

TL;DR:
If you're wondering what it costs to add AI Agent to your Helpdesk, you're in the right place. This article walks through how pricing works, what counts as a billable interaction, and how to think about the investment before talking to anyone on our team.
The good news: there are no seat fees, no per-message charges, and no token-based billing. You pay for conversations your AI actually resolves. If you've looked into other AI tools for customer support and found the pricing models confusing or hard to predict, Gorgias AI Agent works differently.
A billable interaction is counted when the AI resolves a customer conversation entirely on its own. The customer asks something, the AI handles it, the conversation closes. That's one interaction.
If the AI can't fully resolve a conversation and hands it to a human agent, that ticket shifts over to your regular Helpdesk plan. It becomes a standard resolved ticket. You're not charged for both.
A few things that don't count as billable interactions:
This matters most for brands coming from seat-based tools. With Gorgias, your whole team can work in the platform. Agent seats are unlimited. Pricing scales with what your AI is actually doing, not with how many people have access.
Understand the difference between seat-based vs. usage-based pricing.
AI Agent is an add-on to your Gorgias Helpdesk plan. The two are priced separately but work together. Your Helpdesk plan covers all the conversations your human agents resolve. Your AI Agent plan covers the interactions the AI resolves on its own.
When you choose a plan, you select how many automated interactions you want included per month. Depending on your plan, that ranges from 90 to 2,500+ interactions, with custom interaction numbers available for enterprise. You can see the full breakdown on the Gorgias pricing page.
Each resolved conversation costs $0.90 on most plans. Starter plans begin at $1 per resolved conversation. You only pay for fully automated interactions, meaning conversations the AI handles from start to finish without a human stepping in.
The main input is your average monthly ticket volume. From there, you estimate how many of those conversations AI could realistically handle on its own.
Order status updates, return requests, and shipping questions tend to be the highest-volume ticket types AI resolves well. AI Agent actions shows the full range of what it can handle, which makes it easier to estimate your starting number.
Your actual automation rate, meaning the share of total tickets the AI ends up resolving, emerges from usage over time. Most brands start with their most repetitive ticket types and expand from there as they see results.
Related: Which Gorgias plan should you choose?
You're charged an overage fee for each additional automated interaction if you exceed your plan's baseline in a given month. The exact rate depends on your plan tier and whether you're on a monthly or annual subscription.
Generally, the higher your plan tier, the lower your overage rate. Annual plans also carry lower overage rates than monthly plans. So if you're regularly going over, upgrading to a higher tier or switching to annual often works out cheaper than paying overage fees month after month.
If you're on a Support + Shopping Assistant plan, the overage rate is $1.50 per interaction across all paid tiers. If you're on a Support-only plan, rates range from $1.00 to $2.00 per interaction on monthly plans, and $0.83 to $1.67 on annual plans, depending on your tier.
For seasonal businesses, forecasting your customer service volume before peak periods is the best way to choose the right plan size and avoid unexpected fees.
At $0.90 per resolved interaction on most plans, each AI resolution costs less than a human agent handling the same ticket. Once you know what a human-resolved ticket costs your business, the comparison becomes straightforward.
For brands building an internal case for the investment, how to pitch AI Agent to your boss covers the ROI framing in detail.
To see what results look like in practice, how 10 brands transformed customer support into revenue has real ecommerce examples.
AI Agent comes with everything you need to set it up, customize it, and improve it over time:
Learn more: Gorgias AI Agent guardrails: What they are and how to configure them
The best way to get a sense of what AI Agent will cost is to look at your own ticket volume and the types of questions your customers ask most. From there, the right plan becomes much clearer.
If you want to talk through the numbers with someone from our team, book a demo and we'll walk through it with you.
If you'd rather keep exploring first, here are a few good next reads:
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TL;DR:
Helpdesk 2.0 starts with the people who use it most: the agents.
We spent time understanding customer support from the agent's seat. What do they reach for constantly? What slows them down? What does a better workday look like?
Everything we found is in this brand-new update.
Conversational commerce is the new standard.
In customer support, this means customers expect context to remain intact wherever they reach out, whether a conversation starts on social, moves to email, or ends on a call.
This new approach to support has also changed the agent's role. Recurring tickets, like order status checks, shipping updates, and returns, are now handled by AI. What lands in the agent inbox are edge cases that require human judgment and troubleshooting, or tickets that require the full picture.
However, the original Helpdesk was built for a different era of support.
Context was separated across views rather than built into the conversation itself. It's something one in five Gorgias customers flagged, through support tickets, NPS surveys, and conversations with our team. So, we got to work.
Helpdesk 2.0 is the result.
Here's a look at everything that changed.
Conversations have a natural rhythm, one that’s already found in every messaging tool we use. We brought that same layout into the helpdesk.
Say goodbye to the 2000s email interface and hello to chat bubbles. This updated design changes how quickly you can orient yourself and resolve the ticket in one go.

Chats with customers now look like real conversations, using the speech bubble style you’re familiar with on popular messaging apps.
Checking a customer's history used to mean leaving the conversation, an extra step that interrupted what should have been a smooth workflow.
Now, past conversations open in a sidebar next to the active conversation. You can view a customer’s full history, search through their timeline, and open prior tickets without going to a new page.

Check past conversations, orders, and customer details in the brand-new Customer Timeline.
Order information is easier to reference than ever. Open a ticket, and you instantly see the customer's recent orders, marked with product images and invoice details at a glance. Need to dig deeper? Click on an order, and the expanded information appears in the same panel.
For teams using custom integrations, apps are fixed in a quick-access integration menu on the right.

See order details, product images, and totals at a glance on the right panel, without leaving the conversation.
You shouldn't have to dig through a thread to figure out what AI already tried. Now you don't have to.
When AI Agent escalates a conversation, it includes a concise handover summary that mentions the issue, what actions were taken, and why it was passed to your team.

Escalated tickets include a brief AI-generated handover summary, marked in yellow, for quick reference.
We restructured and simplified the navigation. The left sidebar organizes everything into clear categories: Inbox, AI Agent, Marketing, and Analytics, so anyone on your team knows exactly where to go.
To quickly update your knowledge base or adjust a workflow, both now live right in the sidebar. For teams managing multiple stores, switching between them is just as straightforward, accessible from the sidebar, so agents can move between inboxes without breaking their flow.

Agents can switch between stores and their corresponding inboxes directly from the left menu.
Support comes down to the person on the other end of the conversation. We built Helpdesk 2.0 is to make sure they have everything they need to show up for that moment.
The best way to see the difference is to work in it. Start a free trial today.
The best in CX and ecommerce, right to your inbox

TL;DR:
The page-based shopping experience dominated for decades. Customers would search, browse, compare, abandon, get retargeted, return, and eventually buy (sometimes).
That journey is no longer the only option.
Shoppers are turning to chat, messaging, and AI-powered tools to find what they need. Instead of clicking through product pages or reading static FAQs, they ask questions, have back-and-forth conversations, and get answers that move them closer to a purchase in real time. The path to checkout has changed, and the brands that recognize this are pulling ahead.
Read our 2026 State of Conversational Commerce Report to learn more about conversation commerce trends from 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
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The traditional shopping journey was a solo experience. A shopper had a need, searched for options, browsed across sessions, and eventually made a decision — often days later, after being retargeted multiple times. Support only entered the picture after the purchase.

The conversation-led journey collapses that timeline:
What used to take days now takes minutes. Discovery, evaluation, and purchase happen in a single thread.
79% of brands agree that AI-driven conversational commerce has increased sales and purchase rates in their business. When brands were asked to rank the highest-return areas:
Those numbers reflect something important: the value of conversation compounds. Faster support reduces friction. Better retention raises lifetime value. More confident shoppers buy more often and spend more per order.
The brands seeing the biggest returns aren't just using AI to deflect tickets. They're using it to create one-to-one shopping experiences at scale.
Looking at AI-only influenced orders across key verticals like Apparel and Accessories, Food and Beverages, Health and Beauty, Home and Garden, and Sporting Goods, the growth across a single year was significant.





Across industries, ecommerce brands saw AI step into conversations, reduce shopper hesitation, and drive higher QoQ conversion rates.
Learn more about AI-powered revenue generation in the full 2026 Conversational Commerce Report.
84% of brands say the strategic importance of conversational commerce is higher than it was a year ago. 82% agree it will be mainstream in their sector within two years.

That shift is registering at the leadership level because of what conversational commerce does to the buying experience. Creating one-to-one touchpoints earlier in the journey drives higher AOV, shorter buying cycles, and stronger purchase rates. Shoppers who get real-time answers to their questions are more confident.
TUSHY, known for eco-friendly bidets and bathroom essentials, is a useful example of what happens when you take conversational commerce seriously.
Bidets aren't an impulse purchase. Shoppers have real questions about fit, compatibility, and installation. Those questions used to go unanswered until the CX team could respond, often after the customer had abandoned the cart.
TUSHY used Gorgias's AI Agent and shopping assistant capabilities to automate pre-sales support. AI Agent engaged shoppers in real-time conversations, addressed their concerns directly, and built confidence at the moment of highest intent.
This resulted in a 190% increase in chat-based purchases, a 13x return on investment, and twice the purchase rate of human agents.
You don't need to overhaul your entire operation to start seeing results. The most effective approach is to start where the impact is clearest and expand from there.
A few places to begin:
Want to see the full picture of where conversational commerce is headed in 2026? Read the full report to explore the data, trends, and strategies shaping the next era of ecommerce.
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TL;DR:
The way shoppers buy online has shifted and customers are at the center.
They no longer want to scroll through product pages, dig through FAQs, or wait 24 hours for an email reply. They open a conversation, ask a specific question, and expect a useful answer in seconds. Brands that can’t deliver these experiences at scale are seeing customer hesitation turn into abandoned carts and lost revenue.
This shift has a name: conversational commerce. It's the practice of using real-time, two-way conversations as your primary sales channel, through chat, AI agents, messaging apps, and voice.
What started as an experiment for early adopters has become a key growth lever, with 84% of ecommerce brands treating conversational commerce as a strategic pillar this year vs. last year.

We surveyed 400 ecommerce decision-makers across North America, the U.K., and Europe to understand how conversational commerce and AI are reshaping the ecommerce landscape. These findings are complemented by aggregated and anonymized internal Gorgias platform data from 16,000+ ecommerce brands.
The State of Conversational Commerce in 2026 trends report breaks down all of the findings, including five key trends shaping the ecommerce landscape.
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A few years ago, adding an AI chatbot to your site that could provide tracking links and Help Center article recommendations was a differentiator. Today, it's table stakes. McKinsey found that 71% of shoppers expect personalized experiences, and 76% get frustrated when they don't get them.
Right now, most ecommerce professionals use AI, with 93% having used it for at least 1 year. Enthusiasm is accelerating quickly, with only 30% of ecommerce professionals rating their excitement for AI at 10/10 in April 2025. Similarly, while AI adoption rose steadily year over year, it reached a clear peak in 2026.

The use cases driving this adoption are practical and high-volume:

These are the tickets that flood brands’ inboxes every day. AI agents resolve them instantly, without pulling teams away from conversations that actually require human judgment.
Explore AI adoption and use case data in more depth in the full report.
The traditional ecommerce funnel, visit site, browse products, add to cart, check out, is losing ground. Shoppers now discover products on Instagram, ask questions via direct message, and complete purchases without ever visiting a website.

Conversational AI is actively increasing revenue, with 79% of brands reporting that AI-driven interactions have increased sales and conversion in their business.

The practical implication is that every channel is becoming a storefront. Creating personalized touchpoints with customers earlier in the journey, through proactive engagement, is impacting the bottom line.
Read the full report to explore how AI conversions have increased QoQ by industry.
Pre-purchase hesitation is one of the biggest conversion killers in ecommerce. A shopper lands on your product page, has a question about sizing or compatibility, can't find the answer quickly, and leaves. That's a lost sale that had nothing to do with your product.
Conversational AI changes that dynamic. When a shopper can ask a question and get an accurate, personalized answer in real time, the friction disappears.
Brands using Gorgias saw this play out at scale in 2025. When AI Agent recommended a product, 80% of the resulting purchases happened the same day, and 13% happened the next day.

Brands are further accelerating the buying cycle through proactive engagement. On-site features such as suggested product questions, recommendations triggered by search results, and “Ask Anything” input bars drove 50% of conversation-driven purchases during BFCM 2025.
Explore how AI is collapsing the purchase cycle in Trend 3 of the report.
There's a persistent narrative that AI is making CX teams redundant. The data tells a different story. 62% of ecommerce brands are planning to grow their teams, not cut them. But the scope of those teams is changing.

New roles are emerging around AI configuration and quality assurance. Teams are investing in technical members to write AI Guidance instructions, develop tone-of-voice instructions, and continuously QA results.
CX teams are also bridging the gap between support goals and revenue goals, as the two functions increasingly overlap.

The result is CX teams that are more technical than they were before. Agents who once spent their days answering repetitive tickets are now spending that time on higher-value work: complex escalations, VIP customer relationships, and improving the AI systems and knowledge bases that handle the volume.
Learn more about the evolution of CX roles in Trend #4.
Despite increasing AI adoption, data shows that ecommerce brands shouldn’t strive for 100% automation. Winning brands are building systems in which AI handles repetitive tier-1 tickets, and humans handle complex, sensitive cases.

AI handles speed and scale. It resolves order-tracking requests at 2 a.m., processes return-eligibility checks in seconds, and answers the same shipping question for the thousandth time without compromising quality.
Human agents handle conversations that require context, empathy, or decisions that fall outside the standard playbook. There are several topics where shoppers still prefer human support.

Successful hybrid systems require continuous iteration, meaning reviewing handover topics, Guidance, and reviewing AI tickets on a weekly basis.
Discover how leading brands are balancing human and AI systems in Trend #5.
The 2026 trends are about expansion and standardization. The 2030 predictions are about what comes next.

Voice-based purchasing is the biggest bet on the horizon. Only 7% of brands currently use voice assistants for commerce, but 89% expect it to be standard by 2030. The vision is a customer who can reorder a product, check their subscription status, or manage a return entirely over the phone.
Proactive AI is the other major shift. Rather than waiting for a customer to reach out, AI will anticipate needs based on browsing behavior, purchase history, and where someone is in their relationship with your brand. Think of it as the digital equivalent of a sales associate who remembers what you bought last time and knows what you're likely to need next.
Explore where ecommerce brands are allocating their AI budgets in the full report.
The brands winning in 2026 are creating smart, scalable systems where AIhandles volume and humans handle nuance. They’re treating every conversational channel as an opportunity to serve and sell.
The data is clear: AI adoption is accelerating, customer expectations are rising, and the revenue impact of getting this right is measurable.
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TL;DR:
Industry benchmarks for ecommerce are hard to come by. Most of what's out there is self-reported, survey-based, or too aggregated to be usable. Teams are left wondering whether their AI adoption is on par with industry standards or if their response times are costing them revenue.
That's a gap we're in a unique position to close.
Gorgias processes millions of customer conversations across thousands of ecommerce brands every day. This has given us a rare, unfiltered view into how the industry operates. But until now, we’ve kept those insights largely internal.
Today, we're making it public with the Ecom Lab.
The result is years of first-party data from thousands of ecommerce brands, packaged into findings that give teams a real foundation to build their strategy on.
The Ecom Lab is Gorgias's public research hub for ecommerce. It publishes insights and reports on AI adoption, support performance, financial impact, and industry trends.
The goal is simple: give teams a real baseline to measure against and to uncover the industry's inner workings.
Metrics that actually move decisions.
The Ecom Lab publishes metrics that matter to ecommerce professionals, including AI adoption rates, first response times, CSAT scores, conversion rates, and ticket intents, all broken down by brand size, GMV tier, and industry vertical.
For the first time, teams can see exactly where they stand in comparison to the broader market.
AI is Everywhere reveals why roughly 4 in 5 ecommerce brands still haven't deployed AI in customer-facing support.
Stop Benchmarking Against the Average argues that support teams should benchmark response times against their specific industry vertical rather than the overall average.
Most Brands are Overpaying for Support breaks down the actual cost of support ticket volume and what happens when AI handles the load.

TL;DR:
You started with a shared inbox, a gut feeling, and a promise to respond within 24 hours. That works until a busy season hits, your team grows, or your founder asks why support costs are climbing, and you have nothing to show them.
Without metrics, you can't explain what's slow, what's broken, or whether your team is actually moving in the right direction.
This guide covers the 14 customer support metrics worth tracking, why each one matters for your ecommerce business, and exactly how to measure them.
Customer support metrics are the numbers that tell you whether your support team is fast, effective, and worth what it costs.
They fall into two buckets. Operational metrics tell you what's happening: how many tickets came in, how fast your team responded, how many were resolved on the first try. Experience metrics tell you how shoppers felt about it: whether the interaction was easy, whether they left satisfied, whether they'd buy from you again.
Both matter. Operational data surfaces where the inefficiencies are. Experience data shows whether those inefficiencies are costing you customers. A three-day first response time is an operational problem. A drop in repeat purchases the following month is the business consequence.
Most small ecommerce teams skip this entirely. It's understandable: when you're a team of two handling 60 tickets a day, measurement feels like a luxury. The problem is that the cost of not measuring is invisible — until it isn't.
Here's what happens when you don't track:
The goal isn't to turn your support team into a data team. It's to have enough visibility that you're making decisions based on what's actually happening — not just what it feels like is happening.
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These metrics tell you how fast your team is operating. They are the first baselines to establish and the clearest indicators of whether your support operation can handle current and future volume.
First response time is the average time between a customer submitting a ticket and receiving the first reply from your team. It is one of the most watched metrics in customer support because it is often the first signal a shopper gets about whether you take their experience seriously.
For ecommerce brands, FRT carries extra weight. A shopper asking about a delayed order or a damaged product is already frustrated. Every hour without a response compounds that frustration and puts a repeat purchase at risk.
How to calculate it: Total first response time across all tickets ÷ total number of tickets
What good looks like: The all-industry median is 6.3 hours, but that number is not your benchmark. According to Gorgias research, FRT varies by 5.5x across verticals at the same GMV. Find your row below:
|
Vertical |
First response time |
|
Hardware |
1.6 hrs |
|
Animals & Pet Supplies |
3.6 hrs |
|
Business & Industrial |
4.0 hrs |
|
Home & Garden |
4.4 hrs |
|
Vehicles & Parts |
4.4 hrs |
|
Electronics |
4.8 hrs |
|
Food & Beverages |
5.1 hrs |
|
Health & Beauty |
5.2 hrs |
|
Baby & Toddler |
5.3 hrs |
|
Sporting Goods |
5.8 hrs |
|
Luggage & Bags |
7.7 hrs |
|
Toys & Games |
8.3 hrs |
|
Apparel & Accessories |
8.8 hrs |
|
Arts & Entertainment |
9.1 hrs |
Source: Gorgias Ecom Lab, median metrics at $10M GMV, March 2026
Tip: Track FRT by channel, not just overall. Your email response time and your live chat response time are not comparable, and averaging them together obscures both.
If your team sees FRT spike during BFCM or product launches, that is expected. The goal is to have a seasonal baseline so you can plan staffing and automation accordingly rather than react after the damage is done.
Average resolution time measures how long it takes to fully close a ticket from the moment it was opened. Where FRT tells you how quickly you acknowledge a customer, ART tells you how quickly you actually solve their problem.
For ecommerce, resolution time varies significantly by ticket type. A question about store hours resolves in minutes. A return involving a third-party carrier can take days. Tracking ART as a single number is a starting point, but the more useful cut is by ticket category: shipping issues, returns, product questions, billing. That breakdown shows you where your process has friction, not just where your team is slow.
How to calculate it: Total resolution time across all closed tickets ÷ total number of tickets resolved
What good looks like: Resolution time ranges from 15.1 hours (Hardware) to 21.9 hours (Arts & Entertainment). Your own historical baseline matters more than the vertical comparison here. Set it early and investigate when it rises.
|
Vertical |
Resolution time |
|
Hardware |
15.1 hrs |
|
Animals & Pet Supplies |
15.6 hrs |
|
Food & Beverages |
15.8 hrs |
|
Health & Beauty |
16.8 hrs |
|
Vehicles & Parts |
17.0 hrs |
|
Business & Industrial |
17.2 hrs |
|
Baby & Toddler |
17.4 hrs |
|
Home & Garden |
19.2 hrs |
|
Sporting Goods |
19.2 hrs |
|
Electronics |
19.4 hrs |
|
Apparel & Accessories |
19.7 hrs |
|
Luggage & Bags |
19.7 hrs |
|
Toys & Games |
20.8 hrs |
|
Arts & Entertainment |
21.9 hrs |
Source: Gorgias Ecom Lab, median metrics at $10M GMV, March 2026
When a ticket requires a human handoff after AI involvement, the median wait before a human picks it up is 10 hours. A third of those tickets are abandoned and never receive a response at all. The brands with the lowest ART are the ones reducing how often tickets change hands.
A consistently high ART on a specific ticket type usually points to a missing self-service resource, a broken integration, or a workflow that needs automation.
First contact resolution rate is the percentage of tickets resolved in a single interaction, with no follow-up required. It tells you how often your team gets it right the first time.
For ecommerce, FCR varies significantly by ticket type. Order status questions and simple policy queries should resolve in one touch. Issues involving carriers, third-party apps, or manual refund approvals often cannot. A low FCR overall is worth investigating, but a low FCR on fulfillment-related tickets may simply reflect your operational reality rather than a support problem.
How to calculate it: Tickets resolved on first contact ÷ total tickets × 100
What good looks like: According to SQM Group's 2024 benchmarking data across 500+ North American call centers, the average FCR rate across all industries is 69%, with retail leading at 73-75%. Those are reasonable targets for an ecommerce support team. World-class is considered 80% or above. If you are below 65%, that is a signal worth investigating before assuming it is a staffing problem.
Ticket volume is the total number of support tickets received in a given time period. On its own it is a simple count. In context, it is one of the most useful operational signals you have.
For ecommerce brands, volume is rarely flat. It spikes around product launches, promotions, and peak seasons. A brand handling 62 tickets on a normal day can see that jump to 600 during a sale. Without tracking volume over time, those spikes are impossible to anticipate and impossible to staff for.
How to calculate it: Total tickets received ÷ time period (day, week, month)
What good looks like: Volume is not a metric you benchmark against peers. It is a metric you benchmark against yourself. The table below shows the median number of support tickets ecommerce brands receive for every 100 orders, by vertical. Use your ratio to forecast volume as your order count grows.
|
Vertical |
Tickets per 100 orders |
|
Electronics |
46 |
|
Vehicles & Parts |
46 |
|
Hardware |
41 |
|
Luggage & Bags |
32 |
|
Home & Garden |
32 |
|
Sporting Goods |
32 |
|
Business & Industrial |
25 |
|
Animals & Pet Supplies |
25 |
|
Baby & Toddler |
24 |
|
Apparel & Accessories |
22 |
|
Health & Beauty |
21 |
|
Arts & Entertainment |
21 |
|
Food & Beverages |
20 |
|
Toys & Games |
19 |
Source: Gorgias Ecom Lab, median number of support tickets per 100 orders at $10M GMV, March 2026
A high tickets-per-order ratio is not a problem to fix. It reflects the complexity of your product and how much customers need to ask before and after buying. The right question is whether you are above or below your vertical peers.
Self-service rate is the percentage of customer inquiries resolved without any agent involvement. A shopper checks your help center, finds the return policy, and moves on without opening a ticket. That is self-service working.
For ecommerce, the opportunity here is significant. Order status, return eligibility, shipping timelines, and product FAQs are all questions that do not require a human to answer. Every one that gets deflected is a ticket your team never has to touch.
How to calculate it: Tickets deflected by self-service ÷ total support interactions × 100
What good looks like: There is no universal benchmark, but Gorgias data gives a useful reference point. The median ecommerce brand self-serves 45% of AI-touched tickets without any human involvement. The top quartile reaches 65%. If you have self-service tools in place and you are sitting well below the median, the gap is usually a content or configuration problem, not a capacity one.
Tip: Track which topics are generating the most deflected tickets. Those are your highest-value self-service investments. Track which topics are failing to deflect. Those are your content gaps.
Read more: FAQ pages: Examples, benefits, and when to add a help center
These metrics tell you how shoppers felt about their interactions with your team. They are the link between support performance and customer loyalty, repeat purchases, and brand reputation.
CSAT is the most direct measure of whether shoppers leave an interaction happy. After a ticket is resolved, customers rate their experience — typically on a scale of one to five. The score reflects the percentage of positive responses.
For ecommerce, CSAT is most useful when it is broken down rather than read as a single number. A team-wide CSAT of 4.2 tells you very little. A CSAT of 3.8 on return-related tickets and 4.6 on product questions tells you exactly where the experience is falling short.
How to calculate it: Number of satisfied responses (4s and 5s) ÷ Total responses × 100
What good looks like: CSAT scores across ecommerce verticals range from 4.45 to 4.66 out of five. If you are below 4.4, that's worth investigating. If you are above 4.6, you're in the top tier.
Customer effort score measures how much work a shopper had to do to get their issue resolved. It is asked as a single post-interaction question: how easy was it to get your problem solved?
The logic behind it is straightforward. Customers who find an interaction effortless are more likely to come back. Customers who have to repeat themselves, navigate multiple channels, or wait through a handoff are not. CES captures that experience directly where CSAT sometimes misses it — a shopper can be satisfied with the outcome but still find the process frustrating.
How to calculate it: Sum of all effort scores ÷ total number of responses (lower scores indicate less effort on a 1-7 scale)
What good looks like: A score of five or above on a seven-point scale is generally considered strong. Below four signals meaningful friction. For ecommerce, returns and exchanges tend to produce the lowest CES scores — if your overall score is healthy but one ticket type is pulling it down, start there.
Tip: CES and CSAT measure different things and are both worth tracking. CSAT tells you if the outcome was good. CES tells you if the process was easy. A brand can score well on one and poorly on the other.
NPS measures how likely your customers are to recommend your brand to someone else. It is asked as a single question: on a scale of zero to 10, how likely are you to recommend us? Respondents are grouped into promoters (nine to 10), passives (seven to eight), and detractors (zero to six).
Unlike CSAT and CES, which measure a single interaction, NPS measures the overall relationship. A shopper can have a smooth support experience and still be a detractor if their broader experience with your brand has been poor. That makes NPS a useful complement to the transactional metrics, not a replacement for them.
How to calculate it: % of promoters - % of detractors
What good looks like: For ecommerce, an NPS above 50 is considered strong and above 70 is exceptional. Below 30 warrants a closer look at where the experience is breaking down across the full customer journey, not just support.
Tip: NPS is most useful when tied to a specific moment rather than sent randomly. Post-purchase and post-resolution are the two highest-signal timing points for ecommerce brands. A detractor after a resolved support ticket is a different problem than a detractor after a first purchase.
These metrics tell you what your support operation costs and whether those costs are justified. They are the numbers that make the business case for headcount, tooling, and automation investment.
Agent performance metrics are the individual-level data points that sit underneath your team-wide averages. They typically include per-agent CSAT, average handle time, and tickets resolved per hour.
Team averages are a useful starting point, but they hide outliers in both directions. One agent with a consistently low CSAT score is invisible when their numbers are rolled into the team total. So is one agent who resolves twice the volume of their peers. Individual metrics surface both.
How to calculate them:
What good looks like: Agent performance metrics are most useful as relative measures within your own team. The goal is to identify your strongest performers, understand what they are doing differently, and use that to coach the rest. A significant gap between your top and bottom performers is usually a training or tooling problem, not a hiring one.
Tip: Use these metrics to coach, not just evaluate. An agent with a low tickets-per-hour rate and a high CSAT may simply be handling more complex tickets. Context matters before drawing conclusions.
Revenue per support interaction measures the dollar value generated from conversations where a support agent influenced a sale — whether by converting a browsing visitor, closing an upsell, or saving a transaction that would have otherwise been abandoned.
Most helpdesks do not track this by default, which is why most support teams are measured purely as a cost center. This metric reframes that. When you can show that your team generated $X in revenue last month through support conversations, the business case for investing in that team changes entirely.
How to calculate it: Total revenue attributed to support interactions ÷ total number of support interactions
What good looks like: There is no established industry benchmark for this metric yet. The more useful starting point is simply turning it on and establishing your own baseline. Once you have a baseline, you can tie specific initiatives — proactive chat campaigns, product recommendation macros, post-purchase follow-ups — to movement in the number.
Tip: This metric is only as accurate as your attribution setup. Make sure your helpdesk is connected to your ecommerce platform so that support interactions can be linked to orders. In Gorgias, this is tracked thanks to its native Shopify integration.
Ticket backlog is the number of open tickets that have not yet received a first response or have been waiting beyond your defined SLA window. It is a snapshot of what is sitting unresolved right now.
For ecommerce brands, backlog is most dangerous during peak periods. A backlog that builds over a promotional weekend compounds quickly: late responses lead to frustrated follow-ups, which add more tickets, which grow the backlog further. By the time you catch up, the damage to your reviews and repeat purchase rate is already done.
How to calculate it: Total open tickets outside SLA window at a given point in time
What good looks like: The goal is zero tickets outside your SLA at the end of each day. In practice, some backlog is inevitable during peak periods. The more useful signal is the trend: a backlog that clears overnight is a staffing or volume spike issue. A backlog that grows week over week is a structural problem that needs addressing before the next peak season hits.
Cost per ticket is the average amount it costs your business to resolve a single support interaction. It is the metric that makes the ROI case for every investment you make in your support operation, from hiring to automation to tooling.
For founders and support managers trying to justify budget, this is the number to know. It turns an abstract headcount or platform cost into a per-unit figure that can be tracked, benchmarked, and improved.
How to calculate it: Total support costs (agent salaries + platform costs + overheads) ÷ total tickets resolved
What good looks like: There is no single benchmark for cost per ticket, as it varies by team size, channel mix, and automation rate. What the data does show is the lever: brands at 50%+ automation rate have AI handling more volume than their entire human team, while averaging just three human agents. That is where cost per ticket drops materially.
If your cost per ticket is rising alongside ticket volume, that is the signal to invest in automation before adding headcount.
SLA compliance rate is the percentage of tickets resolved within your defined service level agreement window. It tells you whether you are keeping the response and resolution time promises you have set for your team.
For ecommerce brands, SLAs are most useful when they are set by channel and ticket priority rather than as a single blanket target. A live chat SLA of two minutes and an email SLA of 24 hours are both reasonable. Averaging them into one number is not.
How to calculate it: Tickets resolved within SLA window ÷ total tickets × 100
What good looks like: Most ecommerce teams target 90% or above for SLA compliance. Below 80% is a signal that your SLA windows are either too aggressive for your current capacity, or that your team has a volume or staffing problem that needs addressing before the next peak period.
Read more: SLA best practices for effective support ticket management
AI resolution rate is the percentage of AI-touched tickets resolved end-to-end without any human involvement. It is the most important metric for any ecommerce brand using automation or AI in their support operation.
Most teams track handover rate — how often AI passes a ticket to a human. AI resolution rate is the inverse, and it is the more useful number. Handover rate tells you where AI failed. Resolution rate tells you what your operation actually costs the shopper and the business.
How to calculate it: Tickets resolved by AI without human involvement ÷ total AI-touched tickets × 100
What good looks like: The median brand resolves 45% of AI-touched tickets end-to-end. The top quartile clears 65%. Every point of movement between those numbers removes a 10-hour median wait, a one-in-three abandonment risk, and a CSAT hit from a shopper's experience.
Tip: A stagnant AI resolution rate is usually a configuration problem, not a model problem. The brands hitting 65%+ are giving AI broader authority, which means more intents covered, more actions it can take, and a narrower escalation policy that reserves humans for judgment calls rather than lookups.
Tracking these metrics across spreadsheets and disconnected tools is how teams end up not tracking anything consistently. Gorgias is an AI-powered helpdesk for ecommerce that centralizes all of it:
The brands that treat support as a growth lever are the ones with full visibility into their operation.
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As you hire more customer service agents, providing quality support across the entire team becomes a major challenge. Without clear rules, agents may each handle key tasks — like building self-service resources or handling refund requests — in different ways.
Fortunately, a good customer service policy helps avoid these problems. But to be truly effective, your policy needs more than platitudes like “Be friendly” or “Respond quickly.” Instead, it should include specific and actionable information.
In this guide, we’ll help you create a useful customer service policy by sharing the five key topics it needs to cover. We’ll also discuss how to write and enforce your policy.
First, let’s start with the basics. Or, you can skip straight to the advice for writing a useful policy.
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.
Customer service policies are among the first documents provided to new agents during their training. They act as cornerstone documents for a business's entire customer service team, since agents can use them during difficult or process-heavy interactions, like customer complaints, order cancellations, and so on.
A customer service policy is an internal document, so you won’t share it publicly. However, you can use it as a foundation and repurpose parts of it into various customer-facing policies (like cancellation or refund policies). These policies help you set customer expectations and reduce repetitive inquiries like "What's your return policy?"
Take a look at how Marine Layer does this in a concise way:

You can share these customer-facing policies in:
While similar, customer service policies and service-level agreements (SLAs) are not the same.
Customer service policies are internal documents that help agents by setting standards and policies. Service-level agreements (SLAs) are external documents that define the expected level of service between a business and its customers. Use an SLA to communicate information like:
If you have SLAs, your policy needs to reference them, as you’ll see in a bit.
For a real-life example, check out Berkley Filters’ Contact page:

Above, Berkey listed the working hours for two of their support channels, as well as their average response time. This is a clear promise to customers that sets their expectations for the level of service provided by Berkley Filters.
While customer service policies vary for each company, they bring some key benefits to all organizations. Specifically, they:
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Even if you're a customer service team of one, we recommend laying the foundations of your customer service policy as early as possible.
Here’s why:
You, and any agents you hire, will be faced with some situations over and over, regardless of business size or industry. The sooner you set the rules for these scenarios, the better your chances of providing consistent service, avoiding confusion, and setting standards for your team.
For online stores, these common situations are:
Team members who handle customer inquiries should know how to deal with these from day 1.
Outside of these situations, you should continue to expand your policy as your customer service team grows. That’s a major aspect of ensuring consistent, high-quality service across a larger team. We’ll discuss some additional policy topics in the next section.
Some elements of the customer service policy will vary depending on company size and industry. For example, a clothing brand's return policy will be different from that one for a brand that sells perishable goods.
However, pretty much all policies should cover the following 5 key topics below.
This is the most important part of your customer service policy. It empowers agents with the knowledge they need to resolve customer issues and provide quality support.
Here are some common workflows to include in this section:
As you can see, there are many scenarios to consider here. Fortunately, once you’ve outlined them, you can easily build a library of message templates around your common processes, so your agents don’t have to waste time typing from scratch.
Gorgias’ version of templates, called Macros, include variables that automatically populate with each customer’s unique information (like names, order numbers, shipping information, and more). This means you may be able to simply pull up and send the relevant Macro without any copy/pasting.

You can also put information about these key policies in useful self-serve resources like FAQ pages or a help center. These empower visitors to instantly resolve simple issues themselves, instead of flooding your team with repetitive tickets (and having to wait for a response).
This is another crucial topic for your agents’ day-to-day that every customer support policy should include. Without prioritization rules, agents can follow their own prioritization logic, resulting in poor response times for urgent tickets.

Here are three prioritization factors to include in your policy:

We have lots of useful advice on this topic, so check out our detailed guide to prioritizing customer service requests.
As we mentioned, SLAs are customer-facing promises about your team's response and resolution times. This information should also be in your policy, so agents are aware of the expectations your SLA sets.
But what if you don’t have an SLA? Well, your agents still need to what standard they’ll be held to, i.e., what “good customer service” means for your company.
That’s why your policy needs to establish a set of customer service metrics or key performance indicators (KPIs), regardless if you have an SLA or not.
First Response Time (FRT) is the primary metric to consider here.
FRT measures how long your agents take to respond to customer inquiries, on average. You can have different FRT targets, depending on the channels you use. For example, a 1-hour FRT might be great for email support, while 1-2 minutes is usually a good target for live chat and SMS.
As Brianna Christiano, Director of Support at Gorgias explains:
“We actually have members of the support team who monitor FRT every hour. This allows us to keep a pulse on our workload and pivot if necessary. If we notice that live chat or SMS inquiries are getting overwhelming, we’ll ask team members who typically do, for example, email support to help with the live messaging channels so we can maintain a low FRT.”
Also, you can use FRT to nudge buyers to try a specific customer service channel.
Let’s take another look at Berkley Filters’ Contact page:

Besides setting expectations, making the average response time public helped Berkley Filters push more buyers toward their new SMS channel.
Other useful metrics for your policy include:


Your support team may be the only direct point of contact with your business for many customers. That’s why it’s crucial to establish that agents’ tone of voice should match the brands’ — whether that’s professional, friendly, or a mix of both.
But this is a pretty broad rule that can be difficult to apply in real-life situations. You also want to add clear examples of what fits within your tone of voice guidelines and what doesn’t.
For instance, starting customer interactions with an energetic tone can be a good foundation. However, agents should adapt to each customer’s tone after the initial contact. After all, annoyed visitors likely won’t respond well to humor or light-hearted conversation.
Also, make sure to add an exhaustive list of words for your agents to use and avoid. For instance, agents shouldn’t sound overly apologetic when discussing fixed company policies (refunds, order cancellations, etc.) with customers. You can instruct them to avoid apologetic language and instead use empathetic — but not overly apologetic — phrases to communicate the facts.
If you use different customer support channels, it’s a good idea to include specific guidelines for them. For instance, call-center agents can be instructed to:
Of course, apply these same tone-of-voice considerations to any customer support templates or self-service resources. All of these are an extension of your brand, and ensuring consistency at the source is mission-critical.
Customer service is much more than responding to tickets. Proactive customer service — where agents make the first move, instead of waiting for people to contact them — can help you exceed buyers’ expectations, drive revenue, and reduce repetitive questions.

If you haven’t tried proactive customer service, here are some ideas you can test and describe in your policy:
Learn more about the best customer service software on the market and how it can help streamline your customer service operations and boost revenue.
Before you dive into the policy’s content, make sure to name your document in a clear way, i.e., “Customer Service Policy” or “[Brand Name] Customer Service Policy”.
No need to get creative with the name. You just need people to be able to find it fast when they need it.
Before diving into writing the policy, consider that it should only cover topics that are specific to the customer service team. Broader topics (like code of conduct or other employee rules) should be part of larger company handbooks or other high-level documents, so the customer service policy doesn’t lose its focus.
In terms of content, it can be useful to separate the policy into two parts.
This first section lays the foundation for the rest of the policy. Your company’s values and mission statement are a common place to start.
For example, Abel Womack — a material handling company — begins the public-facing version of their company’s policy by saying that it “has been established to be reflective of our shared values”, which are integrity, empathy, customer care, and teamwork.

Some policies also include details about the company’s products at this stage. If you sell various complex products, it can be useful to add that information. If not, you can skip it and move on to the meat of the policy.
The second half contains actionable information that helps agents provide excellent customer service.
Writing this part can be tricky, especially if you haven’t done it before. Fortunately, an outline makes the process much easier, compared to starting with a blank page.
Feel free to copy the outline below, which is based on the checklist from the previous section.
📚 Useful Resources: Our free refund and return policy generator & Loop Returns, which automates the returns process.
📚 Useful Resources: Best practices for prioritizing customer service requests.
📚 Useful resources: Detailed guide on evaluating customer service & 25 key customer support metrics.
📚 Useful resources: Our guide on proactive customer service & customer self-service ideas
From here, it’s all about filling in the specifics using your brand’s terminology e.g., “customer service representatives”, instead of “customer service agents”, and so on.
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So, you’ve done the hard work of creating a detailed and actionable customer service policy. Now, let’s get agents to actually use it.
First and foremost, ensure the document is easy to find by:
Also, keep in mind that the policy shouldn’t be a static document. Instead, it needs regular updates as you add new products, team members, and support channels. Entrusting a customer service team member, likely a manager, to keep it updated is a must.
Another key tip for improving enforcement is tying the policy to the metric(s) you use to evaluate agents’ performance. This will keep people accountable and give you an objective way to determine their adherence.
Here’s an example of this idea in action by Brianna Christiano, Director of Support at Gorgias:
“At Gorgias, we use an internal quality metric to gauge the support team’s performance. Each week, managers audit 3 of their agents’ tickets and determine the quality and efficiency of the provided service, based on that metric. This lets us continuously evaluate and reinforce customer service rules and standards.”
Finally, getting managers to shadow new agents is another best practice here. This lets managers reinforce your policy from day 1. Plus, it’s a useful way to check if new agents can satisfy customers’ needs.
After weeks of writing, introducing a new policy to the team feels great. But getting the document out there is only half the battle.
You then need to monitor if the policy is helping you reach your customer service goals.
To do that, keep a close eye on your support metrics (FRT, ART, and so on) in the weeks after the initial implementation.
It’s also crucial to determine if your new policy is truly customer-centric. This means tracking feedback metrics, like CSAT and other customer satisfaction metrics that have a major impact on customer retention.
The evaluation process is as important as creating the policy, so be careful not to overlook it. For additional practical tips, check out our guide to evaluating customer service programs.

TL;DR:
Managing product returns is often one of the most significant expenses of running an online store. Data from Invesp shows that 30% of all products purchased online are returned, compared to just 8.89% of products purchased from brick-and-mortar retailers.
There are several reasons why returns are so common in ecommerce — the most prominent listed in the image below. But regardless of the reason, the bottom line is that your store's bottom line depends on an optimized returns process.
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We’ve already discussed how you can optimize your returns process, but most growing stores need additional help. Thankfully, there are plenty of returns management software tools on the market today that are designed to reduce the expense of returned products without harming customer satisfaction.
In this article, we'll explore what to look for in great returns management software before highlighting the nine best returns management tools available today.
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Returns management is the process of helping customers who need to return an item, whether online to an ecommerce shop or in person at a brick and mortar store. Typically, customers submit a return request, send or bring an item back, and the business restocks the item and credits back the customer.
Ecommerce returns automation is a tool that manages the returns process for online stores using automation and AI.
Instead of relying on manually managing returns and refunds, automation software minimizes human error and accelerates the following processes:
There are several key reasons why returns management software is a valuable tool for any ecommerce business. From helping you automate your returns process to helping you reduce your return rate through insightful data, here are just a few top reasons why the right returns management solution can be highly beneficial:
Managing returns is often a time-consuming process — and an expensive one. According to Axios, returning a $50 item costs retailers an average of $33. And slow, clunky processes are a big part of the issue.
By automating much of your product returns management process, returns management software can make handling online returns much less of a hassle:
📚 Related reading: Our guide to automating customer service processes to save time and improve support quality.
One of the most important things to look for in returns management software is its existing integrations. For example, returns software that integrates with your email marketing platform makes sending out customized shipping updates easy.
Meanwhile, choosing returns software that integrates with your customer support platform makes it easy for support agents to process returns while assisting customers. Below, we’ll link whenever a returns tool integrates with Gorgias to save you the time of searching.
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These are just a couple of examples of the value you gain when your returns management system integrates with the other tools your ecommerce store uses.
84% of shoppers say that they will not purchase from a retailer again after a bad returns experience. So, offering speedy service for returns is mission critical. By streamlining and automating your returns process, the right returns management software can make the process faster and more convenient for your customers.
According to data from Statista, reverse logistics — otherwise known as returns management — cost U.S. businesses a total of $102 billion in 2020 alone. If you want to reduce returns' impact on your store's bottom line as much as possible, it is essential to optimize both your returns process and the customer experience with your products.
To this end, nothing is more important than the customer returns data that you collect. By providing returns data in a clean and organized dashboard, returns management software makes it much easier to draw the insights you need to process returns in a more cost-effective manner. It also offers your customers a better experience, which lends itself to a lower return rate.
📚Recommended reading: Our VP of Success’ guide to evaluating customer service.
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If you are looking for tools that will make managing returns much more efficient and convenient for you and your customers alike, there are several excellent options to consider adding to your tech stack. Here are our picks for the top nine returns management tools.
Next to each tool, we’ll list the G2 review score to help you understand current user satisfaction.
ReturnLogic is a comprehensive solution designed to automate the entire returns process, offering customizable workflows that can automate tasks such as:
ReturnLogic also offers warranty processing for accepting warranty claims from third-party purchases, powerful insights and analytics, and a customizable return portal designed to make returning products more convenient for your customers.
Another key benefit of ReturnLogic is that its return portal is designed to encourage customers to exchange items rather than request refunds, enabling you to further reduce the impact of returns on your store's profits.
See more about ReturnLogic’s integration with Gorgias.
With Returnly, ecommerce store owners can create customized return portals designed to optimize the customer experience and make returns less of a hassle for your customers and support team alike. Along with an attractive and easy-to-use return portal, Returnly also offers a range of automation rules that enable you to control how and when returns get processed.
Finally, Returnly provides detailed analytics and returns data that you can leverage to optimize your returns process further. The result is a well-rounded returns solution that offers everything online store owners need to reduce the expense and hassle of managing returns.
See more about Returnly’s integration with Gorgias.
As one of the more popular returns management solutions today, there's a lot to like about Loop Returns. With Loop Returns, store owners can create a branded return portal complete with automations that streamline the returns process, and feedback forms to generate valuable insights on why customers return their products.
The Loop Returns return portal also encourages exchanges, allowing your store to retain more revenue. Another key benefit of Loop Returns is that it enables customers to use a QR code to return their product rather than printing a shipping label (though Loop Returns does offer customers the option to print a shipping label as well).
📚Recommended reading: Learn how Kulani Kinis Saves $400k in Refunds Using Gorgias + Loop Integration
See more about Loop’s integration with Gorgias.
LateShipment.com is a post-purchase experience platform designed to improve multiple aspects of a store's post-purchase process, including order tracking and returns management.
One of the best features of LateShipment.com is that it provides a litany of order fulfillment data points, including real-time tracking updates that can be sent automatically to customers via email or SMS. Regarding returns management, meanwhile, LateShipment.com offers a customizable return portal complete with real-time tracking and a wide range of rules and automations that you can use to customize and automate your returns process.
Finally, LateShipment.com promises to recover every dollar lost to carrier errors by automatically auditing shipping invoices and requesting refunds when an error occurs, helping your business save on shipping costs.
📚Recommended reading: Learn how to offer your customers free shipping without breaking the bank.
See more about LateShipment.com’s integration with Gorgias.
yayloh is a return management platform that automates and optimises the returns process for fast-growing direct-to-consumer brands, particularly those in the fashion and lifestyle market.
With customisable workflows, yayloh reduces the workload for customer service teams and provides customers with a fully-digital and branded self-service returns experience.
The platform stands out for its focus on return data. yayloh collects and analyses customer feedback in top-tier data dashboards and datasets to help merchants make data-driven product adjustments to reduce returns rates.
With yayloh's all-inclusive solution, brands of all sizes can scale their businesses, boost customer loyalty and reduce returns, all while ensuring a smooth and efficient post-purchase experience for customers.
See more about yayloh's integration with Gorgias.
Unlike many solutions on this list, OrderHive is not designed specifically for returns management. However, OrderHive's excellent inventory management and ecommerce automation features can be incredibly valuable for optimizing your returns process.
For example, OrderHive's real-time tracking features make it easy to provide customers with tracking updates on product exchanges. At the same time, the platform's inventory management tools simplify the process of updating your inventory when returns are processed.
But the real value of OrderHive comes from its wide range of ecommerce automation features. These features enable you to automate an incredibly long list of routine tasks, including tasks associated with returns management — such as processing returns and updating inventory levels.
🧰 Tool: Want to update your returns policy? Use our free template generator to get started.
The features offered by Return Rabbit might not be anything all that new or revolutionary, but Return Rabbit is very good at what it does nonetheless. With Return Rabbit, ecommerce store owners can:
Similar to other tools on this list, Return Rabbit encourages exchanges via customized product recommendations presented to customers in the return portal.
📚 Recommended reading: The best Shopify apps for growing your ecommerce business.
12Return is a returns management solution designed for both brick-and-mortar and ecommerce stores. For ecommerce stores, 12Return offers the ability to create both branded return portals and merchant dashboards designed to simplify the returns process for customer support agents.
12Return also provides customizable automation rules for authorizing returns and automating a wide range of returns management tasks.
Perhaps the most unique feature of 12Return is local returns processing, which enables customers to ship returned products to a local 12Returns hub for a faster and more efficient returns process.
ReverseLogix is a platform that offers everything you could want from a returns management solution, along with a few unique features you probably won't find anywhere else.
ReverseLogix boasts standard returns management features such as:
However, they also offer features such as configuring returns workflows based on priorities such as sustainability and cost-effectiveness, and a Repairs Management module for managing part replacements and warranty-based repairs.
Another nice feature of ReverseLogix is its detailed reporting, designed to provide insights into your returns process and the customer's experience with your products.
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Ordoro is a comprehensive order fulfillment platform that can manage orders and returns. With Ordoro, you can look forward to a long list of order fulfillment features, including:
If you are looking for an all-in-one solution to order fulfillment, inventory management, and returns management, then Ordoro is a great option to consider.
Want more suggestions? Check out our list of 150+ top ecommerce tools or our list of the best shipping software for ecommerce.
Managing returns is one of the necessary evils of running an online store. With the right returns management software, you can greatly mitigate the expenses and hassles associated with returns management.
Integrating these solutions with a powerful customer support platform such as Gorgias makes them even more beneficial. The ability to integrate with a wide range of returns management solutions is just one of the features that make Gorgias the premier customer support solution for ecommerce stores.
With Gorgias, you can create automated customer support workflows to assist with returns management and other customer support tasks. Along with these powerful automation rules, Gorgias also offers live chat support, a centralized customer support dashboard, advanced customer support reporting and analytics, and so much more.
To see for yourself how our industry-leading customer support software can enhance your returns process and your ecommerce business as a whole, sign up for Gorgias today!

On Instagram, the most common types of engagement are likes and comments. For likes, you can’t do much about them, but you can take advantage of Instagram comments to drive more engagement, build relationships with followers, increase customer trust, and even boost conversions.
If your business has a strong presence on Instagram, you may receive a lot of comments from followers. That means you have a higher chance to turn comments into your advantage.
But sometimes, it’s easier said than done, right? With a flood of comments every day, you may struggle to respond and manage them effectively.
That’s why this post is for you. You’ll learn several Instagram comment ideas to interact with your followers and some useful tips to monitor comments without losing your mind.
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The average post on Instagram receives 285.48 comments, taking into account posts of highly influential users. Mention found that 26% of Instagram users love to comment on or share personal Instagram Stories.
Why do people comment on others’ posts?
The reasons are many. For example, they want to ask a question, give feedback, share a personal perspective, add to discussions, or interact with a community. Sometimes, they feel so resonated with a story that they want to start a conversation.
Whatever the reasons, the Instagram comments section gives you a huge opportunity to communicate with your followers and discover potential customers.
Here are three main reasons why you should create an Instagram comment strategy:
Think this way: if you’ve uploaded a photo and received 20 comments within only five minutes, you probably have a lot of following on Instagram, or your content is very engaging, right?
The opposite is true as well. If you get a few comments whenever you publish a post despite having a huge following, your engagement rate may be low. In this case, you should probably rethink your Instagram comment strategy.
When a customer mentions you on Instagram, a lot of eyes are on you. How you handle that can tell a lot about your social media management and customer service. If you respond to it tactfully, it shows you care about your customers and take control of the situation.
Meanwhile, choosing to shy away and remain silent will lead to people bad-mouthing your brand. And as you might know, words can travel fast.
By providing great customer service through Instagram comments, you not only retain existing customers but also win new ones.
Below are Instagram comment ideas and tips you can apply right away. Note that there is no one-size-fits-all answer – every comment and every situation is different. Use the following as a reference to create the right strategy for your business.
When customers ask a question, they want an answer instantly. This is true, especially if the question is about product availability, price, or shipping issues.
Aim to respond to Instagram comments within 24 hours. This way, you can build trust with your followers and leave them a good impression of your business.
Look at all of Dannijo’s posts, and you can see they respond to comments within minutes, if not seconds. No wonder they have great engagement.

Using Instagram Quick Replies is a great way to do that. This cool feature allows you to create draft messages for commonly asked questions, like “what is the shipping cost?” or “can I return the item?”

Whenever you want to use those messages, just insert the “quick reply” instead of typing out the same message multiple times.
You can use Instagram Quick Replies on mobile devices (iPhone and Android). But this feature is only available for Instagram business accounts. So make sure you set up an Instagram business page beforehand.
Like other social networks, Instagram is about two-way conversations. But we don’t join Instagram to talk with bots – we want to share, discuss, and speak with humans. We seek real, genuine connections.
That’s why brands must be human when interacting with followers on Instagram. Speak to them like you’re already in a relationship with them, as if you’re good friends. Avoid using a formal and distant tone.
You should take customer queries and complaints seriously, but there are times when you can add a bit of humor to entertain a conversation. According to Hootsuite, “entertaining content is one of the top five reasons people follow particular brands or individuals online.”
Think about when you saw an animated GIF on Tumblr or a funny tweet. You couldn’t help but sharing it with your circle, right? That’s why adding a touch of humor to your Instagram comments can be helpful to connect with your audience instantly.

Make a good joke, and your followers will share it with their followers. Some of those followers will start following you to get more jokes, and your outreach will grow exponentially. More followers, more customers. It’s as simple as that.
Emojis aren’t common in Instagram posts, but comments too. More and more brands are responding to their Instagram comments with emojis.

Emojis are friendly, fun, and engaging. They’re great for humanizing your brand and connect with followers quickly.
A worthy note is that before using emojis, ask yourself if it aligns with the tone of your brand. Make sure you understand the meanings of different emojis so you can use them the right way.
It’s also important to understand whose comment you’re responding to. Just because you see other followers using emojis doesn’t mean everyone is okay with them. Learn more about your target audience to create an emoji marketing strategy that makes sense for your business.
A thank-you comment is necessary when someone gives you a compliment or mentions you on Instagram. Something as simple as “Thank you” or “Thanks” or “Glad you like this one” is more than fine. If they called out specifics in their comments, try to respond with a similar level of personalization. Show them your appreciation.
Another tip is when saying thanks to your followers, try to expand the conversation. If a follower said they were happy with your order, you could ask them why they liked it. Let them know you’re available to support them whenever they need help.
If a customer reaches out to your Instagram with a question or a customer service issue, you must respond to them. You should provide that support.
Here are some helpful tips to handle followers’ complaints on Instagram:
If a follower’s question is complicated and requires a wordy answer or needs more time to fix, you ask for their email address in the comments and send the full response through email.

It’s an opportunity for you to impress your follower with the high level of customer service you provide. Ensure you let the follower know you’ll contact them via their email.
A lot of people will tell you to ignore or delete negative comments on your Instagram posts. But wait… rethink before you do that.
Of course, dealing with difficult customers is never easy, and it only gets more challenging when both of you don’t understand each other or the customers expect more than what you can offer.
Despite that, it isn’t a smart move to delete comments. Why? Because the difficult customers might do the following:
With all that being said, it’s obvious that you should come up with a strategy to handle negative comments, instead of just deleting them.
A good tactic is to reply to those comments or direct message commenters with an apology. Then, ask for more information about why they made that statement. Explain you need this information to figure out the best solution for them.
If the person continues to be an issue after you’ve attempted to resolve the matter, try to move the conversation to a private space (like an email) or block them when necessary.
It seems a lot of work, but keep practicing that. It’ll help improve your brand’s online presence and make people remember your excellent customer service.
If you just start using Instagram for your business, commenting on other posts is a good idea. Doing that will help you identify your target audience, understand what they need, expand your brand awareness, and drive engagement to your Instagram profile.
You can comment on your followers’ posts, influencers’, or the posts of brands that are relevant to your niche.

If you’re struggling with identifying who you should start interacting with, look at your recent collaboration or co-marketing projects. Then, start engaging with them.
Have you ever glanced at your (hundreds of) Instagram notifications and feel tired of replying to your followers’ comments? You see many comments on some much older posts and don’t know which one to start with. AGRH. You get lost.
If you’re in this situation, the first thing you should do is set a specific time to handle Instagram comments. Give yourself windows of time when you’re pleased to respond to those messages. Doing that can help you remove distractions, maintain concentration, and increase productivity.
The second tactic is to use an all-in-one customer service tool like Gorgias.
Think this way: Your customers aren’t on Instagram only. They may also follow your business on Twitter and Facebook. Some of them may prefer connecting with you via email, SMS, or phone call. Others might often visit your website and find it convenient to chat with you via chat box.
That’s where tools like Gorgias (and other social media apps that integrate with your Shopify store) come in handy.
Gorgias' social media features allows you to centralize all customer requests and comments across channels into a single dashboard. You can easily manage every customer interaction on Instagram (for instance: Instagram comments, Instagram ads comments, Instagram mentions), emails, and other messages – using only Gorgias is enough to deliver an exceptional omnichannel customer experience.
Gorgias also helps streamline your team collaboration. When someone comments on your Instagram, a corresponding ticket is automatically created. You can solve the ticket right away using macros, change its status, or assign it to another agent. Everything will be done inside Gorgias without you logging into your Instagram app.
Take the time to go through Instagram comments and address them. Show your followers that you care about them, appreciate their engagement, and strive to maintain relationships with them. The more you do that, the more your followers want to stick with you and support your business.
Interested in using Gorgias to monitor Instagram comments and customer inquiries on other channels? Sign up for a Gorgias account today and discover all the premium features our ecommerce ticket management help desk offers.
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TL;DR:
You're building your ecommerce store the right way. Researching payment processors before you launch means you understand that checkout directly impacts sales.
Whether you're comparing Stripe, PayPal, Square, or Shopify Payments, the decision comes down to a few key factors: security, fees, customer experience, and whether the processor can grow with your business.
Let's dive into what payment processing actually is, how to evaluate your options, and which processor fits your needs so you can set up checkout once and focus on growing your store.
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Ecommerce payment processing is the system that lets online stores accept digital payments securely. When a customer checks out, their payment information moves through a series of steps that verify the transaction and transfer funds to your store.
Unlike older systems that redirect customers to third-party pages, modern payment processing keeps customers on your site throughout checkout. They enter their card details, the system encrypts the data instantly, and authorization happens in the background.
Every transaction involves three core parts working in sequence:
Every transaction follows four steps that happen in seconds:
When a customer submits payment at checkout — whether by card, digital wallet, or buy now, pay later — the payment gateway immediately captures and encrypts their information using SSL/TLS protocols. Modern gateways are embedded directly in your checkout, so customers never leave your site.
The payment processor receives the encrypted data and forwards it to the card network, such as Visa or Mastercard. The network routes the request to the customer's issuing bank, which checks if they have sufficient funds, if the account is in good standing, and if any fraud rules are triggered. The bank approves or declines the transaction.
The authorization response travels back through the same path: issuing bank → card network → processor → gateway. Your customer sees the result in real time, usually within two to three seconds. If declined, they can try another payment method. If approved, the transaction moves to settlement.
Settlement is a batch process that happens separately, typically once per day. Your acquiring bank requests funds from the customer's issuing bank for all approved transactions. Settled funds appear in your merchant account within one to three business days and are then available for transfer to your business bank account.
Offering multiple payment methods reduces cart abandonment and meets customer preferences at checkout.
Here are the four major categories every ecommerce brand should consider:
The right processor balances cost, security, customer experience, and growth potential. Here's what to evaluate:
Choose a PCI-compliant processor that handles security for you through hosted payment forms or tokenization. Look for built-in fraud tools like 3D Secure 2.0 (biometric verification), AVS (address verification), and CVV checks. These protect against fraud while keeping approval rates high for legitimate customers.
Offer the methods your audience prefers. At minimum, accept major cards (Visa, Mastercard) and at least one digital wallet (Apple Pay or Google Pay). Consider adding BNPL for higher-ticket items. North American customers typically use cards, wallets, and Affirm, while European customers favor PayPal, Klarna, and iDEAL.
If you sell globally, ensure your processor handles multi-currency settlement, local payment methods, and dynamic currency conversion. Be aware that cross-border transactions carry higher fees and longer settlement times.
Tokenization replaces card data with secure tokens you can store and reuse, enabling one-click checkout for returning customers while reducing your PCI compliance burden.
Check for native integrations with your ecommerce platform (Shopify, WooCommerce, BigCommerce), CRM, accounting software, and support tools like Gorgias. Seamless data flow between systems reduces manual work and errors.
Most processors charge 2.5–3.5% plus $0.10–$0.30 per transaction, monthly fees of $0–$50, and $15–$25 per chargeback. Interchange-plus pricing is most transparent for high-volume merchants. With payout timing, most settle in one to three days, but faster options exist for a fee.
Select a provider with 24/7 support and the ability to handle traffic spikes during peak events, add new sales channels, and expand internationally as you grow. Payment issues directly impact revenue, so reliable support matters.
Security protects your customers and your business. A data breach or fraud problem can damage your reputation and trigger fines. Here's what to look for:
PCI DSS is a set of security rules required by card companies to protect customer payment data. It's mandatory, but you don't need to become a security expert.
Choose a processor with hosted payment forms or tokenization. Customer card details go directly to the processor, never touching your server. This means the processor handles complex security requirements for you. Without this, you risk fines and could lose the ability to accept payments.
Look for processors with built-in fraud protection:
Chargebacks happen when customers dispute charges, often because they don't recognize the transaction or had a delivery issue. If more than 1% of your transactions become chargebacks, you'll face higher fees or lose your account. Each chargeback costs $15-$25, even if you win.
Choose a processor with early alerts (before disputes become official) and tools to fight unfair disputes. Prevent chargebacks by using clear billing descriptors, visible refund policies, order tracking, and fast customer support.
Resolving problems before customers call their bank saves money and headaches. Tools like Gorgias AI Agent help you respond quickly and issue refunds when appropriate, stopping disputes before they start.
If you're just starting out and wondering "Should I use PayPal or Stripe?" — you're asking the right question. The answer depends on your platform, technical comfort, and where you're selling.
Here are the main options:
Provider |
Best For |
Pricing Model |
Key Features |
|---|---|---|---|
Shopify Payments |
Shopify-native stores |
2.9% + $0.30 USD |
No third-party fees, Shop Pay, fast payouts |
Stripe |
Customization and global scale |
2.9% + $0.30 USD |
API flexibility, 135+ currencies, subscriptions |
PayPal |
Brand trust and fast acceptance |
2.99% + $0.49 (US) |
Instant trust, PayPal wallet, Venmo, Pay in 4 |
Square |
Unified POS + online for SMBs |
2.9% + $0.30 online |
Free POS, simple pricing, in-person + online |
Adyen / Checkout.com |
Enterprise and multi-acquirer |
Custom (interchange-plus) |
Payment orchestration, global reach, 100+ methods |
BNPL and wallets |
Add-on methods |
Varies by provider |
Increase conversion and AOV on mobile |
Built directly into Shopify with no setup hassle. Accepts all major cards plus Apple Pay, Google Pay, and Shop Pay. The big win: no extra 0.5-2% fee that Shopify charges for third-party processors. Payouts are fast, reporting is unified with your orders, and fraud protection is automatic. Only downsides: Shopify-only, limited countries, and strict policies for certain industries.
The go-to for businesses that need flexibility or plan to scale globally. Supports 135+ currencies and payment methods from cards to wallets to local options like iDEAL. Great API if you want custom checkout flows. Pricing starts at 2.9% + $0.30, but setup requires some technical knowledge and support can be slow for smaller accounts.
Everyone knows PayPal, which means customers trust it immediately. Fast approval (often same-day), accepts cards plus PayPal balance, Venmo, and Pay in 4 installments. Pricing is 2.99% + $0.49. The trade-off: reporting is clunky and support quality varies.
Perfect if you sell both online and at markets, pop-ups, or a physical location. Free POS hardware connects to the same dashboard as your online store. Simple pricing: 2.9% + $0.30 online, 2.6% + $0.10 in-person. Includes business tools like invoicing and payroll. Best for small businesses—less suitable if you need heavy customization.
For large brands processing high volumes. Advanced features like payment orchestration and 100+ payment methods, but requires technical resources, longer onboarding, and volume minimums.
Most processors let you add Affirm, Klarna, Afterpay, Apple Pay, and Google Pay through integrations. These boost conversion, especially on mobile and for higher-priced items. BNPL providers charge 2–6% but often increase average order value enough to justify the cost.
Your payment processor directly influences whether customers complete checkout or abandon their cart. Keep these best practices in mind:
Choose a processor with embedded checkout so customers never leave your site. Redirects to third-party pages kill trust and increase abandonment — in fact, 22% of customers bail due to slow or complex checkout. Display recognizable payment logos (Visa, Mastercard, PayPal) and SSL security badges to reassure customers their data is safe.
Mobile shoppers don't want to type card numbers on small screens. Offer Apple Pay, Google Pay, and Shop Pay for one-tap checkout with biometric verification. Fast mobile checkout also increases impulse purchases at the point of sale.
Enable one-click checkout for repeat customers using tokenization, where the processor stores secure tokens instead of actual card numbers. This is critical for subscriptions and mobile shopping. Offer multiple wallet options (Shop Pay, PayPal, Apple Pay, Google Pay) so customers can choose their preference.
Failed transactions, refund requests, and order questions all need fast resolution, or customers get frustrated and file chargebacks. Slow support costs you sales and increases chargeback fees.
Payment processing is just one piece of running a successful online store. Once your checkout is set up, focus on the other fundamentals:

TL;DR:
Ecommerce merchandising is the strategic presentation of products to drive sales and create better shopping experiences.
With online shopping more competitive than ever, how you showcase products can make or break a sale.
This guide shows you how to optimize product discovery, improve the customer experience, and boost revenue.
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Ecommerce merchandising is the practice of strategically presenting products to drive sales and improve the shopping experience.
Think about a physical store. Products aren't randomly thrown on shelves — merchandisers place bestsellers at eye level, create enticing displays, and use signage to grab attention. Ecommerce merchandising works the same way, just digitally.
The goal is to put the right product in front of the right customer at the right time. The advantage? You can optimize in real-time based on customer behavior, purchase history, and browsing patterns — something brick-and-mortar stores can't easily do.
This includes organizing your product catalog, optimizing search and filters, creating compelling visuals, personalizing recommendations, and fine-tuning your product pages to convert browsers into buyers.
Merchandising directly affects your revenue because it influences every step of the customer journey from product discovery to checkout. Here's why it should be a top priority:
Your customers expect personalization. They don't want to dig through generic product pages or wrestle with basic search. They expect experiences that adapt to their preferences and recommendations that feel hand-picked. If your site feels one-size-fits-all, you're already behind.
Your competition isn't just down the street. It's everywhere. Customers can comparison shop across dozens of stores in minutes. If they can't quickly find what they want on your site, they'll bounce to a competitor who makes it easier. You're not just competing locally anymore. You're up against every online retailer worldwide.
You have data physical stores can only dream of. You can test product arrangements, track which layouts convert better, and adjust your strategy in real-time based on actual behavior. That's a massive advantage, but only if you use it.
Effective merchandising has four foundational building blocks. Here's what you need:
Building an effective merchandising strategy requires a systematic approach, not guesswork. Follow these five steps.
Review your catalog organization, search performance, and conversion data. Identify which products are easy to find and which are buried. Check search analytics to see where customers struggle and where they drop off. This baseline shows you where to focus.
Establish what success looks like. Choose 3-5 key metrics—conversion rate, average order value, search exit rate—that align with your business objectives. Clear KPIs let you measure impact and prove ROI.
Identify key touchpoints: homepage, category pages, search, product pages, checkout. Understanding this flow helps you prioritize which areas to optimize first and where merchandising has the biggest impact.
Start with high-impact, low-effort improvements like fixing broken search, adding recommendations, or streamlining category navigation. Quick wins build momentum and show stakeholders what's possible.
Set up a testing framework with regular analytics reviews, A/B testing processes, and customer feedback channels. Merchandising isn't one-and-done. It requires continuous refinement.
These are the foundational must-haves for any ecommerce store:
✅ Optimize your search functionality – Implement autocomplete, synonym mapping, and smart filters so high-intent shoppers can actually find what they're looking for.
✅ Use high-quality product media – Include multiple angles, zoom functionality, videos, and lifestyle shots. Customers can't touch products online—visuals bridge that gap.
✅ Display social proof prominently – Add reviews, ratings, customer photos, and trust badges on product pages. Customers trust other customers more than your marketing copy.
✅ Ensure mobile responsiveness – Make sure you have responsive design, touch-friendly navigation, and fast loading. 61% of searches happen on mobile.
✅ Show real-time inventory – Display accurate stock levels and low-stock alerts. Nothing kills trust faster than letting customers buy unavailable products.
✅ Optimize checkout flow – Offer guest checkout, multiple payment options, transparent pricing, and progress indicators. Every friction point increases abandonment.
✅ Track Core Web Vitals – Monitor LCP, INP, and CLS. Aim for sub-3-second page loads. Slow pages kill conversions.
Track these six KPIs to understand how your merchandising impacts revenue. Metrics turn opinions into data-driven decisions.
The percentage of visitors who buy something. This is your most direct measure of merchandising success.
Example: If 100 people visit your site and 3 buy, your conversion rate is 3%. Track this by traffic source, device, and product category to spot where you can improve.
The average dollar amount customers spend per transaction. Growing AOV through bundles and recommendations increases revenue without needing more traffic.
Example: If you make $5,000 from 100 orders, your AOV is $50. If product recommendations bump that to $55, you've added $500 in revenue from the same number of customers.
Total revenue divided by total visitors. This combines conversion rate and AOV into one number that shows overall merchandising effectiveness.
Example: 1,000 visitors generate $3,000 in sales = $3 RPV. If your merchandising gets that to $3.50, you've gained $500 per thousand visitors.
The percentage of people who leave after viewing just one page. High bounce rates mean navigation problems or customers not finding what they expected.
Example: If 60% of homepage visitors bounce immediately, something's wrong. It could be unclear navigation, slow loading, or irrelevant content.
The percentage of customers who search and then leave without clicking any products. This directly measures search quality.
Example: If 40% of people search for "running shoes" and then exit, your search isn't showing them relevant results. Fix this by improving synonym coverage and result relevance.
Total revenue a customer generates over their entire relationship with your brand. Good merchandising makes repeat purchases easy through personalization and seamless experiences.
Example: A customer makes their first $50 purchase, then returns for three more $40 purchases over two years. Their CLV is $170—much more valuable than a one-time buyer.
Testing and optimization approach:
Pro Tip: Your support team sees patterns that metrics can't capture. Combine quantitative data with qualitative feedback from customer conversations. Pre-sales customer support can go a long way toward boosting sales by assisting customers with issues that might otherwise prevent them from converting.
Once your foundation is solid, these tactics drive growth. Use them to differentiate your store and boost conversions beyond the basics.
Show "Because you bought X" recommendations, tailor homepages by customer segment, and use dynamic content based on browsing history.
Guide uncertain shoppers with quizzes that recommend products based on their needs and preferences.
Create thematic collections ("Summer Essentials," "Work From Home Setup") that reduce decision fatigue and inspire purchases.
Use product bundles, tiered discounts, and free shipping thresholds to increase average order value without constant discounting.
Trigger automated chats based on behavior like reaching out when someone views high-value products or lingers on checkout.
Let customers "try on" products virtually or see 360-degree views to boost confidence and reduce returns.
Extend your merchandising to Instagram, TikTok, and other platforms where customers already shop.
Use machine learning to adjust product rankings, predict demand trends, and personalize at scale.
Organizing your store and displaying products to customers is just one element of creating a customer experience optimized for revenue generation.
Gorgias extends your merchandising strategy through three key capabilities:
AI Agent answers product questions instantly, provides recommendations, and handles order inquiries without human agents.
Customer data integration means agents see browsing history, cart contents, and past purchases to make personalized suggestions during support conversations.
Proactive engagement through chat campaigns can re-engage cart abandoners or offer help at key decision points in the customer journey.
When merchandising and support work together, you reduce pre-purchase support inquiries because product pages answer common questions. You turn support conversations into sales opportunities by equipping agents with context and product knowledge.
See how Gorgias helps ecommerce brands turn support into a revenue driver. Book a demo.
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TL;DR:
Shoppers expect instant, personalized responses across every channel they use. Poor communication drives churn, while great communication drives retention and repeat purchases. Customer communication is the two-way dialogue between your brand and shoppers at every touchpoint. This article covers what customer communication is and why it matters for your bottom line. We also cover which channels to use and eight strategies to improve your approach with automation, personalization, and the right tools.
Customer communication is the ongoing, two-way dialogue between a brand and its shoppers across all touchpoints. Unlike one-way marketing like email blasts or ads, customer communication is responsive and interactive, addressing individual needs and questions.
The scope includes pre-purchase questions, order tracking emails, support tickets, feedback surveys, and proactive outreach like shipping delay notifications. Customer communication management (CCM) is the strategic approach to managing these interactions at scale. It ensures consistent, helpful responses that build trust and drive revenue.
Effective customer communication spans multiple touchpoints:
Customer communication covers support, sales, retention, and feedback across the entire customer lifecycle. It's not just reactive support when something goes wrong. It includes proactive engagement like abandoned cart reminders, restock alerts, and post-purchase check-ins.
This communication spans awareness (social media responses), consideration (live chat with product questions), purchase (order confirmation emails), post-purchase (tracking updates and support), and retention (loyalty program messages). Every interaction shapes how shoppers perceive your brand and whether they'll buy again.
CRM (customer relationship management) systems manage customer data and relationships, tracking purchase history, preferences, and lifecycle stage. CCM focuses on creating, delivering, and optimizing the messages you send using that data.
They complement each other: CRM provides the customer context, while CCM uses it to personalize communication. Integration creates a unified customer view, enabling consistent messaging across all channels and ensuring every interaction feels relevant and timely.
Great customer communication drives measurable business outcomes: higher retention, increased customer lifetime value (CLV), improved CSAT scores, and reduced cost-to-serve. Responsive, helpful communication builds trust, which strengthens brand perception and creates loyalty.
Poor communication, on the other hand, leads to churn, negative reviews, and lost revenue. A report from Emplifi found that 15% of U.S. customers say they're likely to leave a brand after a single negative experience. In ecommerce, where shoppers have endless options, communication is a competitive advantage.
The risks of poor communication include:
Responsive, personalized communication increases repeat purchases and CLV. When shoppers feel heard and valued, they're more likely to return. Reducing churn by even a small margin has an outsized impact on revenue, since acquiring new shoppers costs more than retaining existing ones.
Great support can also translate to better reviews and word-of-mouth, which directly generate more revenue. According to a Podium report, 47% of customers are willing to spend more at a business with higher reviews. The report also found that 41% of customers say reviews are the most important factor when choosing a business.
Consistent, helpful communication builds trust over time. Trust drives loyalty, referrals, and positive word-of-mouth. Shoppers remember how you made them feel, not just what you sold them.
Strong communication reinforces brand perception. When every interaction is professional, empathetic, and on-brand, shoppers see you as reliable and customer-focused. This perception influences purchase decisions and willingness to recommend your brand.
When communication fails — slow responses, inconsistent information, impersonal messages — shoppers get frustrated. This leads to abandoned carts, negative reviews, and lost sales. Churn is expensive and often preventable with better communication.
A single poor experience can undo months of marketing effort. Shoppers who feel ignored or misunderstood are unlikely to give you a second chance.
Ecommerce brands communicate with shoppers across multiple channels: email, live chat, SMS, social media, phone, and help centers. Choosing the right channel depends on urgency, complexity, and customer preference. This is often called the "right medium" decision. Use synchronous channels like chat and phone for urgent issues, and asynchronous channels like email and help centers for less time-sensitive inquiries.
Map channels to lifecycle stages for maximum impact. During awareness, shoppers engage on social media and help centers. During consideration, they use live chat to ask product questions. At purchase and post-purchase, email and SMS deliver order updates and support. Retention efforts use proactive email, SMS, and loyalty programs.
Omnichannel consistency matters: the same brand voice and accurate information across all channels reduce confusion and build trust. Tools like shared inboxes and unified platforms help maintain this consistency at scale.
Each channel has strengths based on urgency and complexity:
Choose sync channels (chat, phone) when urgency and complexity are high. Choose async channels (email, help center) when shoppers can wait for a response or prefer to resolve issues independently.
Match channels to where shoppers are in their journey:
Aligning channels with lifecycle stages ensures shoppers get the right information at the right time through their preferred medium.
Omnichannel consistency means delivering the same tone, messaging, and information across all channels. This builds trust and reduces confusion. Shoppers should feel they're talking to the same brand whether they're on chat, email, or social media.
Tools like shared inboxes, templates, and brand guidelines help maintain consistency. A unified platform ensures reps have full context, so shoppers don't have to repeat themselves when switching channels.
Effective communication requires intentionality: every message should have a purpose and align with customer needs. A strong strategy includes four elements: delivering the right message, assigning the right messenger, using personalization, and engaging in proactive outreach.
Better strategy leads to higher CSAT, lower churn, and more revenue. Shoppers notice when brands are responsive, consistent, and genuinely helpful.
The right message is accurate, helpful, relevant, and timely. Clarity and conciseness matter: shoppers want answers, not paragraphs. Tone should be empathetic, professional, and on-brand.
A right message checklist:
Decide who should respond based on the inquiry. AI and automation can handle simple questions, like tracking status or return policy inquiries. Complex or sensitive issues require a human agent, and sometimes a specialist.
Routing and escalation ensure the right person (or bot) handles each inquiry. Internal collaboration tools like shared inboxes provide visibility and enable smooth handoffs between team members.
Personalization means using customer data — name, order history, preferences — to tailor messages. Shoppers expect brands to know them. Seventy-five percent of consumers are more likely to purchase from brands that offer personalized online experiences.
Personalization tactics include:
Tools like CRM integration and customer data platforms make personalization scalable. Automation can pull in order numbers, tracking links, and purchase history to create customized responses instantly.
Proactive communication means reaching out before the shopper asks. Examples include order tracking updates, shipping delay notifications, and product restock alerts. Proactive outreach reduces support volume and builds trust by keeping shoppers informed.
Feedback loops involve listening to customer input, acting on it, and closing the loop by telling shoppers what changed. This shows you value their opinions and creates a continuous improvement cycle.
Key tools for effective customer communication include a helpdesk or shared inbox to centralize conversations, automation to handle repetitive tasks, a knowledge base for self-service, chatbots for instant responses, and CRM integration to personalize at scale.
These tools work together to streamline communication. A unified platform like Gorgias combines helpdesk, automation, AI, and CRM integration into one system, making it easier to manage conversations across channels.
A helpdesk is a centralized platform for managing all customer conversations. It pulls in messages from email, chat, social media, SMS, and phone into one place. A shared inbox lets multiple agents see and respond to messages, eliminating duplication and ensuring nothing falls through the cracks.
Automation uses rules, macros, and AI to handle repetitive tasks like order tracking updates and FAQ responses. For example, Gorgias offers Rules to auto-tag and route tickets, Macros for templated responses, and an Automation add-on with AI Agent to resolve common inquiries instantly.
Automation frees up reps to focus on complex issues while ensuring shoppers get fast responses to simple questions. Using Gorgias' automation tools, luxury jeweler Jaxxon not only saw a 17% drop in live chat tickets, but a 46% revenue boost.
A knowledge base is a library of help articles, FAQs, and guides that shoppers can search independently. Self-service empowers shoppers to find answers without contacting support, reducing ticket volume and providing 24/7 availability.
Benefits of self-service include:
Tools like help centers, chatbots, and FAQ widgets make self-service accessible. Check out Gorgias's live chat solution to add self-service flows directly to your website.
CCM platforms manage the creation, delivery, and optimization of messages, while CRM systems manage customer data and relationships. Integration is key: CRM provides customer context (order history, preferences, CSAT scores), and CCM uses that context to personalize and deliver messages.
Modern platforms like Gorgias combine both: a helpdesk with CRM-level data visibility and CCM-level message management. This unified approach reduces tool sprawl and ensures consistent, data-driven communication.
Measuring communication effectiveness helps you identify gaps, optimize strategy, and prove ROI. Key metrics include first response time (FRT), average response time (ART), resolution rate, CSAT (customer satisfaction), NPS (net promoter score), and quality assurance (QA) loops.
These metrics tie directly to business outcomes: faster responses lead to higher CSAT, better resolution reduces churn, and strong NPS drives referrals.
FRT (first response time) measures how quickly you respond to a new inquiry. Speed matters: shoppers expect fast answers.
ART (average response time) tracks the average time across all responses in a conversation. Maintaining swift average response times keeps shoppers engaged and satisfied.
Resolution rate is the percentage of inquiries resolved without escalation. Higher resolution rates mean shoppers get answers on the first try, reducing frustration and repeat contacts.
Improve these metrics with automation, smart routing, and ongoing agent training.
CSAT (customer satisfaction score) is a post-interaction survey rating, typically asking "How satisfied were you with this interaction?" It provides immediate feedback on individual conversations. Learn more about how to improve CSAT score.
NPS (net promoter score) measures likelihood to recommend your brand. It's a broader gauge of overall satisfaction and loyalty.
QA loops involve reviewing conversations, coaching agents, and identifying trends. Use feedback to refine templates, update training, and continuously improve communication quality.
Implementing a customer communication strategy takes planning and iteration. A 30-60-90 day roadmap provides quick wins early while building toward long-term optimization. Real-world examples show how brands use omnichannel communication and automation to reduce response times, increase CSAT, and lower support costs.
Days 1-30: Audit your current communication channels, tools, and metrics. Identify gaps like slow response times or missing channels. Set clear goals: improve FRT, increase CSAT, reduce ticket volume. Choose quick wins like adding FAQ articles or setting up basic automation rules.
Days 31-60: Implement quick wins. Create automation rules for common questions like "where is my order?" Build out your help center with FAQs and guides. Train your team on new tools and processes. Start tracking key metrics to establish baselines.
Days 61-90: Optimize based on data. Analyze which automation rules are working and which need refinement. Expand self-service options based on common ticket themes. Measure ROI by comparing ticket volume, response times, and CSAT scores to your baseline.
Brands that combine omnichannel support with automation see measurable improvements. By centralizing conversations from email, chat, social media, and SMS into one platform, teams respond faster and maintain context across channels.
Automation handles repetitive inquiries, freeing agents to focus on complex issues. The result: reduced response times, higher CSAT scores, and lower support costs. For example, implementing automation and self-service can reduce ticket volume by double digits while maintaining or improving customer satisfaction.
Ready to transform your customer communication? Book a demo to see how Gorgias can help you automate, personalize, and scale your support.
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The Gorgias helpdesk is a highly customizable, automatable tool. In theory, you could use it like a standard inbox, answering customer support tickets from top to bottom. But you’re better off taking advantage of its features to organize your inbox, automatically prioritize and assign tickets, and automate repetitive tasks.
Streamlining your helpdesk from the jump is the best way to spend less time on administrative work so you can respond faster and leave customers satisfied.
TalentPop is a customer service management agency for ecommerce brands like yours and optimizes Gorgias for over 500 top brands like Jaxxon, Lilly Lashes, and Kettle & Fire. And while each brand’s needs are unique, every ecommerce company could benefit from essentials like automated ticket routing and answering WISMO requests.
We developed this playbook to share these best practices for setting up Gorgias so your team can get back to focusing on what matters most: tending to urgent requests and having impactful conversations with your valued customers.
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In Gorgias, Tags keep track of the contents and context of a ticket at a glance:

Especially as your team grows, Tags are the best way to keep your helpdesk organized, filter for specific conversations, and track the progress of customer resolutions. Plus, when combined with automation (which we’ll discuss in the next section), Tags help your team prioritize requests, route conversations to a specific team member, or send messages to customers.
Accurate and up-to-date Tags also help you analyze ticket trends much easier. For example, if you suddenly experience a 20% spike in tickets tagged with “product-complaint,” you can quickly dig into that issue.
Gorgias comes with a set of Tags that you can start using automatically, but you should build out the list based on your needs. When we help brands build out their list of Tags, we start by auditing past tickets to understand existing patterns.
Below, we included a list of the most common Tags you’ll likely find helpful. Start there, and consider auditing your own helpdesk to add any additional tags your team would find helpful.

Tags for customer account management
Tags for collaboration
Tags for customer feedback
Tags for product feedback
Tags for discounts
Tags for orders
Tags for return and exchange
Tags for shipping
Order status
Tags for social media
Tags for subscriptions
Tags for urgent inquiries
Tags for VIP customers
Tags for wholesale requests
Once you have those (and other) Tags set up, you can apply them manually or use automation to automatically tag incoming tickets.
In Gorgias, Rules are flexible tools to automate a wide range of day-to-day tasks, like tagging, routing, automatically closing no-reply messages, and even replying to basic messages.
Just like Tags, Rules will vary from brand to brand. And the possibilities of Rules are near-endless, so no blog post can give you a complete list of Rules to use. That said, here are four categories of Rules (with specific examples) you’ll likely find useful:
Manually applying Tags can eat up agent time (and leave room for error). Move faster and ensure your tags are more accurate by setting up Rules to auto-tag tickets based on ticket content.
The following Rules use keywords in the message to apply Tags. For even more advanced tagging, you can use Gorgias’s Intent and Sentiment Detection to tag tickets even when the ticket doesn’t include a specific keyword.
Rule description: When an agent requests an email address update from customers, apply the “edit-address” tag.
Rule benefit: This Rule helps you keep track of incorrect email addresses and email address updates. When you then use this Tag in correspondence with a View, you’ll have an easy time matching up the customer’s old and new email addresses.
How to set up Rule:

Rule description: Automatically tag incoming tickets mentioning product damage with “Damaged/Defective.”
Rule benefit: Tagging these kinds of tickets is a great way to prioritize these sensitive interactions, so customers aren’t left waiting after they receive a damaged item. If you respond quickly and courteously, you greatly increase your chances of mitigating an escalation and retaining the customer.
How to set up Rule:

💡Tip: Adjust the rule to include keywords from previous tickets about damaged inquiries, which will best reflect how customers talk about your product getting damaged. For example, if you sell clothes, people will use words like “torn” and “stained” more than “broken.”
Rule description: Automatically tag incoming tickets containing exchange requests with “Exchange Request.”
Rule benefit: This is a very beneficial auto-tagging feature that, when corresponding to a view, will help your customer service agents prioritize exchange requests on time. From our experience, this is especially helpful for apparel and jewelry brands, although you can use it for a variety of brands.
How to set up Rule:

💡Tip: We recommend updating the Exchange Request Rule with language from previous and future tickets. Continuously optimizing the rule to include additional keywords will help make the tagging function more accurate over time.
Rule description: Automatically tag incoming tickets containing refund/cancellation requests with “Refund/Cancellation.”
Rule benefit: When corresponding to a View, this auto-tagging feature will help your team effectively prioritize refund and cancelation requests, which is important for a couple of reasons:
How to set up Rule:

Rule description: Automatically tag incoming tickets mentioning new product reviews with “Review.”
Rule benefit: When corresponding to a view, this rule will help your customer service agents properly manage and respond to incoming reviews, both positive and negative.
How To Setup Rule: Unlike our other rules, there can be multiple configurations for this set-up — it depends on the platform that you are using. Gorgias currently integrates with several review apps, but each one can require a different setup. In this example, we will include the most common configurations.
Here’s a Rule that leverages the Gorgias integration with Yotpo, flagging new reviews of your channel:

Here’s a review based on the ticket’s subject line to catch new reviews based on the standard format of some review platforms:

💡Tip: Take your internal reviews-monitoring processes to the next level by manually tagging reviews as positive or negative. This will help you better understand which reviews are positive or negative, overall trends, and flag reviews with a high score but negative tone.
Another trick we like is to tag reviews with the relevant product’s SKU to help your team better understand which products people enjoy or dislike the most. This feedback is invaluable for your Product team.
Rule description: Automatically tag incoming tickets containing time-sensitive requests with “Urgent.”
Rule benefit: Urgent tickets should always be prioritized, which is what this rule — when corresponding to a view — helps your team to do.
How to set up Rule:

💡 Tip: Set up this rule with keywords that your team deems urgent, like when customers threaten to contact the Better Business Bureau or ask to speak with a manager. Negative comments don’t have to be the only urgent ones, either: You can tag pre-sales tickets or tickets from VIP customers as urgent.
Additionally, you can apply a rule for Urgent tickets explicitly related to social media. This setup is a stellar method for ensuring public (ie. customer-facing) issues are resolved quickly.
Rule description: Automatically tag incoming tickets mentioning problems with your website with “Website Issue.” (Note: You might also choose to also add the Urgent tag so you can address these issues quickly.)
Rule benefit: This Rule is a lifesaver — it’s been highly effective for our clients during sales, general marketing campaigns, or even on an average Tuesday. It can ensure that you don’t miss out on sales and that your customers always have the best experience.
How to set up Rule:

Rule description: This ticket advises customers when your live chat is unavailable due to business hours or holidays.
Rule benefit: One of our favorites for gauging bandwidth, this rule is great for identifying when messages come in outside your regular business hours. With this data, you may consider bringing on additional support if ticket volume is high outside of your regular customer service schedule.
Note: To use this Rule, you’ll have to set up Business Hours. You can also adjust your chat setting so chat is unavailable outside business hours, and customers must fill out Contact Forms (which require their email address) to send a message so you can follow up via email when your team logs back on.
How to set up Rule:

In case you missed it, an internal note in Gorgias is a note added to a ticket that’s only visible to your team — it’s not shared with the customer. Internal notes can be added to conversations to share vital or helpful information about the customer or the ticket with your team. These notes can also record any actions taken on the customer's request.

Rule description: When an agent creates an internal note, this Rule automatically tags the tickets as “Internal Note - Open.”
Rule benefit: This Rule is great for ensuring internal team communications are appropriately tagged and sorted into Views, so all internal views get flagged and all customer questions get answered.
How to set up Rule:

An auto-reply is a pre-written response automatically sent to a customer based on the ticket’s content, channel, timing, or a variety of other factors. You can use auto-replies to:
Note that auto-replied tickets still have limitations and should be frequently reviewed and re-assessed.
Rule description: Answer and resolve inquiries about order status.
Rule benefit: Provide instant responses to the most common question in ecommerce customer support and free your agents up for higher-impact interactions.
How to set up Rule:

📚 Related reading: Check out our complete guide to automating WISMO requests.
Views filter and organize customer data within the left sidebar, allowing customer service teams to access and respond to customer inquiries quickly. Views can also prioritize tickets by urgency or organize them by channel. This feature helps customer service teams manage their workload more efficiently and provides insights into common customer issues or trends.
Views are simple to set up based on ticket tags and other qualities, so we won’t spend time explaining how to set them up here. Instead, we’ll share a couple of types of Views you’ll likely find useful.
Building views based on urgency within Gorgias is a good idea for several reasons:
Building views based on specific channels within Gorgias can be extremely helpful for your brand’s customer service needs:
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Macros in Gorgias are pre-made responses that insert commonly-used text into a ticket response after being triggered by a keyboard shortcut or by clicking a Gorgias interface button.
They help agents decrease response times by eliminating the need to repeatedly (and manually) type the same response for similar customer service inquiries. A customer service representative might use a Macro to insert a standard response to a frequently asked question or even a product return request.
As we tell our own TalentPop agents during training, it is never in your best interest to 100% rely on Macros. Macros should be a foundation for writing responses to customers, as every inquiry is unique and each customer deserves a personalized experience.
Handling returns and exchanges can be complex. As a customer service management agency that has worked with over 500 top ecommerce brands, we can confidently say that a “one-size-fits-all” approach is not the correct one for these situations.
With this in mind, we generally provide our agents with different options to handle situations based on client SOPs.
Below you will find an example of what an unbranded Macro for this could look like:
Hi {{ticket.customer.firstname}},
It's {{current_user.firstname}} from [Brand Name].
Thanks for reaching out!
You can return an item within [X days] of receiving your order.
Once we receive your package, please allow up to 2 weeks for us to receive and inspect your product.
Once everything is properly verified on our end, we can process the return and issue the credit back to your original payment method.
For more information, please take a look here [Link to Return Policy].
We would love to help you out regarding your return request.
Since you received your goods within the return window of [X days], we can absolutely help you with a return.
Attached is a return label you can use to ship the items back to us.
Once we receive your package, please allow up to [X days] for us to receive and inspect your product.
Once everything is properly verified on our end, we can process the return and issue a credit back to your original payment method.
For more information, please take a look here [Link to Return Policy].
Your order was delivered on [Delivery Date] and is already past our return window of [X Days], we can no longer process a return.
For more information, please take a look here [Link to Return Policy].
Should you have any further questions, please let me know and I am more than happy to assist you.
All the best!
{{current_user.firstname}}
[Brand Name]
💡Tip: Another option to make this Macro more concise is to separate the situation types specifically. I.e. Return: Return Policy, Return: Within Return Window, Return: Outside of Return Window, etc. We find this the best approach, as it provides you with cleaner data that you can use to better understand customer situations.
Just like exchanges, we can either create a single Macro that explains different options for an agent to choose from, or create separate Macros for each situation (like regular refund/order cancellations, damaged refunds [minor/major defect], discount errors, product out of stock, subscription refund, etc.)
Below you will find an example of what an unbranded Macro for this could look like:
Hi {{ticket.customer.firstname}},
It's {{current_user.firstname}} from (Brand Name). Thanks for reaching out!
I am more than happy to help you out with your refund request.
I've refunded your last order {{ticket.customer.integrations.shopify.orders[0].name}} as requested.
We have successfully processed a partial refund on your order {{ticket.customer.integrations.shopify.orders[0].name}} as requested.
Please allow (X-X) business days for the refund to be processed. These funds will be refunded back to the original form of payment used for the purchase.
Thank you and please let us know if there is anything else that we can help you with.
We are very sorry to hear that you were not satisfied with your purchase. We can't process your refund request at this time because (insert the reason why a refund is not applicable).
Please let us know if you have any questions on this.
If the customer wants to follow up on a refund request that has been processed
Upon checking your order {{ticket.customer.integrations.shopify.orders[0].name}}, I can confirm that your refund has been processed on our end. You will see the refund amount on your payment account within 3-5 business days.
If you do not see any updates, I would recommend contacting your bank directly to verify the refund progress.
We apologize for any delays on this.
Please let us know if you have any questions.
All the best!
{{current_user.firstname}}
[Brand Name]
💡Tip: If you create a more specific refund Macro, we recommend adding the specific tags and corresponding actions that should be taken while using it. For example:


This action lets you choose whether you want to process a full refund or a partial refund:

Hello {{ticket.customer.firstname}},
It's {{current_user.firstname}} from (Brand Name). Thank you for bringing this to our attention.
I am so sorry for how you received this item!
Since this defect seems it should not affect the integrity of the item, we can provide the following options:
1. Keep the item and we will issue an XX% discount code for the inconvenience and condition that the product showed up in.
2. We will issue a return label for you to be able to send it back and we can then process a replacement or a refund.
Please note that if you decide to keep the item, it will not qualify for further compensation in the future if any additional issues occur.
Thank you,
{{current_user.firstname}}
[Brand Name]
Hello {{ticket.customer.firstname}},
It's {{current_user.firstname}} from (Brand Name). Thank you for bringing this to our attention.
We're so sorry you received your order damaged. We totally understand how frustrating this feels and we'd love to be able to make it up to you!
Here are a few options for you to choose from:=
1. A replacement (if stock allows).
2. A refund back to your original payment method.
3. A refund in form of store credit (gift card).
Please let us know what option would work best!
Also, please use the discount code XXXX on your next purchase as a gift from us.
Thank you!
{{current_user.firstname}}
[Brand Name]
In the examples above, you may notice that in both situations, we are providing customers with options to choose from. From our experience, when customers can choose the type of service they want, they are more likely to be satisfied with their overall experience.
Hi {{ticket.customer.firstname}},
We would love to assist you!
Can you kindly share with us what you would like to change in your order?
Once we have this information, we can go ahead and update your order.
We have successfully updated your order. We have sent you a new order confirmation to your email for your reference.
Please let me know if you have any questions and we look forward to getting your order in your hands!
Hi {{ticket.customer.firstname}},
It appears that your order was fulfilled last {{ticket.customer.integrations.shopify.orders[0].fulfillments[0].created_at|datetime_format("MMMM d YYYY")}} and unfortunately we can no longer cancel it.
You can simply refuse the package upon delivery, and once your online tracking information updates that your order is on its way back to us, please let us know over email so we can assist and provide you with either a store credit or a refund.
Out of curiosity, can you kindly share what made you change your mind about your order? I'd love to share this with our Product Team! From there, we can understand how we can improve things on our end and how we can best help you out.
Please let me know if you have any questions and I look forward to your reply.
Live chat can be an impactful support channel for your ecommerce business, as it can decrease response times, improve your overall customer experience, and drive revenue further.
This Macro is great to use as a sign-off; you can amend it according to your brand voice or the situation at hand.
Hi {{ticket.customer.firstname}}!
I hope I was able to address your concerns.
Please feel free to reach out anytime. All the best! {{current_user.firstname}}
If we can be of further assistance, please free to reach us again or send us an email at support@client.com. Thank you and have a great day!
This Macro is great to use when you have agents online and receive a live chat message, but are busy responding to another customer.
Hi {{ticket.customer.firstname}}! We received your message and an agent will be with you soon!
You can pair this Macro with an autoresponder Rule, so customers automatically receive this message in response to the first live chat message they send. Here’s what that Rule looks like:

The basic setup of Gorgias is easy, but some brands may want extra help to fully customize Tags, Views, Rules, and Macros to provide great service as efficiently as possible. If this sounds like you, TalentPop is here to help.
As a trusted Gorgias Partner, we have extensive experience with Gorgias’s helpdesk. We understand that every business is different, and we strive to help each of our clients find the best solutions that work for their teams. We’re well equipped to customize the platform to your preferences and unique situation streamline your processes and help your business grow.
Whether you’re getting started with Gorgias or are ready to level up your helpdesk to meet your needs, our implementation team is here to be your Gorgias guide.
If you’re interested in learning more about how we can help, book a call with our team for a free consultation.


