically tags and prioritizes tickets, the customer support team can focus on delivering exceptional customer experiences.

To create a library of useful tags, ask yourself these questions:

• What are the most common inquiries? 
• Which channels receive the most urgent inquiries?
• Which types of tickets require escalation?
• Can you identify high-value customers from the inquiry?

Based on these questions, you can start creating Tags based on the most relevant customer query topics, ticket urgency, high-value vs. low-value tickets, and response urgency. 

Harness automation to streamline workflows

Automating parts of the customer service workflow can be a game-changer. Work with the customer service team to identify the repetitive tasks in their day that they can go without and offload to automation. 

On Gorgias, you can create Rules to…

• Auto-tag tickets. Automatically apply tags to tickets to categorize them based on keywords, issue types, or other criteria for easier tracking.
• Send automated responses. Send pre-written responses (called Macros) to customers based on specific triggers or ticket attributes.
• Assign tickets to specific agents. You can assign incoming tickets to specific support agents or teams based on criteria like keywords or urgency.
• Auto-close resolved tickets. Automatically close tickets when certain criteria are met, such as a customer confirming issue resolution.

Check out our customer service automation guide for more tips on which automations can speed up your support.

How Princess Polly built a seamless customer service operations system

Princess Polly, the leading Australian fashion DTC brand, is an expert when it comes to establishing streamlined customer service operations.

With their priorities set on comprehensive metrics and a constant feedback loop, they entrusted Gorgias to do the heavy lifting. Immediately after using Gorgias, Princess Polly managed to increase their efficiency by 40%, decrease resolution time by 80%, and decrease first response time by 95%.

📚 Read more: Princess Polly improves their CX team efficiency by benefiting from Gorgias-Shopify integration

Optimize your support ops team’s efficiency with Gorgias

Whether you're starting your support ops team from scratch or expanding it, Gorgias can be there to build it with you. With powerful features like Macros for automating routine tasks and detailed support performance and revenue statistics at your fingertips, Gorgias empowers your support ops team to work smarter, not harder. Unlock a new level of productivity by booking a Gorgias demo today.

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TL;DR:

• CSAT measures satisfaction after a specific support interaction, and scores above 80% signal strong performance.
• The fastest CSAT gains come from reducing customer effort, not adding more agents.
• AI handles high-volume, repetitive tickets so human agents can focus on complex issues that actually require judgment.
• Root cause analysis, not symptom-chasing, is what separates teams that sustain CSAT improvements from those that plateau.

CSAT scores are easy to misread. A dip in satisfaction looks like a support problem, so the instinct is to hire more agents or add a new channel. But most CSAT problems stem from disjointed processes and a lack of context. 

The brands consistently earning 4.0 CSAT scores are working smarter. They've automated what doesn't require human judgment, routed what does, and built feedback loops that surface problems before they scale.

This post covers eight strategies for improving CSAT, including how AI fits into each one, and a 30-day action plan you can run with your current team.

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What is CSAT (customer satisfaction score)?

Customer satisfaction (CSAT) score is a customer support metric that measures how a customer feels after an interaction with your brand's customer support. 

Brands measure CSAT by sending out customer satisfaction surveys as a follow-up to customer service interactions. The survey simply asks customers to rate the interaction on a scale from one to five, one being the worst and five being the best.

Unlike other metrics, CSAT focuses on immediate reactions to individual interactions rather than long-term sentiment. The post-interaction survey format delivers real-time feedback that helps you identify problems while they're still fresh.

On top of the numeric score, CSAT surveys also usually include a field for customers to explain why they chose that rating. This qualitative feedback is a hugely important benefit of measuring CSAT because they help you understand your customer support's strengths and weaknesses. Most brands use a Likert scale (one-to-five rating) combined with an optional text field for additional context.

CSAT differs from related metrics in scope and purpose:

• CSAT: Measures satisfaction with a specific interaction
• NPS (Net Promoter Score): Measures long-term loyalty and likelihood to recommend
• CES (Customer Effort Score): Measures effort required to resolve an issue

How to calculate CSAT (and what a good score looks like)

Divide the number of respondents who rated their interaction as 4/5 or 5/5 by your total number of CSAT survey responses. Then, multiply by 100. The number you are left with is your company's overall CSAT score.

The CSAT formula: 

(Number of positive responses / total responses) × 100

Example:

If you have 500 CSAT responses and 400 of those responses are positive (scores 4/5 and above), then your CSAT score is 400/500 x 100 = 80.

However, you can also keep things simple by taking the average of all your CSAT responses and using that as your CSAT score.

Surveys that measure CSAT

Common survey formats include:

• Likert scale (1-5 ratings)
• Emoji-based ratings (happy/neutral/sad faces)
• Binary options (satisfied/unsatisfied)

The 1-5 scale remains most popular because it provides enough granularity to identify trends without overwhelming customers with choices. Some brands also use star ratings, which function identically to numeric scales.

When you send surveys matters as much as how you structure them. The best practice is to trigger CSAT surveys immediately after key interactions — support conversations, order deliveries, or product returns. This timing captures feedback while the experience is still fresh, leading to higher response rates and more accurate data. Most platforms automate this process through post-interaction triggers.

What is a good CSAT score?

A strong CSAT score is considered 4/5 or higher (80%). 

Here are industry benchmarks that provide context for your scores:

• 70-80%: Industry average across most sectors
• 80%+: Strong performance indicating high satisfaction
• Below 70%: Signals need for immediate improvement

Pro Tip: Aim for a CSAT score of 4.8. That benchmark reflects what high-performing ecommerce brands achieve with optimized support operations. Your response distribution also matters — a score of 80% built from mostly 4s and 5s is more stable than one skewed by a few perfect scores and many low ratings.

Why CSAT is a revenue metric, not just a support metric

After analyzing 10,000 brands, we found that raising CSAT by just one point, from 4.0 to 4.9, correlated with a 4% lift in overall revenue.

It’s a simple mechanic: Higher satisfaction drives repeat purchases and increases customer lifetime value (CLV). 

At the opposite end, poor support accelerates churn, forcing higher acquisition spending to replace customers you shouldn't have lost. When you factor in acquisition costs, the economics of bad support are worse than they look on the surface.

Strong CSAT also reinforces word-of-mouth. Customers who have a genuinely good support experience tell people. And the more people who know about your brand’s quality, the likelier they’ll join your customer base.

8 ways to improve CSAT without making your agents work harder

These strategies target specific friction points across the support experience. They work together, but each one delivers value on its own.

1. Meet customers where they already are

Customers don't want to hunt for support. Forcing someone to leave Instagram to send an email, then repeat their issue from scratch, creates friction before the conversation even starts.

Omnichannel support means covering the channels your customers actually use, like email, live chat, SMS, social media, voice. A unified inbox pulls all of those conversations into one place so agents have full context regardless of where the conversation started.

Asynchronous messaging, particularly SMS and social DMs, also reduces wait times. Customers send a message when it's convenient and get a response when it's ready. That flexibility alone improves satisfaction without requiring 24/7 staffing.

2. Shorten your surveys and close the loop on detractors

Long surveys get abandoned. One rating question and an optional comment field is enough. The format matters less than the follow-through.

Every low rating should trigger a follow-up within 24 hours, ideally routed to a senior agent or team lead. The goal isn't to argue with the rating. It's to acknowledge what happened, explain it honestly, and describe what will change.

Detractor themes also belong in your weekly review. If the same complaint appears across five different tickets, that's a process or product issue that needs to go somewhere beyond the support queue.

3. Use quality assurance to raise the floor, not just the ceiling

A team where some agents are excellent and others are inconsistent will have volatile CSAT, even if the average looks acceptable.

Manual QA can only cover a sample of tickets. Auto QA tools use AI to score 100% of interactions against defined standards: response time, tone, accuracy, resolution quality. That coverage gives you a complete picture instead of a representative one.

Use QA data for targeted coaching with real examples from your own ticket queue. Calibration sessions, where the team reviews the same ticket and scores it independently, help align standards and surface disagreements before they affect customers.

Read more: Why your strategy needs customer service quality assurance

4. Find root causes, not just symptoms

A spike in low CSAT scores is a symptom. The cause might be a shipping carrier issue, a confusing product page, a long policy that agents can't clearly explain, or a checkout error.

Tagging is the most practical way to surface root causes at scale. When tickets are consistently categorized by intent, such as order tracking, returns, shipping issues, and product questions, you can track frequency over time. 

For example, let’s say "shipping delay" tickets double in a week. You’ll know that's an operations issue, not customer support.

Sentiment analysis adds another layer. Some platforms can flag negative conversations before a CSAT survey is submitted, which gives you a window to intervene proactively rather than waiting for a bad rating to land.

5. Automate what doesn't require human judgment

A significant share of support volume is predictable. "Where is my order?" "How do I start a return?" "Can I cancel my order?" These questions don't require empathy or creative problem-solving. They require fast, accurate answers.

Conversational AI can handle these intents instantly, at any hour, without a queue. That frees your human agents to focus on the conversations that actually benefit from their judgment: complaints with emotional weight, edge cases, high-value customers with complex needs.

According to the Salesforce State of Service 2024 report, the share of agents who find it difficult to balance speed and quality dropped from 76% in 2022 to 69% in 2024 — a shift largely credited to maturing AI and automation investments.

Common automatable intents in ecommerce include:

• Order tracking (WISMO)
• Returns and exchanges
• Order cancellations
• Discount code requests
• Account management tasks

Self-service options like FAQ pages and help centers extend this further by resolving questions before they become tickets at all.

Read more: How to automate half of your CX tasks

6. Give agents the context they need to stop asking obvious questions

Nothing erodes customer confidence faster than being asked for information the company already has. When an agent asks for an order number that's attached to the email, or doesn't know about a previous complaint, it signals that the company isn't paying attention.

Unified customer context, order history, past tickets, loyalty tier, and preferences surfaced in a helpdesk, cuts that friction immediately. Agents resolve issues faster because they're not spending the first two minutes gathering basic information.

Session replay and customer journey tools add another dimension. When an agent can see exactly what a customer experienced on the site, where they clicked, where they got stuck, what error they saw, diagnosis gets faster and more accurate.

7. Resolve issues on the first contact

First-contact resolution (FCR) is one of the strongest individual drivers of CSAT. Customers who have to follow up, reopen tickets, or repeat themselves are less satisfied even when the issue eventually gets resolved.

Improving FCR usually comes down to three things:

• Routing: Getting the right ticket to the right agent the first time, based on intent and complexity
• Full context at the start: Agents shouldn't have to ask for information that's already available
• Accurate resolutions: Sending the correct answer based on training, knowledge base maintenance, agent helpfulness, and/or tool accuracy

Macros and templates help with speed and consistency, but they need to be personalized at the detail level. A response that's clearly templated but doesn't address the situation is worse than a slow, personal one.

8. Build a proactive follow-up motion

Waiting for customers to complain is a reactive posture. A Gartner survey of more than 6,000 customers found that proactive customer service results in a full point increase in NPS, CSAT, Customer Effort Score, and Value Enhancement Score.

Shipping delay notifications, post-purchase check-ins, and resolution follow-ups reduce ticket volume and signal that you're paying attention.

For example, when something goes wrong, a replacement or a discount isn't enough on its own. The follow-up 24 to 48 hours later, confirming the customer is actually satisfied, is what closes the loop and restores confidence.

Automated outreach can scale this without adding headcount. The key is keeping touchpoints relevant and specific. A generic "how did we do?" message after a complicated return feels hollow. A message that references the specific issue and confirms it was resolved feels like care.

A 30-day plan to increase your CSAT score

Improving CSAT requires sequencing. Quick wins build momentum. Structural changes take longer but deliver more durable results.

Week 1: 

• Audit your current CSAT average
• Identify the top detractor themes
• Shorten your survey to one rating question plus an optional comment
• Establish your baseline metrics dashboard

Week 2:

• Identify your three highest-volume ticket types
• Deploy an AI agent or chatbot for those intents
• Update knowledge base articles to reflect accurate, current information
• Train agents on the new workflows and escalation paths

Week 3: 

• Implement an automatic QA tool to score all interactions
• Schedule weekly coaching sessions using real ticket examples
• Document a service recovery workflow for detractors, including follow-up timing, resolution steps, and satisfaction confirmation

Week 4: 

• Review three weeks of CSAT data
• Refine AI agent guidance based on real conversations
• Recognize agents who improved and share what worked across the team

Most teams see measurable movement in CSAT within 30 days when they follow this sequence. The gains compound when the structural pieces, automation, QA, and root cause analysis, are in place and maintained.

If you want to see how teams use tools like Gorgias to operationalize these strategies across channels, book a demo to walk through a real setup.

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It's tough to point to a single most important metric in customer service. But if we had to, first response time would be a top contender.

First response time (FRT) is the time between a customer asking a question and your team’s initial response. When your FRT is too long, customers are left wondering whether you even received their question, let alone will get them an answer.

"Of course, the best-case scenario is quickly answering the customer's question (or automating the answer). But even if you can't solve the question right away, letting the customer know you received their inquiry — and that it didn't get sent into the void — is great for customer confidence and satisfaction.” —Bri Christiano, Director of Customer Support at Gorgias

Let’s dive into first response time to understand why it’s so make-or-break for your team. Then, we’ll unpack best practices you can use to lower FRT for your team, plus how to use this KPI alongside other metrics to support your overall customer service strategy. 

Why is first response time important in ecommerce?

A quick first response time is a key way to build customer trust, letting customers know right away that you are taking their inquiry seriously and that you will resolve the issue as fast as possible.

Here are a few reasons a strong FRT improves your customer experience and your support team’s impact on the business:

Meet customer expectations 

According to our research, 90% of U.S. customers say an immediate customer service response is “important” or “very important.” Plus, 60% of people who need support want it in 10 minutes or less. 

In other words, near-instant FRTs are important to 90% of shoppers — and after 10 minutes, you’re disappointing over half of your shoppers. 

Drive conversion rate

First-response time is especially important for pre-sales support questions, like "Will this arrive before Christmas?" or "Which size is right for me?". Any customer reaching out about pre-sales support likely needs their questions answered before they commit to click checkout, or before they hop over to Amazon to buy it.  

A speedy response is just the thing to give the shopper the information they need to make a confident purchase decision and boost their trust in your brand — two factors that can contribute to high conversion rates. 

Increase revenue-related KPIs

First response time also impacts other important support metrics, including ones that impact your revenue:

• Resolution time: A fast response time often leads to a quicker resolution — and a customer who’s more likely to cite a positive shopping experience with your brand. 
• Lower return rate: Give a customer a fast response to their questions, especially in pre-sales moments, and they’ll have the information they need to make a confident purchase decision. This lowers the likelihood that they’ll need to return the item later. 
• Higher conversion rate: If a customer has a question about a product, they need a quick response to convince them to click checkout. Otherwise, they’re just going to go to a competitor. 
• Customer satisfaction: Fast response times go a long way to show a customer they are valued. Offer a quick response to increase brand trust, which leads to improved customer satisfaction. 

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How to calculate and track first response time 

Luckily, you don’t have to be a math wiz to find your brand’s first response time.  

Start by simply looking at your tickets. Compare the time the ticket came in with the time a support agent responded. That time difference is your FRT. 

For example, if a ticket comes in at 8 am Monday, and an agent responds at 8 am Tuesday, your response time is 1 day. 

You can also keep track of first response times across a certain period, or from a certain agent, to understand the average response time. Simply collect response times over a certain period, then, divide that number by the total number of resolved tickets during that same time frame. 

The equation looks like this: 

Total first response times during chosen time period / total # of resolved tickets during chosen time period = Average first response time

Here’s what calculating FRT averages looks like, using real numbers: 85,000 seconds / 900 resolved tickets = 94.4 seconds (average first response time) 

That means that, on average, your agents are able to respond to customer tickets within 94.4 seconds of receiving a request (for that period). 

If math isn’t your thing, don’t sweat it. Most helpdesks these days automatically calculate and report on average first response time for you. 

Gorgias calculates important metrics, like first response time, automatically. Plus, you can slice and dice the information to understand FRT by factors like: 

• Channel (email, SMS, social media, etc.)
• Contact reason (to understand what kind of questions to automate)
• Agent (to inform coaching)
• Time period (to understand if it changed after implementing something)

This way, you’re never left in the dark about how your support strategy is performing.  

First response time benchmarks by support channel 

Customers want the option to get in touch with your customer service team on the channel of their choice. Even more, Salesforce reports that 74% of shoppers want a variety of channels to choose from.   

If you’ve adopted an omnichannel support strategy, keep in mind different channels have varying response times. 

We’ve broken down a few of the most popular channels to give you an idea of what to expect — and what response times Gorgias customers achieve, on average. 

Email 

• Stellar: 1 hour
• Above average: 2 hours
• Average: 1 day
• Unacceptable: More than 24 hours

Gorgias customers see an average email FRT of 7 minutes and 57 seconds.  

Chat

• Stellar: Under 1 minute 
• Above average: Under 5 minutes 
• Average: 10 minutes 
• Unacceptable: Over 1 hour 

Gorgias customers see an average chat FRT of 7 minutes and 54 seconds. 

SMS

• Stellar: Under 1 minute
• Above average: Under 5 minutes 
• Average: 10 minutes 
• Unacceptable: Over 1 hour 

Gorgias customers see an average SMS first response time of 59 seconds.

Social media 

• Stellar: A few minutes
• Above average: Under 2 hours
• Average: 1 day
• Unacceptable: More than 1 day

Gorgias customers see a slightly different average FRT depending on the social media platform. 

• Facebook Messenger: 4 hours and 30 seconds 
• Instagram DM: 7 hours and seven minutes 
• Twitter DM: 7 hours and 58 minutes 

Automation is preferable to offer a quick response to your customers. Either an instant automated answer to their question, or an automation to let them know you’re on the way.  

5 tactics to reduce first response time 

Reducing your FRT is a great way to optimize for customer satisfaction. Luckily, there are a few tactics you can take now to reduce FRT that also reduce the load on your support team. 

1. Automate repetitive questions to reduce ticket volume

Automating responses to repetitive customer questions has a two-fold benefit:

• Automating answers with a helpdesk effectively means achieving one-touch resolutions for your most common customer inquiries.
• It reduces the overall number of tickets reaching your agents, letting them focus on high-impact inquiries that automation can’t handle. 

How this works in Gorgias

Gorgias Automate deflects up to 30% of tickets (meaning 30% of customer issues were resolved without human interaction.) If 30% of your helpdesk is cleared, that means you can get to the leftover tickets faster. 

Two great features in Automate are Flows and Article Recommendations, which provide personalized, automated answers to customer FAQs.

Both features give customers a 0-second first response time, but these interactions don’t impact your measured FRT since no ticket is created.

You can then track how much time and money automation saves your customers in first response time:

Take a look at how skincare brand Topicals implemented Flows to help shoppers navigate their product offerings. So, when a customer asks, “How do I find the right face wash?” Flows will ask a series of questions and offer a personalized recommendation based on the customer’s answers. 

2. Automatically send a message that you’re on your way

Even if you can’t use automation to answer a customer question, it can let customers know their message has been received and that an agent is on their way to help. 

Leaving customers in the dark about when they’ll receive a response is likely to make any customer anxious. An automated response not only lowers your FRT by responding immediately, but it also quells your customers’ fears that their questions will not be answered.

"Offer an automated message to fire almost instantly so customers know their question was received and someone will be looking into it shortly. Fire it off regardless of channel — the only exception being if your human agent happens to be available to respond."

—Bri Christiano, Director of Customer Support at Gorgias

Berkey Filters built a Rule using Gorgias to automatically reply to SMS messages as they came in.  

In their message, Berkey Filters starts by thanking the customer for reaching out. It also sets expectations by sharing customer support’s hours of operation. That way, if a customer messages outside of operating hours, they aren’t left waiting for a response. 

By adding in an "If the message from agent is false" condition, it also protects you from accidentally firing off this response if a live agent has already responded.

This is only one example of how to use Rules, or Gorgias automations, to automatically reply to tickets. With Gorgias, you could set this up for any channel, or set up a Rule so that it only fires outside of your set business hours, on live chat, when your agents are away, and so much more.

3. Assign and prioritize tickets automatically 

Some tickets need a more immediate response than others. Angry or upset customers require ticket escalation to try and salvage the relationship and prevent negative reviews, returns, or customer churn. 

Prioritizing your incoming tickets will help your agents lower FRT on tickets that need the fastest responses. They can respond to high-priority tickets first. Any other tickets that automation can’t cover can wait. 

Instead of manually sorting your tickets day in and day out, Gorgias can automatically prioritize tickets as they come in. 

Gorgias makes use of AI to analyze incoming tickets based on natural language processing (NLP). The platform also lets you create Rules to determine a ticket’s priority level. Then, it processes language on incoming tickets using the Rule you set in order to take an automatic action. 

This is also where Gorgias’s deep integration with Shopify really shines. The integration lets you pull in customer information, like order number and order status, to help prioritize tickets. 

For instance, you can prioritize cancellation requests from customers that placed an order in the last 24 hours, to avoid shipping products with the wrong shipping address. You could also prioritize messages from customers who have spent more than $100 (or any amount) from your store, to make sure your VIP customers are taken care of.

4. Drive support traffic to messaging channels (and away from email)

Email is notoriously one of the slowest customer support channels out there. The good news? This aligns with customer expectations: A customer who sends an email isn’t waiting at the computer for a response, whereas one who sends a live chat message probably is.

With all the faster options out there, don’t rely on email as your most prominent support channel. Deprioritize email by adding a live chat option, or by making your email address a little harder to find on your website. Consider also adding a robust Help Center and guiding shoppers toward self-service channels. 

You can easily use email as a springboard to push customers to other, faster channels. 

Berkey Filters does this by using an automated response to inform customers about faster options to connect with an agent. Plus, they share a link to the Help Center, so customers can see if they can find a solution to their problems themselves, without needing human interaction. 

Customers were informed right away that they were placed in the email queue, but were offered the option of texting or joining a chat with a live agent to resolve their problem even faster. 

5. Give your agents templates and Macros

One of the most time-saving tools you can give yourself and your team is templated responses, which help your agents avoid typing messages from scratch, or copy/pasting customer information. 

At Gorgias, these templates are called Macros. These are canned responses you can use to populate answers to customer questions. You can also personalize these responses by pulling data from your Shopify account. 

If you can't automate an answer, the Macro gives your agents a headstart so they aren't wasting time remembering what the right policy is, typing out a message from scratch, or manually copying/pasting the customer's information (like name or order number). 

First response time works best when it’s combined with other metrics

First response time isn’t a be-all, end-all KPI — it’s just one metric, best used in concert with others to get a broader understanding of how your team is performing. 

Average Resolution time

Average resolution time (ART) is the amount of time it takes your customer support team to fully solve a customer’s problem and close the ticket.

Gorgias customers have an average resolution time of 1.67 hours.

Read our guide on resolution time to learn best practices to improve this metric for your brand.

How Average Resolution Time works alongside FRT

The initial response time is vitally helpful to understand how quickly your agents can spring into action, but it’s your resolution time that speaks to how helpful your responses are. 

If you have a great first response time but have unhelpful answers, or just go back and forth with a customer, your resolution time is going to suffer. Calculating both helps you make sure you're balancing speed (FRT) with quality answers that lead to a full Resolution (RT)

OLIPOP grew quickly and needed help from Gorgias to keep up with their exceptional customer support. 

Gorgias helped them reduce Response Time by 88% and Resolution Time by 91%, which led to a 1,200% increase in revenue from customer support. 

"We wanted to make sure customers can reach out to us via any platform and we'd have the ability to quickly answer it all in one place." —Eli Weiss, Director of CX, OLIPOP

📚 Related reading: How OLIPOP decreased their response time by 88% and resolution time by 91% with 25x ROI

CSAT

Customer satisfaction score, or CSAT is an important metric to measure your customer base’s level of satisfaction with their shopping experience. 

The more satisfied a customer is, the more likely they are to become a repeat shopper, refer friends, or leave a great review. 

Using Gorgias, you can automatically send customer satisfaction surveys and track your scores over time. Learn more about our satisfaction survey and dashboard: 

How CSAT works alongside FRT

First response time is a metric that goes hand-in-hand with your CSAT. 

If you slow response time, you can expect your CSAT to be similarly low. A customer who has to wait days for an email response, or several minutes on hold during a phone call is likely to have an unsatisfactory experience. 

Decreasing your first reply times will inevitably increase customer satisfaction.

Read our Director of Support's guide to improving CSAT scores for more guidance.

Contact rate

Customer contact rate is a metric to measure the percentage of active customers in contact with your support team over a specified period. 

Generally speaking, you want your customer contact rate to be low. A low rate means most customers are satisfied with their shopping experience and don’t require further support. 

One tactic to lower your contact rate is to offer more self-service options, like a knowledge base or FAQ. That way, your customers can help themselves with frequently asked questions like “Where’s my order?” or “Do you accept returns?” Then, higher-priority tickets can be tackled by your reps. 

How Contact Rate works alongside FRT

While you want your first response time to be low, even better is reducing your contact rate. 

That means your customers are running into fewer issues that would lead them to reach out to customer support in the first place. Or, that they turn to self-service resources when they do have an issue. 

Gorgias: your ecommerce helpdesk for cutting first response times

If your support agents have to answer every question by hand, or toggle between a dozen different tabs to respond to different challenges, your first-response time will always suffer.

A helpdesk like Gorgias has an immediate positive impact on your FRT because it collects messages from every channel, automatically responds to basic questions, and gives agents powerful tools to respond to messages as fast as possible.

Before implementing Gorgias, Timbuk2’s customer service team took, on average, 2 days to respond to customer inquiries. They knew they needed to centralize and automate their customer support — that’s where Gorgias came in. 

Making the leap to Gorgias helped Timbuk2 streamline its support strategy, gaining a 96% faster response time and a nice 35% boost in revenue. 

"Increased customer support should go hand in hand with revenue growth. We want to turn customer experience into a profit center and we have more opportunities to grow with Gorgias." —Joseph Piazza, Senior Customer Experience Manager, Timbuk2

Gorgias helps ecommerce companies improve their first response time, along with other key metrics, to build exceptional customer experiences that drive revenue. 

‍Sign up for Gorgias or book a demo to start tracking and improving your first response time today!

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TL;DR:

• Customer service drives loyalty and repeat purchases, directly impacting your bottom line
• Quality support reduces acquisition costs by turning customers into brand advocates
• Ecommerce brands use customer service as a competitive differentiator in crowded markets
• Measuring customer satisfaction score (CSAT), net promoter score (NPS), and first contact resolution (FCR) helps quantify the return on investment (ROI) of your support investments
• AI-powered tools like Gorgias scale personalized service without increasing headcount

Customer service isn't just a support function — it's a revenue driver. For ecommerce brands, every support interaction is an opportunity to build loyalty, increase cart value, and turn one-time buyers into repeat customers. Right now, every small business owner is experiencing the frustrations of rising customer acquisition costs, making retention more critical than ever. But scaling personalized service is hard when your team is stretched thin across email, chat, social media, and phone.

This guide covers the top benefits of customer service and how to measure its impact. We'll also explore how AI-powered tools like Gorgias help ecommerce teams deliver exceptional experiences without adding headcount.

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What is customer service?

Customer service is the support you provide to customers before, during, and after they purchase from your brand. It's about answering questions, solving problems, and creating experiences that build trust and loyalty at every touchpoint.

In ecommerce, customer service spans the entire path a customer takes with your brand. Pre-purchase support helps hesitant shoppers make confident buying decisions. During purchase, it addresses checkout issues and payment problems. Post-purchase, it handles everything from shipping questions to returns and exchanges. The best customer service is omnichannel. It meets customers wherever they prefer to communicate, whether that's email, chat, social media, or SMS.

Great customer service includes both reactive support (responding to customer inquiries) and proactive support (anticipating and addressing issues before customers even ask). The role of customer service goes beyond just solving problems — it's about creating positive experiences that keep customers coming back.

Understanding what customer service is and why it matters is the first step. Let's explore how it directly impacts your bottom line.

Customer service vs customer experience vs customer support

These three terms often get used interchangeably, but they mean different things. Understanding the distinction helps you build a more effective strategy for each area.

While customer support focuses on reactive problem-solving, customer service is broader and more proactive. Customer experience (CX) encompasses everything — it's the sum of all interactions a customer has with your brand. The importance of customer support lies in how it contributes to both service quality and overall experience.

The top benefits of customer service for ecommerce growth

The benefits of excellent customer service extend far beyond just keeping customers happy.

Increases customer retention and loyalty

Retention means customers come back to buy again. Loyalty means they prefer your brand over competitors. When you solve problems quickly and treat customers well, you reduce churn rate and increase repeat purchases.

Reduces customer acquisition costs

Customer acquisition costs (CAC) are rising across ecommerce. Keeping current customers costs much less than attracting new ones. Exceptional service turns satisfied customers into advocates who refer friends and family, reducing your dependence on expensive paid channels.

Builds brand reputation and trust

Brand reputation and trust are built one interaction at a time. Great service creates social proof through positive reviews and testimonials that influence new shoppers.

When potential customers see hundreds of five-star reviews highlighting helpful support teams, their brand perception shifts.

Creates competitive differentiation

Competitive differentiation matters in crowded markets. When you sell products similar to competitors, exceptional service becomes your unique selling proposition. Customers will pay more and stay loyal to brands that treat them well.

Increases average order value and upsell opportunities

Average order value (AOV) is the average amount customers spend per transaction. Support teams can increase AOV through strategic upselling and cross-selling. When agents offer helpful product recommendations, it increases cart value without feeling pushy.

Provides actionable customer insights

Customer insights from support tickets are goldmines for product and marketing teams. Support feedback loops reveal pain points, common questions, and feature requests that drive product development. Your team hears directly from customers about what's working and what's not. This voice of customer data helps you make smarter business decisions — from tweaking product descriptions to fixing checkout issues. For example, if dozens of customers ask the same question about ingredient sourcing, that's valuable insight for your product pages.

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Customer service channels that matter in ecommerce

Modern customers expect to reach you on their preferred channels. Omnichannel support means meeting them where they are, whether that's email, chat, or social media.

• Email for detailed, non-urgent inquiries that require documentation
• Live Chat for real-time answers to quick questions during checkout
• Self-service and Help Centers to let customers find answers instantly
• Social media for public conversations that protect your brand reputation
• SMS and messaging apps for order updates and other brief exchanges
• Phone for complex issues where a human connection builds trust

The key is implementing channels based on your customer preferences and team capacity. Don't spread yourself too thin — it's better to excel on three channels than struggle across six.

Common customer service challenges and how to solve them

Even the best support teams face recurring challenges. Here's how to tackle the most common ones:

• Use AI automation and Self-service to manage rushes during peak seasons like Black Friday, Cyber Monday (BFCM)
• Use an omnichannel helpdesk to centralize conversations from all channels
• Use automated routing and Macros to meet service level agreements (SLAs) for response times
• Handling repetitive inquiries: Answering “Where is my order?” hundreds of times leads to agent burnout. Solution: Build robust self-service order tracking and automated responses for frequently asked questions to free agents for complex issues.
• Providing 24/7 coverage with limited team: Small teams can't staff round-the-clock support. Solution: Implement AI chatbots to handle basic questions outside business hours and set clear expectations about response times for after-hours inquiries.

Customer service best practices for ecommerce teams

Great customer service doesn't happen by accident. Here are proven practices that drive results:

Be proactive, not just reactive: Don't wait for customers to complain. Reach out when you spot potential issues like shipping delays. Proactive support prevents negative experiences and shows customers you're paying attention. Set up automated messages to notify customers of delays before they ask.

Use customer data to make conversations feel human. Reference past purchases, use their name, and tailor recommendations to their preferences to build stronger relationships.

Empower customers with Self-service: Build comprehensive FAQ pages and Help Centers that answer common questions. Self-service deflection reduces ticket volume while giving customers instant answers. Include searchable documentation and video tutorials where helpful.

Use automation for repetitive tasks: Automation handles routine work like order status updates and return confirmations. This frees agents to focus on complex issues requiring human judgment and active listening. Use Rules and Macros strategically.

Measure what matters: Track key metrics like CSAT, response time, and resolution rate. Set clear SLAs for different ticket types. Review metrics regularly to spot trends and improvement opportunities. Data drives better decisions.

Close the feedback loop: Collect customer feedback consistently, then act on it. Share insights with product and marketing teams. Continuous improvement comes from listening and iterating. Create a culture where customer input drives changes.

How to measure the impact of customer service

You can't improve what you don't measure. Tracking the right metrics helps you quantify the ROI of your support investments and identify areas for improvement.

• CSAT (customer satisfaction score) to measure satisfaction with specific support interactions
• NPS (net promoter score) to gauge overall brand loyalty and predict growth
• FRT (first response time) to track how quickly your team responds to new tickets
• FCR (first contact resolution) to measure the percentage of tickets resolved in a single interaction
• CES (customer effort score) to measure how easy it is for customers to get help
• Ticket volume and deflection rate to track efficiency gains from Self-service resources
• Revenue from support to track sales influenced by support conversations and prove return on investment (ROI)

For example, a leading ecommerce group increased revenue and improved profitability by using advanced data analytics to measure and optimize their customer experience. Use these metrics together to get a complete picture of performance rather than focusing on just one.

Turn customer service into a growth engine with Gorgias

Looking back on everything we've covered, great customer service drives retention, reduces costs, and creates competitive advantages that directly impact your bottom line. But delivering exceptional experiences at scale is impossible without the right tools.

That's where Gorgias comes in. Built exclusively for ecommerce, Gorgias equips online stores with powerful tools to enhance customer interactions and drive revenue growth.

With deep Shopify integration, omnichannel support, and the new AI Agent, you can automate inquiries. This lets you scale personalized service without adding headcount.

I encourage you to see how Gorgias can transform your support team into a revenue driver. Book a demo to learn how Love Wellness and thousands of other ecommerce brands use Gorgias to turn customer service into their competitive advantage.

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At my company, every single employee — from office manager  to the CEO — must create a Gorgias account and spend 20+ hours answering customer support tickets. It’s an unusual program, but it’s incredibly impactful.

My name’s Amanda Kwasniewicz, VP of Customer Experience at Love Wellness, a brand dedicated to helping women improve their gut, brain, and vaginal health. 

When everyone interacts with customers and learns how customer support operates, we become a more customer-centric, collaborative company. Below, I’ll share more details about this program so you can build something similar at your company.

Why you should have non-support employees answer support tickets

In my eyes, this program truly adds so much value back to the company. It always generates insights and improvements for the CX team (as well as other departments). Plus, it facilitates ongoing collaboration between support and other departments, long after the program ends. 

Here are some specific benefits, each illustrated by real-life wins, to help you understand why this program is so impactful:

Establish respect for support

Customer support was never disrespected. But this program helped the entire company understand how much we’re responsible for. Plus, it gives everyone a better idea of how our work impacts the rest of the business (and vice versa). 

At many companies, all kinds of decisions are made in silos that impact customer experience, and a handful of people on the CX team are left to clean up the mess. This program helps the rest of the company consider the downstream impact on the customer’s experience for whatever they’re working on — whether that’s updating the website, developing a product, or planning logistics. 

In other words, it helps give CX a seat at the table and encourages everyone to think proactively about how their work will impact customers. 

Find areas to improve support

Getting all kinds of skill sets and perspectives into the helpdesk has sparked many smart improvements to the CX team’s processes. A couple of examples: 

• Someone from our Ops team recognized a high number of DNRs (orders the customer never received). They suggested we turn on an “Order delivered” notification so customers can grab the order the minute it hits their doorstep, or can reach out to our team right away if they can’t find it. 
• Another Ops team member suggested an app that tracks delivery issues (like failed delivery attempts and returns to sender). Now that we track these issues, we can proactively reach out to impacted customers to better manage the issue. (By the way, the app we use is Trackhive, but it’s no longer available — a simple app like TrackingMore should work!)

Find areas of opportunity outside of support

When other departments get into the helpdesk, they discover tons of ways their work impacts the customer. This program always sparks ideas for changes in other parts of the business to improve CX:

• The Product Development Team noticed customer complaints about our packaging and pushed our manufacturers to update the packaging so it’s easier to open. 
• A marketing email was sent out with a broken link and an incorrect promotion, which led to an influx of support tickets. The marketing built a new process to test marketing emails before they go live, preventing countless mistakes going forward.
• Our Retail Team discovered a product issue caused by the way retailers stored one of our products. They jumped on the issue, and are now attuned to these kinds of issues, and quickly help solve issues stemming from retail orders. 
• Our VP of Finance learned we had an effective system to track replacement orders and was able to use that data to improve the company’s operational budgeting. 

Improve cross-functional collaboration

Once non-CX employees understand the value and processes of Support, they’re more likely to rope you into conversations and support your team down the road. 

Here are a couple of examples from my experience:

• When the company evaluated a new 3rd-party logistics (3PL) partner, we were roped into the conversation to ensure we chose an option that let us automate more support tasks, like canceling orders and editing addresses.
• During a particularly busy period, our small team of 5 needed help managing the support inbox. 3 non-CX employees (who had previously gone through this program) stepped in to catch up with our inbox. It’s a great strategy to manage the Black Friday — Cyber Monday surge!

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How I structure this kind of program

Getting non-CXers into the helpdesk and answering tickets requires customer service training and guidance. Especially since we’re pulling employees away from their roles, we need to make sure it’s an efficient and effective program. 

Here’s how my team manages it:

Train a cohort every 4-6 weeks

Training new hires one at a time would be a big timesuck for my team. So instead, we train a group of new hires (or anyone else we missed in the past) once every few months or so. For us, groups of 6-8 work well — but adjust for the size of your team. 

Onboarding is a 2-hour session run by me, where we cover the fundamentals of CX, the tools we use, and the processes they need to know to answer tickets. Here’s a checklist of what I cover:

• Customer Experience fundamentals (including Love Wellness’s CX philosophies)
• Where our information lives (the Help Center for customer-facing content, and Guru for employee-facing content)
• Shopify 101: A tour of the checkout flow and order details
• Gorgias 101: A tour of the helpdesk, including how to respond to tickets
• A tour of Macros (listed in the image below), so they rarely have to draft emails from scratch

Set up a dedicated View in Gorgias

During the last 30 minutes of onboarding, we give each employee their own Gorgias login and set them free to start answering emails. To make the inbox more digestible (and steer trainees away from complex emails), we set up a View with simple inquiries as a sort of training ground, in addition to adding them to a Training Team.

We prefer to manually add tickets to this view when the CX team stumbles across simple questions. But you could easily set up an auto-tag to send simple questions — like subscription renewals or requests to edit orders — to this View.

We also have a simple process for trainees to hand off tickets that become complicated to the CX team. They simply send the handoff Macro, which lets the customer know an answer is coming and automatically assigns the ticket to the CX team. 

Require 20 hours of support work over 4 weeks

Once training is complete, the cohort is set free! The expectation is that everyone who participates in this program spends 20 hours on CX over a month. 

How they choose to spend that 20 hours is choose-your-own-adventure style. They can answer 1-2 emails daily, for 3-4 days a week, to meet the 20-hour requirement. During lighter periods, they can also study past tickets or read FAQ content — anything that helps them better understand CX and how we communicate with customers.

Appoint a CX’er to be available for support

While trainees self-guide their 20 hours, one member of the CX team is available to answer questions or jump in to provide support. We also schedule a 30-minute, 1-on-1 shadowing session so the trainee and the CXer can deep-dive on any topics that come up. 

These 1-on-1 sessions are where we spark a lot of great ideas. Naturally, the trainee and the CXer learn more about one another’s departments and processes and find opportunities to collaborate or support one another. 

The CXer that manages the program has a few additional responsibilities over the 4 weeks:

• Monitoring a Slack channel where trainees can ask for help
• Sending weekly updates on each trainee’s stats
• Running a survey to gather feedback from the trainees

How to get buy-in

This program requires 20 hours from every employee, which is no small ask. If you’re excited about implementing something like this at your company, I recommend preparing a business case to convince your boss that it’s worth the investment.

Here are some tips as you prepare your case:

Find an executive champion

I was lucky that a previous boss had an operational background and understood how CX is deeply interconnected with other parts of the business. She was actually the one who suggested this program, and her executive support was essential to put the plan into action. 

If possible, find someone with leadership status to champion this program. They can help convince whoever has the power to approve the program and get the rest of the company excited to participate. 

Regardless of whether you’re trying to implement this program, I want to encourage you to frequently showcase the work of your CX team to executives and the rest of the company. It’s not often that CX gets a spotlight for their work — unless something is on fire. By showing how complex and impactful the team’s work is, you’ll boost team morale and get buy-in for out-of-the-box initiatives like this. 

Emphasize the cross-functional benefits

This program is great for your CX because you’ll get new ideas to improve processes and a trained staff of agents who can step in during busy periods. But the larger benefits — the ones to emphasize when building your case — are the cross-functional collaboration and improvements.

Be sure to underscore how this program orients the entire company to think about CX and adopt a more customer-centric mindset. Plus, share a few examples about how Marketing, Product, and other teams (like Logistics and Wholesale) could refine processes by understanding how their work overlaps with the CX team’s work. 

Share this article

A testimonial from someone with first-hand experience goes a long way — let this article be that testimonial! My anecdotes about the benefits of this program are 100% real, and I’m confident any company could see similar improvements. 

Plus, you’re welcome to use my structure as a template to get started.

Choose a helpdesk with unlimited seats

Most helpdesks charge per user seat, which makes this kind of program impossibly expensive. You’d have to pay for each account, limiting your ability to get additional help in a pinch or share CX insights from customer conversations with the rest of your team. 

One of the (many!) reasons we chose Gorgias is because it allows you to have unlimited users, so every single person in the company can create an account, interact directly with customers, develop a great understanding of CX, and find ways to refine processes and implement customer feedback throughout the business. 

If you haven’t yet, I strongly recommend chatting with the Gorgias team — it’s a no-brainer for any ecommerce brand looking to make their CX more effective and efficient.

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TL;DR:

• Customer service channels are touchpoints where shoppers interact with support teams — including phone, email, chat, social media, self-service, and AI agents
• Modern brands need multiple channels because customers have different preferences, and issues vary in complexity and urgency
• Choose your channels based on customer demographics, journey stage, cost-to-serve, and team capacity
• An omnichannel approach with unified customer data across all channels delivers the best customer experience and highest agent efficiency
• Measure performance with customer satisfaction (CSAT), average handle time (AHT), first contact resolution (FCR), and service level agreement (SLA) adherence to continuously optimize your support strategy

Customers are everywhere, and they expect you to be right there with them. According to McKinsey, over 80% of customers would likely contact multiple channels, including email, live chat, and phone support, if they needed additional assistance. This means expanding where you offer support to meet customer expectations.

A good customer experience isn’t only about the one-on-one interaction between an agent and customer, it’s also about everything else that happens before — including the freedom to choose how they communicate with you.

This guide covers 9 essential customer service channels and how to choose the right mix for your brand. We’ll also show you how to measure and optimize channel performance for maximum efficiency and customer satisfaction.

‎What are customer service channels?

Customer service channels are the touchpoints where shoppers interact with your support team to get help, ask questions, or resolve issues. These channels range from traditional options like phone and email, to digital channels like social media and AI-powered chatbots.

Channels fall into two main categories: synchronous and asynchronous.

• Synchronous channels like phone and live chat enable real-time conversations where both parties are engaged simultaneously.
• Asynchronous channels like email allow customers to send messages and receive responses at different times. Understanding this distinction helps you match the right channel to the urgency and complexity of customer issues.

Most businesses need multiple channels because shopper preferences vary widely — and most prioritize immediacy. According to Gorgias’s customer expectations survey, 76.5% of customers care about fast answers. Choose your channels based on how your shoppers want to talk to you and the types of issues they typically face.

The top customer service channels (2026)

Most ecommerce brands rely on offering multiple channels to meet varying customer expectations and handle issue complexities. 

Here are the top 10 channels to offer for consistently exceptional customer experiences.

Phone support

Phone support remains one of the most powerful channels for resolving complex issues and building customer trust. Despite the rise of digital channels, reliable phone support provides a human connection that is preferred and appreciated across all generations. Voice conversations allow agents to pick up on emotional cues and demonstrate empathy in ways that text-based channels can’t match.

“I’ve seen that a phone call can actually turn things around,” says Bri Christiano, Senior Director of Customer Success at Gorgias. “Some people just need to be heard on the phone, especially people who are more used to having conversations over the phone. I’ve called angry customers, and if you let them speak and hear them out, and repeat back to them their frustrations, that alone will save that customer in the end.”

How it works in customer service:

Modern phone support uses technologies like interactive voice response (IVR) for call routing, automatic call distribution (ACD) to connect customers with the right agents, and computer telephony integration (CTI) to pull up customer data instantly.

Best for:

• Complex issues requiring detailed explanation or troubleshooting
• Urgent inquiries where customers need immediate resolution
• High-value customers or escalated complaints
• Older demographics who prefer voice communication
• Situations requiring emotional connection

Limitations:

• Most expensive channel to staff and maintain
• Agents can typically only handle one call at a time (low concurrency)
• Requires adequate staffing during business hours
• No written record unless call is transcribed
• Can be stressful for agents handling difficult conversations

Email support

Email serves as the primary channel for asynchronous support. Unlike real-time channels, email lets customers explain their issues in detail at their convenience and gives agents time to research and craft thoughtful responses. This makes email particularly valuable for complex inquiries that benefit from documentation and detailed explanations.

Most customers expect a quick response to their issues — and treating an email like the first step before a shopper leaves a bad review helps prevent escalation. If an agent receives a customer service email from an angry customer, a great first step is to apologize right away and take steps to de-escalate the situation with a thoughtful solution.

How it works in customer service:

Modern email support relies on ticketing systems to organize incoming messages, service level agreements (SLAs) to set response time goals, and macros or templates to speed up responses to common questions. Collision detection prevents multiple agents from responding to the same ticket, while threading keeps conversation history organized.

Best for:

• Non-urgent inquiries that don’t require immediate resolution
• Detailed explanations or step-by-step instructions
• Documentation needs where customers want written records
• Product recommendations requiring research
• Follow-up communication after initial contact

Limitations:

• Slower response times compared to real-time channels
• Can feel impersonal without proper personalization
• High volume can overwhelm teams without automation
• Back-and-forth exchanges take longer to resolve
• Email threads can become confusing with multiple replies

Live chat

Live chat provides real-time support directly on your website or app. This channel has become increasingly popular because it combines the immediacy of phone support with the convenience of digital communication.

Shoppers prefer chat because they can multitask while waiting for responses and get help without interrupting their shopping experience. In fact, a 2019 CGS survey found that 86% would rather interact with a human over a bot. 

The team at CROSSNET made use of live chat to quickly handle support tickets, and their efforts resulted in massive growth, including $450,000 USD in a single sale.

How it works in customer service:

Key features of live chat tailored for customer support teams include agent concurrency (handling multiple chats simultaneously), AI agent compatibility, escalation rules for transferring conversations, and transcript history.

Best for:

• Pre-sales questions from shoppers browsing your site
• Quick answers to simple inquiries
• Tech-savvy customers comfortable with digital communication
• Capturing high-intent visitors before they leave
• Order tracking and status updates

Limitations:

• Requires real-time staffing during business hours
• Can feel rushed if agents handle too many concurrent chats
• Limited for complex issues requiring detailed explanation
• Customers may abandon chat if wait times are too long
• Typing speed can slow down resolution compared to phone

SMS & messaging (WhatsApp, Messenger)

Customer service SMS and messaging apps like WhatsApp and Facebook Messenger are quickly rising in the ranks as preferred ways for shoppers to get in touch with brands. A text message is convenient — most people have mobile devices with them, and they’re more willing to respond to a quick text than find your contact page.

One reason for messaging’s popularity lies in fast response times and high engagement rates. Most customers expect to have a response to their message within 10 minutes. OLIPOP has seen an 88% decrease in response time since implementing SMS messaging — powered by Gorgias — in their customer support strategy.

How it works in customer service:

Top brands that offer SMS support include opt-in compliance (customers must consent to receive messages), session messaging windows (time limits for brands to respond), and two-way communication capabilities. 

WhatsApp Business API and Rich Communication Services (RCS) let brands send messages with media and interactive elements.

Best for:

• Order updates and shipping notifications
• Appointment reminders and confirmations
• Mobile-first customers who prefer texting
• Quick questions that don’t require detailed responses
• Younger demographics comfortable with messaging apps

Limitations:

• Character limits can restrict detailed explanations
• Compliance requirements vary by region and platform
• Platform fragmentation (WhatsApp, Messenger, SMS) requires multiple integrations
• Customers may not check messages as reliably as email
• Limited formatting options compared to email

Social media support

Social media platforms like Instagram, Facebook, and X (formerly Twitter) have become essential customer service channels. In fact, 80% of millennials prefer social media to other channels.

Social media support happens in two ways: public interactions through comments and posts, and private conversations through direct messages (DMs). Both are important because public responses demonstrate your commitment to customer service to potential customers, while DMs allow for personalized support on sensitive issues.

A growing number of younger shoppers — particularly Gen Z-ers — treat social media like a search engine, using these platforms to answer their questions about brands and products by scrolling through content created by real customers.

How it works in customer service:

Effective social media support requires social listening tools to monitor brand mentions, rapid-response SLAs to address complaints promptly, and clear escalation policies to move complex issues to other channels. 

“It’s really important to be monitoring social posts, even if you don’t have a massive following,” says Bri Christiano, Senior Director of Customer Success at Gorgias. “These are public platforms where potential new customers are going to look at your brand and see immediately how you engage with customers.”

Best for:

• Public accountability and demonstrating responsive service
• Brand visibility and turning support into marketing opportunities
• Younger demographics who prefer social platforms
• Quick acknowledgments before moving to private channels
• Community building and customer engagement

Limitations:

• Public complaints can damage brand reputation if not handled quickly
• Resource-intensive monitoring across multiple platforms
• Platform dependency and algorithm changes affect reach
• Limited control over conversation flow and format
• May attract trolls or negative attention

Self-service (knowledge base & portals)

Self-service options let customers solve questions and issues on their own. This channel includes knowledge bases or help centers, FAQ pages, and customer portals where shoppers can manage their accounts and orders.

Self-service benefits both customers and support teams. Customers get instant answers, regardless of timezone, without waiting for agent availability. For support teams, self-service reduces ticket volume by deflecting common questions, freeing agents to focus on complex issues that truly require human expertise.

How it works in customer service:

A help center works great when used with automation features like Flows to create a complete self-service experience. It is also the main data source for AI agents to deliver human-like answers to customers.

If you’re not ready to create a comprehensive Help Center, you can start with a simple FAQ page. Check out our free FAQ template generator to get started.

Best for:

• Common questions with straightforward answers
• After-hours support when agents aren’t available
• Scalability as your customer base grows
• Customers who prefer finding answers independently
• Reducing cost per contact through ticket deflection

Limitations:

• Requires ongoing content maintenance and updates
• Can’t handle all issue types or complex scenarios
• Effectiveness depends on article quality and search functionality
• Some customers will always prefer human interaction
• Initial investment in content creation can be substantial

AI chatbots & agents

Unlike chatbots that follow pre-defined decision trees, AI agents use natural language understanding (NLU) to comprehend questions and provide relevant answers independently.

AI agents work 24/7 to provide instant responses even when your support team is off the clock. They excel at answering frequently asked questions, tracking orders, qualifying leads, and guiding customers through common processes. 

One way to meet rising customer expectations is to consider implementing both live chat and AI agents that work in tandem. This way, you can leverage live agents during working hours, then let the bots take over customer queries when it’s time for your reps to clock out.

How it works in customer service:

AI tools made for customer service use guardrails or guidance instructions to ensure it doesn’t violate customer service policy. It’s important for customer service teams to build a smooth handoff process so customers can talk to live agents when AI can’t resolve their issue. 

Off-limit topics for AI may include:

• Angry messages and complaints
• Emotional situations
• Legal and compliance inquiries
• Medical, financial, or health guidance

Best for:

• High-volume repetitive questions like order status and return policies
• 24/7 coverage without staffing overnight shifts
• Instant responses during peak traffic periods
• Qualifying leads before routing to sales teams
• Initial triage to categorize and route inquiries

Limitations:

• Requires training data and ongoing optimization
• Can’t handle all nuance and complex scenarios
• Needs clear escalation path to human agents
• May frustrate customers if responses feel robotic
• Initial setup investment in configuration and testing

Community forums

Online forums provide a space for customers to help one another through peer-to-peer support. Forums work particularly well for brands with passionate user communities or complex products where experienced customers can share expertise.

The beauty of forums lies in the social proof they generate. When customers see that others have successfully solved similar problems, they gain confidence in your product and brand. Build them using free apps and websites, like Discord, Slack, Reddit, or Facebook groups.

How it works in customer service:

Successful forums require moderation to maintain quality and safety. Features like accepted solutions, upvoting, and superuser programs help surface the best answers and recognize valuable community members. Do your research before building from scratch to see if your brand already has a word-of-mouth presence on a third-party forum.

Best for:

• Product communities with engaged user bases
• Technical troubleshooting where customers can share solutions
• Long-tail questions that don’t fit standard documentation
• Building brand loyalty through community engagement
• Reducing repetitive support inquiries through peer answers

Limitations:

• Requires active moderation to prevent misinformation
• Slower responses compared to direct support channels
• Not suitable for urgent issues or account-specific problems
• Community needs critical mass of active users to be effective
• Risk of negative conversations if not properly managed

Video support

Video support enables face-to-face conversations for complex issues that benefit from visual demonstration or screen sharing. This channel combines the personal connection of phone support with the added dimension of visual communication.

Customers appreciate video support when they need to show a product issue, follow technical instructions, or receive personalized guidance. The visual element helps agents diagnose problems faster and provide more accurate solutions, making it ideal for high-touch support in enterprise sales or premium services.

How it works in customer service:

WebRTC for real-time video streaming, screen sharing for technical support, co-browsing for guiding customers through processes, and sometimes facial recognition for identity verification (know your customer, or KYC). 

Bandwidth requirements and scheduling challenges mean video support works best for specific use cases rather than as a primary channel.

Best for:

• Complex technical issues requiring visual troubleshooting
• High-touch support for premium customers
• Product demonstrations and setup assistance
• Visual verification of product defects or damages
• Building personal relationships with key accounts

Limitations:

• Bandwidth and technical requirements can create access barriers
• Scheduling challenges compared to on-demand channels
• Privacy concerns for customers uncomfortable on camera
• Requires stable internet connection for both parties
• More resource-intensive than other channels

How to choose and resource your channel mix

Building the right channel mix requires balancing customer needs with operational realities. Follow these steps:

1. Understand where your customers are

Analyze customer demographics and communication preferences. Topicals uses SMS to connect with Gen Z skincare shoppers, while Comme Avant handles most support through social media DMs.

2. Map channels to the customer journey

Match channels to shopping stages: social media and live chat for awareness, chat and email for pre-sales questions, and phone or video for complex post-purchase issues.

3. Consider cost-to-serve

Phone and video support cost the most because agents must serve a single customer at a time. Live chat is more efficient since agents handle multiple conversations. Self-service and AI agents offer the lowest cost-per-contact after initial setup.

4. Start with pilot programs

Test one channel at a time, measure performance, and optimize before expanding. This staged approach helps you work out operational challenges and validate value.

5. Resource appropriately

Train teams for channel-specific skills — phone agents need empathy and active listening, while chat agents need quick typing and multitasking abilities. Ensure your technology infrastructure supports your chosen channels.

Measure and optimize channel performance

Measurement drives improvement in customer service. Without clear metrics, you can’t identify which channels deliver the best results, where to invest resources, or how to justify your support budget. 

Tracking the right key performance indicators helps you spot trends, optimize operations, and demonstrate the value your support team delivers to the business.

Key metrics to track by channel:

• CSAT (customer satisfaction score): Measures customer happiness with support interaction
• NPS (net promoter score): Measures customer loyalty and likelihood to recommend
• AHT (average handle time): Measures efficiency of support interactions
• FCR (first contact resolution): Measures percentage of issues resolved in first interaction
• SLA adherence: Measures whether team meets response and resolution time commitments
• Occupancy rate: Measures percentage of time agents spend on active support work

Manage all your channels in one place with Gorgias

When your tools don’t integrate, your team wastes time switching between systems, customer data stays siloed, and the experience feels disjointed.

Gorgias provides a unified helpdesk built specifically for ecommerce brands, bringing email, chat, phone, SMS, social media, and more into one inbox. Deep integrations with Shopify and 100+ apps give agents complete context with order data and purchase history — no tab switching required. Plus, Gorgias AI Agent handles 60%+ of tickets automatically, freeing your team to build deeper customer relationships.

Book a demo and see how Gorgias creates the best ecosystem for all your customer service channels.

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TL;DR:

• Customer service chatbots automate repetitive support tasks like order tracking and returns, freeing your team for complex issues
• Modern AI chatbots use natural language processing to understand context and personalize responses across all channels
• Top platforms like Gorgias integrate directly with Shopify and ecommerce tools to resolve tickets without agent involvement
• Look for features like knowledge grounding, omnichannel support, agent handoff, and deflection analytics
• Implementation takes minutes with no-code builders, pre-built templates, and Help Center integration

Customer service chatbots handle support conversations on autopilot, answering questions on your website, chat, and across channels like Instagram or SMS. They take care of the repetitive stuff (tracking orders, explaining your return policy, answering product questions) so your team doesn't have to.

For ecommerce brands, a good chatbot means fewer "Where's my order?" tickets clogging up your inbox, faster responses, and lower support costs. You need one that plugs into your store, can process returns or exchanges, and pulls answers straight from your policies.

This guide breaks down what customer service chatbots actually do, which platforms work best for online stores in 2025, and how to pick and set one up without the headache.

What is a customer service chatbot?

A customer service chatbot is a digital tool that automates support conversations on your website using artificial intelligence. It interprets customer questions through natural language processing (NLP), pulls answers from your knowledge base, and resolves issues without needing your support team.

There are two main types: rule-based chatbots and AI-powered chatbots. Both respond to customer questions automatically, but rule-based bots follow preset scripts and decision trees, while AI bots use large language models to understand context and generate more flexible responses.

For ecommerce businesses, chatbots deliver 24/7 support at scale. They handle repetitive questions (like "Where's my order?" or "What's your return policy?"), reduce wait times, and cut down on ticket volume. When they can't resolve something, they hand off to your team with full context.

Top customer service chatbot picks (quick overview)

If you're evaluating customer service chatbots for your ecommerce brand, here's a comparison of the top 8 platforms. This shortlist highlights key evaluation criteria to help you narrow down your options before diving into detailed feature comparisons.

Best customer service chatbots (2025)

Choosing the right customer service chatbot requires evaluating platforms based on use-case fit, integration depth, and proven resolution rates. Below, we've ranked eight platforms using a comprehensive evaluation rubric that considers ecommerce-specific features, time-to-value, pricing transparency, and customer satisfaction score (CSAT) impact.

1. Gorgias (for Shopify & ecommerce support automation)

Gorgias is a conversational AI platform built specifically for ecommerce brands, with deep Shopify integration and AI automation designed for online retail. Unlike general-purpose helpdesks, Gorgias combines ticketing, AI Agent, and order management in a single platform optimized for common ecommerce scenarios like WISMO (where is my order), returns, cancellations, and product questions.

The platform's AI Agent is trained on your Help Center articles, saved macros, and real-time Shopify data. This enables it to provide personalized responses that pull order details, tracking information, and customer history.

Self-service Flows let customers handle routine requests independently through your chat widget or Help Center. Meanwhile, Shopify Actions allow the AI to execute tasks like editing orders, processing refunds, or canceling orders directly from the conversation.

Gorgias also provides proactive support capabilities, automatically reaching out to customers about shipping delays or abandoned carts. The platform tracks deflection and resolution metrics so you can measure automation impact and continuously optimize your self-service options. Brands using the platform achieve 30-45% ticket deflection while improving response times and customer satisfaction.

Main features:

• AI Agent trained on your help center, macros, and Shopify data
• Self-service flows for order tracking, returns, and cancellations
• Omnichannel support (email, chat, SMS, social, voice)
• Shopify Actions (edit orders, process refunds, cancel orders from chat)
• Agent handoff with full conversation context
• Deflection and resolution analytics
• No-code automation builder with pre-built templates

Ideal for:

• Shopify and Shopify Plus brands
• Fashion, beauty, home goods, and wellness brands
• Teams handling high WISMO and returns volume
• Brands wanting to automate support and drive sales in one platform

Pricing:

• Starter: $10/month (50 tickets)
• Basic: $60/month (300 tickets)
• Pro: $360/month (2,000 tickets)
• Advanced: $900/month (5,000 tickets)
• AI Agent add-on available on all plans

2. Intercom

Intercom’s Fin is an AI-powered chatbot that uses brand knowledge and policies to  answer customer questions. It's particularly strong for businesses that need both support and sales automation in one place, which is why it's popular with SaaS companies and ecommerce brands looking for a unified messaging platform.

Fin AI uses natural language understanding to provide contextual responses and integrates with Intercom's messenger and ticketing system. The platform includes conversation routing, team collaboration tools, and performance analytics. However, ecommerce-specific actions like order management require custom development or third-party integrations.

Pricing:

• Essential: $29/seat/month
• Advanced: $85/seat/month
• Expert: $132/seat/month
• Fin AI Agent: $0.99/resolution (add-on)

3. Zendesk

Zendesk is an enterprise-grade helpdesk with AI-powered chatbot capabilities built in. The platform's AI bot is pre-trained on billions of support conversations, so it handles common customer service scenarios with strong baseline accuracy. It's built for large-scale operations, especially if you need multilingual support or complex routing across multiple teams.

The platform includes robust reporting, workforce management tools, and extensive integrations with CRM and ecommerce platforms. Zendesk's AI features cover intent detection, sentiment analysis, and automated article recommendations. 

The downside: the complexity and pricing can be steep for smaller brands, and ecommerce-specific automation requires additional configuration or apps.

Pricing:

• Suite Team: $55/user/month
• Suite Growth: $89/user/month
• Suite Professional: $115/user/month
• Advanced AI add-on: $50/agent/month

4. Freshchat

Freshchat is a multichannel messaging platform with an AI assistant called Freddy. Part of the Freshworks suite, it offers strong team collaboration features and omnichannel support across web, mobile, email, and social channels. It's a solid fit for growing support teams that need intelligent routing based on agent availability and customer intent.

Freddy AI answers questions from your knowledge base, suggests articles, and handles basic inquiries. The visual bot builder lets non-technical teams create conversation flows without coding. Freshchat integrates with Freshdesk for ticketing and includes basic analytics to track chatbot performance and customer satisfaction.

Pricing:

• Free Plan: Up to 10 agents
• Growth: $19/agent/month
• Pro: $49/agent/month
• Enterprise: $79/agent/month

5. Tidio

Tidio is an affordable AI chatbot and live chat solution built for small ecommerce stores with basic automation needs. The visual flow builder makes it easy to create chatbot conversations without technical skills, and Lyro AI assistant handles common questions using your knowledge base. It integrates with Shopify, WooCommerce, and BigCommerce.

The platform includes pre-built templates for abandoned cart recovery, order tracking, and lead generation. Pricing is accessible for small businesses, with a free plan that covers basic chatbot functionality. Advanced AI features and higher conversation volumes require paid plans.

Pricing:

• Free Plan: 50 conversations/month
• Starter: $24.17/month
• Growth: $49.17/month
• Plus: $749/month

6. Chatfuel

Chatfuel is a chatbot builder specialized for social media platforms like Facebook Messenger, Instagram, and WhatsApp. It's ideal for brands focused on social commerce or influencer partnerships, with robust automation for DMs and social customer service. The platform's strength is its deep integration with Meta, letting you automate responses to comments, messages, and story replies.

The visual builder includes templates for order tracking, product recommendations, and promotional campaigns. Chatfuel can connect via API to pull order data or integrate with your ecommerce platform. 

The limitation: it only works on social channels, so it won't cover your website or other support channels.

Pricing:

• Business Plan: $23.99/month (1,000 conversations)
• Enterprise Plan: From $300/month

7. Kommunicate

Kommunicate is a no-code chatbot platform with flexible AI model support, letting you choose between GPT-4, Gemini, Anthropic, and custom models. This flexibility appeals to enterprise teams that need specific AI capabilities or want control over their AI infrastructure. The platform includes a visual bot builder, live chat handoff, and omnichannel support across web, mobile, and messaging apps.

Kommunicate's strength is its customization options and multi-model support. You can build complex conversation flows, integrate with external systems via API, and create custom AI workflows. 

The limitation: Its flexibility adds complexity, and setup may require more technical expertise than simpler platforms.

Pricing:

• Lite Plan: $83.33/month (500 conversations)
• Advanced Plan: $166.66/month (2,000 conversations)

8. Ada

Ada is an AI-powered automation platform built for large enterprises with global support operations. It specializes in multilingual support across over 100 languages and handles complex conversation flows with enterprise system integrations and detailed performance analytics.

The platform is designed for high-volume support teams needing enterprise-grade security, compliance, and scalability. Implementation includes dedicated support, custom AI training, and ongoing optimization. 

The limitation: enterprise focus means custom pricing and longer implementation timelines.

Pricing:

• Custom pricing only (contact for quote)

How to implement a customer service chatbot

Implementing a customer service chatbot doesn't require technical expertise. Today’s platforms provide no-code builders, pre-built templates, and guided setup. 

The key is approaching implementation strategically: identify your highest-volume use cases, prepare your knowledge sources, and establish clear guardrails before going live.

We recommend following these four essential steps to deploy a customer service chatbot.

Define intents and data sources

Identify your top 10-20 customer questions using ticket data from your helpdesk. Look for repetitive inquiries like "Where is my order?" or "What's your return policy?" These repetitive and simple questions are best for automation.

Next, audit your data sources: Help Center articles, macros, FAQ pages, and past conversations. These become your chatbot's brain. Make sure your content is up-to-date and comprehensive enough to answer variations of each question. Many platforms can import help center content automatically, but review it to fill gaps.

Read more: What makes a great knowledge base for AI?

Choose flow vs. AI assistance

Rule-based flows use decision trees with buttons and predefined paths. They work well for straightforward scenarios like “Track my order” or “Start a return" where the process is consistent. Flows are predictable and easy to test.

AI-powered responses use natural language understanding to interpret open-ended questions and generate answers from your knowledge base. AI handles more variation but requires careful testing to ensure accuracy. Many brands use a hybrid approach: flows for transactional tasks, AI for informational questions.

Train on help center and macros

Connect your chatbot to existing knowledge sources by importing help center articles, saved agent responses (macros), and product information. This grounds the AI's responses in on-brand content and reduces hallucination.

Review your training data for gaps, outdated information, and inconsistencies. The better your source content, the better your chatbot's responses. Plan to update this content regularly as products and policies evolve.

Test, guardrails, and handoff

Before launching, test your chatbot in test mode with real team members asking typical questions. Verify that responses are accurate, on-brand, and helpful. Test edge cases and unusual phrasings to identify gaps in your coverage.

Set guardrails to define what the chatbot should and shouldn't handle. Exclude sensitive topics (account security, payment disputes), set confidence thresholds for escalation, and establish clear handoff protocols. Make sure customers can easily reach a human agent, and that agents receive full conversation context when taking over.

Related: Should brands disclose AI in customer interactions? A guide for CX leaders

Must-have customer service chatbot features

Not all customer service chatbots are built for ecommerce. Here's what to look for: the ability to pull real-time order data, maintain conversation and customer context across channels, and execute actions beyond simple Q&A. 

The best platforms combine knowledge, routing, compliance, and analytics to deliver instant replies without sacrificing customer experience.

Omnichannel support

Look for platforms that maintain channel continuity or omnichannel support. This means your chatbot works consistently across email, live chat, SMS, social media, and voice channels. 

Customers should be able to start a conversation on Instagram, continue it via email, and finish in chat without repeating themselves. The idea is to preserve customer context across touchpoints so the customer experience feels seamless.

Knowledge grounding

Knowledge grounding ensures your chatbot pulls answers from verified sources like your help center, macros, product catalog, and order data rather than generating responses from scratch. This improves accuracy and reduces AI hallucination. Look for platforms that show which source was used for each response so you can identify and fix content gaps.

Did you know? Advanced platforms use retrieval-augmented generation (RAG) to find relevant information even when customers phrase questions differently than your help articles, handling variations and context-dependent queries more effectively.

Guardrails and compliance

Guardrails control what your chatbot can discuss, ensuring it stays within approved topics and escalates sensitive issues to human agents. You should be able to exclude certain subjects (account security, complaints), set confidence thresholds, and define clear AI-to-human escalation rules. This protects your brand and prevents incorrect or inappropriate information.

Compliance requirements vary by industry and region, but most ecommerce brands need GDPR compliance for European customers. Enterprise brands may require SOC 2, HIPAA, or specific data residency controls. Verify that your platform offers encryption in transit and at rest, plus role-based access control to limit which team members can access sensitive customer data.

Related: How AI Agent works & gathers data

Agent assist and handoff

Agent assist uses AI to support your human agents during conversations by suggesting relevant help articles, drafting replies, and summarizing long threads. This speeds up resolution times and keeps responses consistent.

Just as important is seamless handoff. This feature allows conversations to be transferred between AI and human agents. Your agents see everything that happened so customers don't have to repeat themselves. The best platforms let agents review and edit chatbot responses before they're sent, so you maintain quality control during hybrid automation.

Analytics and measurement

Measuring chatbot performance means tracking specific metrics: deflection rate (conversations resolved without agents), resolution rate (successfully resolved), containment (conversations that never escalate), and CSAT (customer satisfaction). These metrics show whether your automation is reducing workload while keeping customers happy.

Look for platforms with detailed reporting on conversation topics, failed intents, and customer feedback. This data shows you where to expand automation, which responses need work, and what new content to create. The best solutions offer real-time dashboards and automated alerts when performance drops below your thresholds.

Benefits of customer service chatbots

The real value for ecommerce brands lies in specific outcomes: reducing WISMO tickets, speeding up returns processing, and freeing agents to focus on complex issues that drive customer loyalty and revenue. 

Effective automation improves customer experience by providing instant answers to routine questions while ensuring complex issues get the human attention they deserve. 

Below are examples of brands who've experienced these benefits firsthand.

24/7 coverage and lower wait times

24/7 availability means customers get instant responses outside business hours, across time zones, and during peak shopping periods. Chatbots handle routine questions immediately, reducing wait times and queue depth so customers with complex issues get faster access to human agents.

Success story: Orthofeet automated 56% of tickets in under 2 months and improved chat first response time by 92%, maintaining service levels without expanding headcount.

Deflection and cost-to-serve reduction

Deflection measures the percentage of inquiries resolved through self-service without agent involvement. High deflection rates directly reduce cost-to-serve, and for brands processing thousands of WISMO and return requests monthly, even 30% deflection represents significant labor savings.

Success story: Arc'teryx achieved a 23x ROI on their AI Agent while freeing agents from repetitive work to focus on meaningful customer relationships that drive loyalty.

Personalization and faster resolution

Personalization means pulling customer-specific data like order history and preferences to provide contextual responses. Rather than generic answers, chatbots can say "Your order #12345 shipped yesterday and will arrive Thursday."

Success story: Caitlyn Minimalist saw an 11.3% uplift in average order value and a 50% sales lift from AI-assisted chats by delivering instant, tailored product recommendations that turn single purchases into collections.

Customer service chatbot trends

AI advancements are driving practical improvements in how chatbots understand context, take actions, and integrate across channels. Here are the key trends shaping the space.

Agentic AI and grounding

Agentic AI shifts chatbots from answering questions to taking actions like initiating returns, processing refunds, or modifying orders autonomously. Grounding ensures AI agents pull information from verified sources before acting, using retrieval-augmented generation (RAG) to combine language model flexibility with knowledge base accuracy, dramatically reducing hallucination.

Low-code orchestration

Low-code and no-code platforms let support teams build and modify automation using visual drag-and-drop interfaces. Pre-built templates for common scenarios like order tracking and returns let brands launch automation quickly, accelerating iteration and letting support teams expand automation coverage without waiting for engineering resources.

Proactive support and triggers

Proactive support initiates conversations based on customer behavior or events like shipping delays, abandoned carts, or back-in-stock notifications. Effective implementations use customer data to personalize outreach, catching issues before they become complaints and creating opportunities to drive purchases.

Omnichannel continuity

Modern chatbots extend beyond web chat to phone support and SMS, with AI voices handling phone inquiries in natural, conversational language. Customers can switch seamlessly between channels—starting a conversation via SMS, continuing on the phone with an AI voice agent, then escalating to a human—without repeating information or losing context.

Customer service chatbot examples

Below are practical examples of how chatbots handle common scenarios across different verticals.

• Ecommerce (returns, WISMO): Chatbots instantly pull real-time tracking data for "Where Is My Order" inquiries and automate return requests by verifying eligibility, processing prepaid labels, and creating returns in your platform — resolving most requests in under a minute.
• SaaS (billing, account): Chatbots handle subscription management by connecting to billing systems like Stripe, letting customers view plans, upgrade or downgrade, troubleshoot failed payments, and manage account access without contacting support.
• Travel (itinerary, rebooking): Chatbots pull real-time booking information like confirmation numbers and gate changes, then handle simple rebooking requests by checking policies, calculating refunds, and processing changes autonomously.
• Telecom (troubleshooting): Chatbots guide customers through diagnostic flows with step-by-step instructions, check network status for outages, and deflect phone calls by handling account inquiries and basic technical issues through voice commands.

How to choose a customer service chatbot

Now that you know what customer service chatbots are and which platforms lead the market, it's time to evaluate which one fits your specific needs. 

The right choice balances capability, ease of implementation, and long-term scalability for your business. 

Use this checklist to systematically assess platforms based on your highest-volume ticket types, required integrations, compliance requirements, and team capabilities.

Core functionality and fit

• Can it handle your top ticket types (order tracking, returns, cancellations, product questions, policy inquiries)?
• Does it support both rule-based flows and AI responses?
• Can it execute actions (process refunds, cancel orders) or just provide information?

Chatbots vs. conversational AI

• Do you need basic information delivery (FAQ answers, policy explanations) or action-taking capabilities (processing returns, issuing refunds)?
• Would a hybrid approach work best — flows for structured tasks, AI agents for complex questions, human handoff for sensitive issues?
• Does the platform offer both options so you can scale from chatbot to AI agent as your needs grow?

Integration and data needs

• Does it offer native integrations with your helpdesk, ecommerce platform, CRM, and marketing automation tools?
• Can it access real-time order status, customer profiles, product inventory, and loyalty data (not just daily batch syncing)?
• Does it integrate deeply with your ecommerce platform (Shopify, BigCommerce, Magento, WooCommerce) to pull real-time order data?

Security and compliance

• Does it meet your compliance requirements (GDPR, HIPAA, PCI DSS, SOC 2)?
• Does it provide encryption in transit and at rest, plus role-based access control?
• Can you control where customer data is stored and processed (data residency)?

Pricing and scale

• What's the pricing model: per-seat, per-conversation, per-resolution, or tiered based on volume?
• What's your total cost of ownership including implementation, ongoing maintenance, and projected conversation volume?
• Can it handle seasonal spikes without performance issues or surprise overage charges?

Get started with customer service chatbots

Implementing a customer service chatbot starts with evaluating your needs. Focus on platforms that go live quickly and deliver measurable deflection within the first week while balancing self-service efficiency with human connection.

Ready to see how Gorgias automates ecommerce support while keeping the personalized experience your customers expect? Book a demo to learn how top brands achieve 30-60% ticket deflection.

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