

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.
Four months ago, our analysts were dealing with a barrage of questions. "What's our ARR by segment?" "Build me a dashboard for this quarter's pipeline." Quick asks piled up behind complex deep dives. Stakeholders waited for answers that should have taken seconds, and analysts spent their time fielding requests instead of doing the strategic work that creates the most value.
Today, anyone at Gorgias can ask a question in plain language and get an accurate, contextualized response in seconds. Not from a colleague or dashboard, nor from a generic answer from the internet. But a response built on our business context. We call it Cortex, our flagship internal AI agent.
In two months, Cortex went from an idea to fielding thousands of questions every week, recommending actions across the business, and deprecating the need for manual dashboard creation. While most companies right now are treating AI as an initiative — at Gorgias, AI is already part of how we work. 72% of Gorgias employees use Cortex each week, and that number is only growing.
We didn’t achieve this by simply plugging a large language model into our stack. LLMs are a critical part of the equation, but they aren't the driving force — it’s everything else under the hood: the infrastructure, context, platform architecture, and the team that brings it all together.

The instinct across many companies today is to start with the model, pick a provider to solve a specific challenge, or invest heavily in getting the data right. All reasonable starting points, but most of them solve for one use case. Underneath that approach is a framing problem: seeing AI as an initiative — something you assign and measure. Seeing AI as another tool your company uses versus how your company operates.
We started somewhere different. Every company is built on four pillars: customers, people, product, and decisions. AI investments tend to place heavy emphasis on the first three. We started with the fourth. Our bet was that if we built everything around the need to make effective decisions first, asking what Gorgias needed to know to operate well, then our AI would become dramatically more powerful.
Cortex is our flagship internal AI agent, and the product where we established the tenets that now run through everything else we build: composable and modular infrastructure, governed context, and accessible from wherever decisions happen. Cortex lives in Slack, as well as across LLM vendors, in its own browser extension, and even on its own dedicated internal site.
Cortex doesn’t stop at answering questions. It can read and write to Notion, file Linear tasks, create HTML apps, automate signal delivery, and more. It operates across every layer of our stack, from dashboards to data pipelines, because we designed it as one integrated system. It is this connection that adds remarkable depth to what people can ask, and what they get in return.

A Sales Lead is pitching and asks Cortex for the full picture of the merchant. In a customized PDF, Cortex lists coverage gaps, pre-sale intent signals, and product fit options. Everything the sales lead needs to walk in with confidence.
A Senior Product leader asks, "How are we performing against OKR #1, and what can my team do to help accelerate it?" Cortex returns a full ARR breakdown, projected end-of-month attainment, segment-level findings, and connects it all back to company-level strategies. A suite of recommendations customized to the leader, the performance, and the signals that bridge how they can support our goals. The kind of answer that used to take someone a week to put together.
These aren't simple lookup queries. They require deep business context spanning multiple areas. Cortex handles these because its Decision Engine gives it the information to reason against governed data, metric definitions, and business context, turning a generic answer into a credible one.
Overnight, teams have built Cortex into how they work. They’re spending less time searching and more time finding answers, not because they were told to, but because Cortex reduced the distance between question and decision.
Cortex’s modular infrastructure allows us to experiment and add new capabilities freely. We’ve already built two more internal AI agents made for entirely different use cases, but using the same Decision Engine as Cortex.
GAIA, our internal experimentation AI Agent, helps our customers identify opportunities in their AI Agent Guidance design. It takes institutional knowledge across our teams and turns it into a scalable system that drives automation and value to our customers. Our CEO, Romain Lapeyre, has been its most vocal advocate since day one.
When we needed a platform for investor readiness and board preparation, we built Oracle. Our board decks and talk tracks are informed and built with the same AI, and our numbers are validated every step of the way.
We’re continuing to expand new AI agents internally, exploring how they can create value for customers and our own teams.
When AI handles thousands of analytical questions each week, the highest-value work for a data team shifts permanently. Late 2025, we repositioned from a Data Analytics function into a Decision Intelligence function — a structural change in what we own and how we operate.
Today, our analysts focus on the most sensitive, complex, and forward-looking decisions and analyses. They partner more deeply with stakeholders by driving next steps from signals. They're even building entirely new capabilities that didn't exist in their role descriptions months ago. Things like AI skills for Cortex, context curation, and insight and recommendation delivery. The role of the analyst hasn't diminished. It's expanded to encompass the most meaningful work an analyst can do: driving outcomes and ensuring those decisions can achieve them.

Our business support model has changed, too. Instead of embedding analysts and dedicated engineers within functional teams, we align capacity to the highest-impact company objectives and move fluidly across them. This model works even better because Decision Intelligence brings together both analytics and engineering teams under one roof.
Elliot Trabac leads our Data, Context and AI Engineering teams. The Decision Engine, Cortex, GAIA, and the platforms I've described exist because of the infrastructure his team innovated and built from the ground up. Noemie Happi Nono leads our Decision Strategy and Operations team, driving decision outcomes with stakeholders, advancing the development of Cortex skills and capabilities, and pushing into new areas of analysis every day.
Together, they're shaping what a modern data function looks like when AI becomes a standard building block for how a company operates.
The question of ROI is long gone. AI has opened the floodgates to more trusted and meaningful signals than ever. The natural next evolution is Proactive Intelligence, signals surfaced toward what you need to know, before you ask. And we're already building this because our architecture is designed to support it.
In the coming weeks, members of the Decision Intelligence team will go deeper into themes I've touched on here. Yochan Khoi, a Senior Analytics Engineer on our team, recently published a technical walkthrough of our context layer and will go further into building context strategies that scale. Others will cover infrastructure, analytical partnerships, evolving data assets into decision assets, and the cost and efficiency gains that make sustained AI investment viable.
AI hasn't changed the most important element of data and analytics functions — delivering outcomes — but it has raised the bar for what it looks like and how far we can take it. We’re just getting started.
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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:
A year ago, ecommerce brands were still debating whether AI was worth the investment. That debate is over. Today, nearly every ecommerce professional uses AI to do their job.
The shift isn't just about adoption. It's about what AI is used for and how brands measure its impact. Support automation was the entry point. Now, AI is embedded across the full operation, from product recommendations to inventory control to real-time shopping conversations.
In our 2026 State of Conversational Commerce Report, we break down trends on AI usage among 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
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If we rewind 12 months ago, the industry was still split on AI. Some ecommerce professionals were excited, but most were still hesitant. In 2024, 69% of ecommerce professionals used AI in their roles. By 2025, that number reached 77%. In 2026, it hit 96%.

The confidence numbers back it up. 71% of brands say they are confident using AI for ecommerce, and 73% are satisfied with its business impact.
In early 2025, only 30% of ecommerce professionals rated their excitement for AI at 10/10. Today, zero percent of respondents describe themselves as hesitant about AI.

Using AI in ecommerce is not new. In fact, it dates back to the 1980s with the invention of algorithms and expert systems. And if you’ve ever leveraged similar product recommendations or chatbots, you’ve already integrated AI into your ecommerce stack.
Modern AI is far more sophisticated.
With the rise of agentic commerce and conversational AI, brands began leveraging AI agents to automate the processing of repetitive support tickets. That’s still happening today, but the scope has expanded beyond the support queue.

Ecommerce brands are deploying AI across every layer of their operation:
When brands were asked which channels contribute most to their AI success, conversational channels dominated. Social media messaging led at 78%, followed by SMS at 70%, and website live chat at 51%. Shoppers want fast, personal conversations, and AI is the best way to deliver that at scale.
Learn more about AI adoption, perception, and use case trends in the full 2026 Conversational Commerce Report.
For decades, customer support success meant fast response times and high satisfaction scores. Those are still important indicators of success, but leading brands are adding revenue-focused metrics to their dashboards.
91% of brands still track CSAT as a measure of AI's impact. But 60% now include AOV as a top indicator, and higher-revenue brands earning $20M+ are focusing on metrics like total operating expenses, cost per resolution, incremental revenue, and one-touch ticket rate.

AI can now start a conversation, ease customer doubts, sell, upsell, and recover abandoned carts in a single conversation. When you’re only measuring CSAT, you’re ignoring the real ROI of conversational AI investment.
Virtual shopping assistants now proactively engage shoppers, adapt to their needs in real time, and offer contextual product recommendations and upsells. When the moment calls for it, they can close the deal with a targeted discount.
Gorgias brands using AI Agent's shopping assistant capabilities nearly doubled their purchase rates and converted 20–50% better than those using AI Agent for support only.
Orthofeet, the largest provider of orthopedic footwear in the US, is a concrete example of this in practice. Using Gorgias, they achieved:
The data tells a clear story: AI has evolved beyond a tool for handling tier 1 support tickets. It’s a core part of your revenue generation strategy.
57% of brands are already using AI for 26–50% of all customer interactions, and 37% expect that share to rise to 51–75% within the next two years. The brands building toward that range now are the ones who will have the operational advantage when it matters most.
The practical question isn't whether to invest in AI. It's where to focus first. Based on where brands are seeing the most impact, three priorities stand out:
Want to go deeper on the full 2026 conversational commerce trends? Read the complete report for data across every major AI use case in 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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Today, we’re announcing our deeper investment in conversational AI for ecommerce.
"Since day one, Gorgias has been dedicated to helping ecommerce brands deliver exceptional customer experiences. We started with a helpdesk to centralize support, then introduced AI Agent to instantly resolve support questions,” says Romain Lapeyre, CEO of Gorgias.
“Now, we're taking the next leap forward with an AI Agent that powers the entire customer journey—anticipating buyer needs, boosting sales, and automating high-quality support. Today, I'm happy to announce Gorgias as the Conversational AI platform for ecommerce.”
Gorgias’s Conversational AI platform will let teams provide fast, scalable, and cost-effective support while helping them drive revenue growth. From automatic order changes and refunds to product recommendations and cross-sells, brands will be able to flawlessly combine their support and sales efforts.
The end result is an AI-powered customer journey where every customer interaction feels complete, personal, and connected, both before and after purchase.
Last year, we introduced AI Agent for email.
Some brands call their AI Agent Lisa, some call it Wally, and most treat it like a real member of the team. But this reliable support sidekick was only available to answer customers on email—until now.
Get ready for instant responses that tackle support inquiries of all sizes. Now, your customers can enjoy fast responses that keep their shopping experience as smooth as possible.
On top of improving first response times, AI Agent can play an even more critical role in unblocking sales, suggesting products, and driving upsells and cross-sells.
With responses sent in 15 seconds or less, brands can delight customers with near-instant resolutions.

Actions let AI Agent perform customer requests on behalf of your support team. This includes changing shipping addresses, fetching fulfillment status, canceling orders, adding discounts, and more.
You can use a library of pre-configured Actions for popular apps like Shopify, Rebuy, Loop, and more. And you don’t need any technical skills to set them up.
With almost half of queries requiring some kind of update, Actions is your go-to for complete resolutions so you can get more accomplished.

Quality checks have traditionally been manual, time-consuming, and inconsistent. Our brand new Auto QA feature changes that by automatically scoring 100% of conversations on resolution completeness and communication quality—whether from a human or AI agent.
With Auto QA, team leads can:

Support teams should be in complete control of their AI. That’s why the AI Agent Report and AI Agent Insights were created—to help you know exactly how your AI Agent is performing and contributing to your customer service operations.
The AI Agent Report provides full visibility into AI Agent’s performance, covering metrics like first response Time, CSAT, and one-touch ticket resolutions. Fully integrated into your Support Performance Statistics dashboard, the report includes:

AI Agent Insights takes it a step further. It analyzes AI Agent’s performance data and provides you with a dashboard of recommendations, including potential automation opportunities, popular ticket intents to optimize, and knowledge base improvements.

Soon, we’ll be expanding AI Agent's skills with the launch of Shopping Assistant, a tool designed to assist customers on their shopping journey.
Shopping Assistanthelps brands boost their sales capabilities through smart product recommendations, on-page checkout assistance, and personalized conversations. Now it's easier to reduce cart abandonment, suggest complementary products to boost average order value, and overcome pre-sale objections.
This new tool will bridge the gap between marketing and CX, ensuring brands can scale personalized interactions 24/7 without increasing headcount.

As we continue to innovate with conversational AI, our focus remains on helping you succeed.
By combining smarter tools with valuable insights, we’re creating opportunities for you to put your customers first and build deeper connections at every touchpoint.
Join us as we pave a new way for the future of ecommerce.
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TL;DR:
Your customer service conversations contain a goldmine of insight about your shoppers—like why they reached out, trends in shopper behavior, and how your products or services perform.
But how do you turn thousands of unstructured support tickets into accurate, digestible, and actionable takeaways?
Ticket Fields are the answer. They give support teams extra layers of data by labeling tickets in a much smarter way than traditional tags. With the right setup, Ticket Fields can help you uncover patterns, make smarter decisions, and highlight the value customer experience (CX) brings to your entire organization.
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Ticket Fields are customizable properties that allow CX teams to collect and organize information about tickets. Agents fill in ticket fields before closing the ticket, making it much easier to scale data collection.
Ticket Fields can be mandatory, requiring an agent to populate a field before closing the ticket. They can also be conditional, only appearing when relevant to the ticket.
There are four types of Ticket Fields: Dropdown, Number, Text, and Yes/No. Here are some ways to use each:

Unlike Tags, which are single-reason and non-conditional, Ticket Fields ensure key information, such as fulfillment details or cancellation reasons, is built into a ticket.
Think of Tags as stickers added to a ticket, while Ticket Fields are part of the ticket’s DNA itself, giving you much more control and insight.
Let’s take a closer look at why Ticket Fields are far superior at collecting data than Tags:
Agents manually apply Tags, which means it’s easy to forget to tag a ticket.
Ticket Fields, however, enforce structure by allowing CX managers to decide which fields are mandatory and which are optional. This flexibility ensures that all tickets contain the same basic details.
Ticket Fields can be conditional, meaning certain types of tickets automatically include fields that must be filled in.
How does it work? Take a look at this example:
If the Contact Reason field is Cancellation, conditional ticket fields like Cancel Reason, Did We Cancel Subscription, and Order Number must also be filled out.
Here’s how it looks in the Field Conditions settings:

No more missing context, gaps in the data, or typing N/A in a field. Support teams can capture the data they need from each ticket every time.
For CX teams transitioning from other helpdesks, being able to import historical ticket data with the field information intact is significant. This preserves workflows and existing data, helping teams get set up in no time without losing crucial information.
Tags, on the other hand, should be used to:
Ticket Fields are incredibly adaptable, allowing you to capture the exact data your team needs to meet your goals—whether it’s tracking product trends, choosing a shipping carrier, or increasing customer satisfaction.
Here are 12 examples of custom Ticket Fields to level up your data analysis.
Type of ticket field: Dropdown
What to do with the data: Identify common reasons customers contact you and take proactive steps to address them.
The Contact Reason ticket field is an easy way to figure out why customers reach out to your support team in the first place.
You can quickly identify trends, such as a sudden spike in return requests, and investigate whether it's a website, fulfillment, product, or service issue.
Some common contact reasons:
Note: Gorgias AI automatically suggests contact reasons, pre-filling the field with a prediction based on message content. Agents can accept or adjust the suggestion, helping the system become smarter over time as it learns from these interactions.

Type of ticket field: Dropdown
What to do with the data: Assess the effectiveness of resolutions and refine your service level agreement.
The Resolution ticket field tracks the action taken to resolve a ticket. Analyzing how your team handles tickets and identifying opportunities to improve resolutions is essential.
For example, you could analyze how often issues are resolved with replacements versus discounts. If you find replacements are overused for minor issues, you might implement a policy to provide discounts instead, helping to reduce costs without harming customer satisfaction.
Here are some values to add to the Resolution ticket field:

Type of ticket field: Dropdown
What to do with the data: Use both positive and negative feedback to update your policies, escalation process, customer-facing resources, product, and more.
The Feedback ticket field can capture general feedback about your brand or feedback specific to your products.
This field is an excellent way to carry out product research. For example, if you’re a food brand, you can create a dropdown that categorizes feedback by sentiment, such as “Too Sweet,” “Too Salty,” “General Dislike,” and “Artificial Taste.” Once you’ve received a decent amount of feedback, you can return to the test kitchen and perfect your recipe.

Type of ticket field: Dropdown
What to do with the data: Track product trends and prioritize improvements.
The Product field is valuable for tracking which items generate the most inquiries. If you have a large inventory, incorporating a Product ticket field can help flag which products are causing the most issues or trouble for shoppers.
If a product is the most used value, this could indicate frequent issues with the product, such as quality issues, defects, or missing information on its product page.
If a product is the least used value, it may not be generating much attention. If this is due to low sales, consider enhancing its visibility through marketing to attract more shoppers. However, being the least used value can also be good news, meaning your product performs well, and shoppers have no complaints.
Pro Tip: To understand which specific products are getting returned, add a conditional “Product” ticket field.

Type of ticket field: Dropdown + conditional field
What to do with the data: Identify recurring quality issues and fix root causes.
Track the most prominent defects reported by customers with a Defect ticket field. This can help you monitor product quality and adjust production, manufacturer, or supplier processes.
For deeper insights, add a conditional “Product” field to pinpoint which products experience specific defects. For example, if you’re a bag brand, you might find that a certain backpack is usually tied to a “Zipper” defect. This can be a valuable insight to pass on to your product team to alter the design or adjust your manufacturing process.
Here’s a look at the dropdown values for the Defect ticket field:

Type of ticket field: Dropdown
What to do with the data: Lower churn by addressing cancellation triggers.
If you’re a subscription-based business with a climbing cancellation rate, adding a Cancellation Reason ticket field can help you stop the churn. This field tracks why customers cancel orders or subscriptions. It’s a powerful way to identify patterns, such as price sensitivity or delivery delays, and to take steps to retain customers.
Cancellation reason examples:
Type of ticket field: Dropdown + conditional field
What to do with the data: Evaluate shipping carrier performance and improve logistics.
For any ecommerce brand, your shipping carrier is a big contributor to customer satisfaction. The faster a customer’s order gets to them, the better.
Use a Shipping Carrier ticket field to track the shipping carrier for tickets related to delivery issues. This will provide insights into which carriers perform poorly, enabling you to modify your logistics and order fulfillment processes.
Pair the Shipping Carrier field with a conditional “Shipping Issue” field to identify potential correlations. For example, if “Delayed” is a top shipping issue for a certain carrier, it may be time to change your logistics process.

Type of ticket field: Dropdown
What to do with the data: Learn how customers find your brand and see what types of customers and issues are tied to the purchase source.
The Purchase Origin field helps you see where customers are coming from. Are they buying directly from your website? Or from social media platforms like Instagram or TikTok?
Dig deeper, and you may also spot connections between purchase origin and common issues.
For your marketing team, this data will help improve strategies at all levels, from advertising and messaging to targeting the right platforms.

Type of ticket field: Yes/No
What to do with the data: Reduce escalations by revising escalation processes and retraining agents.
The Customer Escalation field tracks whether a ticket was escalated to a manager. It helps teams identify training needs and improve processes to reduce escalations.
As the use of AI agents increases in ecommerce customer service, having a clear view of which tickets are escalated can help pinpoint gaps in AI performance and identify scenarios that require human intervention.
Analyzing this data over time can guide updates to AI workflows and agent training, reducing the need for escalations altogether.
Type of ticket field: Number
What to do with the data: Understand how discounts impact customer satisfaction.
The Discount Percentage ticket field tracks the percentage of a discount applied to a customer's order, offering insights into how promotions affect customer behavior.
For example, if customers using a 20% discount frequently contact support about order confusion or dissatisfaction, it might indicate unclear promotion terms or product descriptions. This data helps brands refine promotional messaging and determine whether higher discounts lead to increased ticket volumes, customer satisfaction, or sales.

Type of ticket field: Yes/No + conditional field
What to do with the data: Improve the customer experience for brand new customers.
The First-Time Buyer field flags whether a customer is making their first purchase, making it easier to spot and support new shoppers. When a customer is marked as a first-time buyer, a conditional “Customer Sentiment” field can appear to capture how they feel about their experience.
First-time buyers often have questions about products or need recommendations to feel confident about their purchase. Pairing this ticket field with sentiment data helps to identify common pain points, preferences, and patterns among new customers so your team can finetune the customer experience and leave a lasting first impression.

Type of ticket field: Number
What to do with the data: Analyze product performance over time.
The Months in Use field tracks how long customers have been using a product. It’s perfect for spotting when items start breaking down, spoiling, or losing effectiveness.
This data helps brands figure out where durability, shelf life, or packaging could be improved to keep customers happy and products performing as expected.
Ticket Fields provide value across the entire CX ecosystem, from agents to decision-makers.
Ticket Fields are only as powerful as the processes that support them. Follow these five steps to help your team turn support tickets into valuable data for better reporting.
Decide what insights your team needs to improve workflows, product quality, or customer satisfaction. For example, if you want to track cancellations, set up fields like "Cancellation Reason" and "Refund Amount." Keep your Ticket Fields focused on data your team can use.
Use Gorgias to configure Ticket Fields in a structured and easy-to-use format. Keep dropdown options concise and specific to avoid confusion. Then, run a test ticket or two to confirm the setup works smoothly for agents.
Read more: Create and edit Ticket Fields
Create a presentation deck that clearly explains the purpose of every Ticket Field, the options agents can select for each field, and how the fields tie into the team’s data goals. For added visuals, include flowcharts to show when and how to use each field.

Pro Tip: Give agents a quick reference tool they can easily consult by providing a cheat sheet summarizing Ticket Field best practices.
Whether the data points to gaps in your workflows, product details, or customer education, acting on these patterns is how you drive meaningful change.
Here are some fixes, from low to high effort, that your team can implement:
Schedule a monthly meeting to review your Ticket Fields Statistics and evaluate their impact on your support workflows and customer satisfaction.
During the meeting, discuss:
Lastly, remember to document the insights and update your team regularly to keep everyone aligned.

Gorgias’s Ticket Fields turn ticket data into insights you can actually use. Spot trends, improve workflows, and make faster, smarter decisions.
Are you ready to see it in action? Book a demo, and let us show you how Ticket Fields can elevate your support.
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TL;DR:
Gorgias uses ticket-based pricing that scales with your support volume. Each plan includes a monthly ticket allotment, unlimited agent seats on higher tiers, and access to core helpdesk features.
The platform's deep Shopify integration and AI capabilities help ecommerce brands automate repetitive inquiries while maintaining personalized support. Understanding how billable tickets work and which add-ons you need helps you choose the right plan for your business.
Gorgias is a helpdesk platform designed specifically for ecommerce brands. This means it connects directly to your Shopify store to pull customer and order data into your support conversations.
The platform offers five pricing plans: Starter, Basic, Pro, and Advanced. Unlike most helpdesk tools that charge per agent, Gorgias charges based on billable tickets. A billable ticket is any customer-initiated conversation that your support team views or responds to.
This pricing model works better for growing ecommerce teams. You can add unlimited agents on Pro and Advanced plans without paying extra per person. Your costs scale with your actual support volume, not your team size.
|
Starter |
$10 USD |
50 |
3 |
|
Basic |
$60 USD |
300 |
500 |
|
Pro |
$360 USD |
2,000 |
500 |
|
Advanced |
$900 USD |
5,000 |
500 |
|
Enterprise |
Custom |
Custom |
500 |
Each Gorgias plan is built for different stages of your ecommerce growth. The key difference between plans is how many billable tickets you get each month and which features are included.
A billable ticket counts when a customer sends you a message and your team interacts with it. Multiple messages in the same conversation only count as one ticket. Automated responses that fully resolve issues don't count at all.
The Starter plan gives you 50 billable tickets per month for $10. This plan works for new stores testing the platform or brands with very low support volume.
You get three agent seats and email support only. No automation features or advanced reporting are included. Think of this as a basic helpdesk to get started without a big commitment.
The Basic plan includes 300 billable tickets monthly for $60. This plan targets growing brands with steady customer inquiries.
You get three agent seats, email and Live Chat channels, plus basic automation Rules. The Help Center feature is included, along with standard integrations. Most established Shopify stores start here.
Key features added in Basic:
Support from Gorgias is based on your business size, not your plan:
The Pro plan provides 2,000 billable tickets for $360 monthly. This plan serves scaling brands with significant support needs.
Most successful direct-to-consumer brands operate on this plan. The unlimited agents feature alone can save thousands compared to per-seat competitors.
You get unlimited agent seats, which makes it cost-effective for growing teams. All channels except Voice and SMS are included. Advanced automation, custom Views, and revenue statistics help you optimize operations.
Support from Gorgias is based on your business size, not your plan:
The Advanced plan offers 5,000 billable tickets for $900 per month. This enterprise-level plan includes everything in Pro plus premium support features.
Support from Gorgias is based on your business size, not your plan:
The Enterprise plan offers fully customized pricing and ticket volume based on your business needs. This plan is built for large ecommerce brands with high support volume and complex operations.
You get unlimited agent seats, along with access to all support channels, including Voice and SMS. Advanced customization options, API access, and deeper integrations help support more sophisticated workflows.
This plan works best for brands operating at scale, managing multiple teams or regions, or needing a highly tailored support setup.
Support from Gorgias is based on your business size, not your plan:
AI Agent is Gorgias's conversational AI tool that handles common customer questions automatically. It starts at $250 monthly as an add-on to any plan.
The key benefit is cost savings. Conversations fully resolved by AI Agent don't count as billable tickets. This means AI can handle hundreds of inquiries without increasing your monthly bill.
AI Agent works for common questions like:
Voice support starts at $70 monthly plus usage fees. SMS pricing varies by country and message volume. Both channels create billable tickets when customers initiate contact.
These channels integrate into your unified inbox. Your team can switch between email, chat, social media, and phone calls without losing conversation context.
Understanding what counts as a billable ticket helps you choose the right plan and control costs.
Billable tickets include:
Non-billable activities include:
Read more: Definitions of billable events (help doc)
Gorgias uses a soft cap system. This means you never get cut off from receiving customer messages if you exceed your monthly ticket limit.
Instead, you pay overage fees for extra tickets. These fees are charged at the end of your billing cycle based on how many tickets you went over.
Overage rates are:
You can monitor your usage in real-time through the Gorgias dashboard. Set up alerts to notify you when approaching your limit. This helps avoid surprise charges and lets you upgrade your plan if needed.
Gorgias offers several ways to reduce your subscription costs and manage payments flexibly.
Paying annually unlocks the maximum discount on all plans except Starter. Annual contracts provide cost predictability and can be adjusted as your business scales.
The discount applies to your base plan cost. Add-ons like AI Agent, Voice, and SMS are typically billed monthly regardless of your main plan billing cycle.
Gorgias offers a free 7-day trial. You can send a maximum of 10 email ticket messages during your trial. You cannot publish a help center during your trial. No credit card is required to start exploring the platform.
Most brands go live within 48 hours using self-serve resources. Gorgias provides setup guides, video tutorials, and email support during your trial.
Your monthly subscription is just one part of the total investment. Consider implementation costs, potential extras, and the return on investment.
Most brands set up Gorgias for free using the provided resources. The Shopify integration is straightforward, and basic workflows can be configured quickly.
Optional paid onboarding helps with:
Budget time for your team to learn the platform. The Shopify-native interface reduces the learning curve compared to generic helpdesk tools.
Additional costs can arise beyond your subscription:
Gorgias typically pays for itself through efficiency improvements. Automation Rules reduce ticket volume by 20-30% for most brands. AI Agent can resolve up to 60% of common inquiries automatically.
These reductions translate to direct cost savings. Your team spends less time on repetitive tasks and more time on complex issues that drive customer satisfaction and sales.
Faster response times improve customer satisfaction scores. Better support experiences lead to higher retention rates and increased customer lifetime value.
Related: What happens when CX agents love their platform? Ask Glossier, Tommy John, and Brunt Workwear
Gorgias works best for Shopify and Shopify Plus merchants who view customer support as a growth driver. The deep ecommerce integration makes it less suitable for B2B companies or non-Shopify platforms.
Starter and Basic plans fit brands doing under $1 million annually with manageable support volume. These plans provide professional helpdesk features without enterprise complexity.
Pro plan serves brands in the $1-10 million range needing advanced automation and unlimited agents. The revenue statistics and custom reporting help optimize support operations for growth.
Advanced plan supports enterprise brands with high ticket volumes and complex workflows. The dedicated Customer Success Manager and priority support ensure smooth operations at scale.
Consider your current ticket volume and growth trajectory. Most brands start with Basic and upgrade as they scale. The ticket-based pricing grows with your actual support needs.
Current customers consistently highlight the value of unlimited agents on Pro and Advanced plans. This feature can save thousands compared to per-seat competitors as teams grow.
Users praise the transparent billing model. Ticket-based pricing is more predictable than usage-based models that charge for every interaction. You know your costs upfront based on support volume.
Some smaller brands find seasonal spikes challenging with ticket-based pricing. However, users report that automation and AI features typically offset subscription costs by reducing manual work.
Review sites like G2 and Capterra show high satisfaction with Gorgias pricing transparency and the ROI from efficiency gains.
Choose your plan based on current ticket volume and expected growth. Start with Basic if you're handling 200-300 tickets monthly. Upgrade to Pro when you need unlimited agents or advanced features.
The combination of ticket-based pricing, unlimited agents on higher tiers, and powerful automation makes Gorgias cost-effective for growing ecommerce brands. You pay for actual support volume, not team size.
Ready to see how Gorgias transforms your customer support operations? Book a demo to get personalized pricing recommendations for your business.
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TL;DR:
According to Salesforce research, 77% of support staff have dealt with increased and complex workflows compared to the year prior. In addition, 56% of agents have experienced burnout due to support work.
As teams transition into the next era of CX—one where almost every customer expects efficiency, convenience, and friendly and knowledgeable service –– they’ll need the support of more than just a stellar lead to avoid the stress that comes with the job.
AI and automation are valuable and impactful tools that can aid teams in providing these top-notch experiences while helping agents lower their own stress.
Here are seven ways to leverage AI and automation to increase agent productivity, meet customer expectations, and decrease burnout on CX teams.
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While there will always be reasons for human intervention, here are seven support challenges that AI and automation can solve for CX teams long term.
Every CX team receives repetitive questions like “where is my order” (WISMO), “can I change my shipping address,” or “what is your return policy” every single day. These questions add up over time, creating frustration and burnout for agents and longer response times for customers.
Instead, teams can leverage AI and automation to answer these questions and take time back for other essential tasks.
If you use Gorgias, there are a couple of ways to put automation to work.

"Gorgias's AI Agent has been a game-changer for us, allowing us to automate nearly half of our customer service inquiries. This efficiency means we don’t need to hire additional staff to manage routine tasks, which has saved us the equivalent of two full-time positions.
—Noémie Rousseau, Customer Service Manager at Pajar
Resource: How to automate half of your CX tasks
Many customers get frustrated due to delayed support responses, especially if (they believe) they’re asking a simple question. Not only can AI and automation support by offering responses to these questions, they allow human agents to respond faster to customers who have more complex questions.

AI Agent has been an effective tool for the team at luxe golf accessory shop VESSEL. “Now we’re able to get back to people so much faster than before,” says Lauren Reams, their Customer Experience Manager.
“We can quickly collect information – avoiding the back and forth questions like what is your name, email or shipping address. Using AI to eliminate the back and forth has been great, and getting back to customers much faster than before has been the biggest win for our team.”
If customers see an inconsistent tone of voice across responses, it’ll affect your brand credibility. It also causes confusion and may create issues maintaining repeat and loyal customers.

Manual quality assurance checks are time-consuming and often inconsistent. But they’re key to providing great support at scale while maintaining a high standard across thousands of interactions. Aside from catching any errors, a regular QA process also builds trust with customers, increases personalization, and helps agents improve over time.
Automated quality assurance can provide up to 90% accuracy, according to research by McKinsey. To ensure 100% of your customer conversations are checked, used Auto QA. This AI-powered QA tool evaluates your team's responses—AI or human—based on Resolution Completeness, Communication, and Language Proficiency.

When CX teams are bogged down with an overwhelming amount of tickets, there’s going to be a lack of time and opportunity to upsell in customer conversations. This is especially true when dealing with angry or upset customers, and during high-impact periods like BFCM.
Activate onsite marketing campaigns with Gorgias Convert to provide product recommendations and promote current discounts, sales, or campaigns.
For example, you can use AI to promote relevant items to shoppers to increase their cart value. You might highlight items that are frequently bought together, or show a bundle that would make a great gift for someone. Research shows that these types of personalized recommendations can increase average order value (AOV) by 15%.

Resource: 5 Holiday Onsite Campaigns to Maximize Year-End Sales
The National Retail Federation (NRF) projects that retail returns will total $890 billion in 2024. With so many brands losing money from returns, it’s essential that you find ways to mitigate them.
By switching to Gorgias, Audien Hearing saw nearly a 5% drop in return rates. And Rumpl saw $8,000 in recouped return fees by integrating Loop Returns with Gorgias.
Loop lets customers self-serve returns through a returns portal that encourages exchanges instead. It makes the entire process a breeze, and eliminates back and forth between customers and busy support teams.

Many times, issues that were completely avoidable are escalated, leaving support teams with more tickets and already frustrated customers. These issues are likely common points of confusion that you can easily solve before they ever reach your customers.
If you use Gorgias, here’s how you can leverage automation:

“I’ve been in this role for four years and this was probably our best back to school season yet. In past years, you knew you were going to come in and be bogged down – but this year was way more seamless and much less stressful and that’s thanks to AI Agent.”
—Danae Kaminski, Customer Care Team Lead at Jonas Paul Eyewear
At Gorgias, our goal is to create solutions to the real problems CX professionals face every day. Tools like AI Agent make it possible for teams to provide better customer experiences, reduce agent stress, and create more cohesive and positive working environments overall.
”Thanks to the time we've saved by automating many of our routine tasks, our team has had the chance to bond more,” says Noémie.
“We even had time for a team picnic and painted a picnic table outside! It’s been great to step away and spend time as a team occasionally, knowing that our customers are still being taken care of by the AI Agent. It’s really improved team morale.”
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TL;DR:
The start of a new year is the perfect time to give your help center the refresh it deserves. For many ecommerce brands, the help center is one of the most underused support tools—yet it's also one of the most powerful. 88% of customers already search your website for some kind of knowledge base or FAQ.
Customers expect fast answers, and a well-designed, updated help center can meet their needs while taking some weight off your support team. We’ll walk you through why refreshing matters and how to do it.
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90% of consumers worldwide consider issue resolution their top priority for customer service. A robust help center gives you the tools to meet this expectation, delivering fast and reliable solutions that simplify your customers’ lives.
A well-designed help center benefits both your customers and your team. For customers, it lets them solve problems quickly and independently. Instead of waiting for an email response or queuing for live chat, a help center empowers them to find answers on their own terms 24/7.
For your team, a refreshed help center is transformative, too. Here’s what a help center update can achieve:
In short, refreshing your help center will improve customer experience and boost efficiency across your entire customer service strategy. It’s a win-win for everyone.
Refreshing your help center doesn’t have to be overwhelming. By breaking the process into clear, actionable steps, you can transform your help center into a powerful self-service tool that delights customers and supports your team.
Here are four key steps to guide your refresh.
Before making any major changes, you need to understand where your help center currently stands. A thorough audit will help you identify areas for improvement and ensure you make targeted updates.
Here's how to start:
Dive into your help center metrics to spot underperforming content. Look at article views, time-on-page, and bounce rates. Low engagement might mean the content is unclear, irrelevant, or hard to find.
With a customer experience platform like Gorgias, you can view the performance of each article:

Customer feedback is invaluable. Use surveys or follow-up emails to ask customers what information they had trouble finding. Their responses can highlight blind spots in your help center.
At the end of each help center article, include a simple question like, "Was this content helpful?" Use the feedback to pinpoint which articles are effective and which may need improvement.

Put yourself in your customers’ shoes. Try searching for answers to common questions. Is the layout intuitive? Are the search results helpful? A smooth user experience is key to a successful help center.
Check if your articles are outdated or missing important updates, like new product features or policy changes.
Read more: How to create and optimize a customer knowledge base
Fresh, well-organized content is the backbone of a great help center. Customers rely on clear and accurate information, so investing in your content can transform your help center into a powerful self-service tool.
Here’s how to refresh your content and make it shine:
Regularly analyze support tickets to identify common and emerging questions. Integrate these into your knowledge base to address customer needs proactively and reduce incoming tickets.
Text alone isn’t always enough. Use images, GIFs, and videos to break down complex topics and make instructions easier to follow. For example, a quick explainer video can save customers time and eliminate confusion.
Princess Polly’s customer help center exemplifies what a great help center should look like. Its visually appealing design ensures that customers can quickly navigate to the information they need. Whether they’re looking for help with shipping, payments, returns, or any other issue, the intuitive layout makes the process simple and stress-free.

Gorgias lets you customize fonts, logos, and headers for your Help Center without any coding. If you want more customization, you can dip into HTML and CSS to tailor specific elements.
Ensure your content reflects your brand voice while staying approachable and customer-friendly. Consistency builds trust and reinforces your brand identity.
Need help finding your brand voice? Read AI Tone of Voice: Tips for On-Brand Customer Communication for guidance.
Review older content for inaccuracies or missing information, such as policy changes or new product details.
Use bullet points, short paragraphs, and clear headings to make articles easy to scan. Most customers skim for quick answers—design your content to match their behavior.
Even the most well-crafted help center is ineffective if customers can’t locate it. Ensuring visibility across all customer touchpoints is key to driving engagement and making self-service the first stop for support. Here’s how to do it:
Make your help center easily accessible by placing links in strategic locations, such as your website’s header, footer, and main navigation menu. Include links in transactional emails, like order confirmations, tracking updates, or shipping updates, where customers often have questions.
Optimize your help center articles with keywords your customers are likely to search for. Use clear, concise titles, meta descriptions, and headings to boost search engine visibility and help customers find answers directly from Google.
Use tools like automated chat and automated email responses to proactively surface relevant help center articles. For instance, when customers type a question in a chatbox, suggest related articles before escalating to a support agent.
Read more: Offer more self-serve options with Flows: 10 use cases & best practices
Don’t wait for customers to stumble upon your help center—promote it! Highlight it in onboarding emails, social media posts, and banners on your site.

Jonas Paul Eyewear ensures their help center is easy to access by prominently linking it in the website’s footer under the “Quick Links” section. The thoughtful placement ensures customers can quickly navigate to the help center from any page, making it a convenient resource for addressing their questions or concerns.
Read more: Boost your Help Center's visibility: Proven strategies to increase article views
Your help center isn’t just for customers—it will also level up your AI-driven support strategy. By structuring your knowledge base effectively, you enable AI tools to deliver accurate, reliable, and consistent answers to customer queries.
Here’s how to make it work:
Ensure your help center articles cover a wide range of customer questions in detail. This makes it easier for AI tools to pull relevant information and respond accurately.
Organize your content with clear headings, bullet points, and simple language. Well-structured articles are easier for AI to parse and interpret.
Use uniform terminology across articles to prevent confusion and ensure AI tools can quickly identify relevant data.
Keep your knowledge base fresh by adding new FAQs, updating outdated content, and incorporating customer feedback. Up-to-date information ensures AI tools provide answers that align with your latest products, policies, and services.
Periodically review how well your AI tools are using your help center content to address customer needs. Identify gaps in information and fine-tune articles as needed.
Dr. Bronner’s built their help center to power AI Agent, a conversational support assistant that answers both transactional and personalized customer inquiries in the same style as a human agent. Making this change helps the brand save $100,000 a year and decrease their resolution time by 74%.

💡Pro Tip: Transform your help center into an AI training powerhouse with Gorgias’s help center AI optimization guide. This guide offers actionable tips for making your knowledge base AI-ready.

By using your help center to power AI tools, you’ll improve customer self-service options and lighten the load on your support team. AI-enhanced support delivers faster resolutions, higher customer satisfaction, and a scalable approach to customer service.
Refreshing your help center isn’t just about improving customer experience—it’s a game-changer for your entire support strategy. With tools like Gorgias’s Help Center, you can empower customers to self-serve while equipping your team with the resources they need to excel.
In 2025, make your help center the cornerstone of your support operations—and watch the results speak for themselves.
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TL;DR:
This year, 71% of customer experience (CX) leaders are using AI and automation to handle the holiday shopping season. These tools, including AI agents and email autoresponders, speed up tasks like responding to customers and updating orders.
But answering tickets isn't enough. Responses must also be high-quality, whether from humans or AI. And while customer satisfaction (CSAT) is the standard measure of how successful these interactions are, they have major limits.
CSAT scores don’t tell the full story about whether agents were helpful or if they used on-brand language. These gray areas in quality lead to missed sales, higher return rates, and frustrated customers during peak periods.
AI quality assurance (QA) is changing that. In this article, we’ll see what QA looks like today, how AI can simplify the process, and how CX teams can use tools like Auto QA to improve quality across all conversations.
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Today, QA in customer support is a largely manual responsibility. Customer conversations are reviewed by CX team leads to ensure customer satisfaction and identify areas for agent coaching. Team leads evaluate agent responses against a checklist of best practices, including the proper use of language, product knowledge, consistency, and helpfulness.
However, reviewing tickets takes a long time.
QA is important, but it's hard to prioritize when customers are actively waiting for help with refunds, urgent order edits, or negative reviews. And when CX teams are under-resourced and short-staffed, it’s easy to put QA on the back burner.
What’s more, as AI plays a bigger role in responding to customers, quality assurance must evolve to ensure the quality of AI-generated responses, not just human responses.
Over time, the lack of QA in CX can hold back support teams for three reasons:
AI-powered quality assurance (QA) uses AI to automate the process of reviewing customer interactions for resolution completeness, communication, language proficiency, and more.
Instead of team leads spending hours manually sifting through tickets, AI takes over and evaluates how well tickets were resolved by agents.
Shifting this traditionally manual work to an automated process pulls teams out of the weeds and into more beneficial work like speaking to customers and upselling.

With AI QA, routine ticket reviews are not just an optional part of your customer service strategy, they become a permanent part of it. The road to greater customer trust, resolution times, and stronger product knowledge becomes easier.
Read more: Why your strategy needs customer service quality assurance
Manual QA is like trying to review a handful of tickets during an incoming flood of new customer requests. Team leads can only focus on a small sample, leaving most interactions unchecked. Without complete visibility, creating a standard across all interactions is challenging.
Now, switch over to AI QA. You don’t have to choose between QA duty or answering tickets—QA checks are automatically done. You’ll still need to monitor AI’s performance, but now there’s more time to focus on creating strategies that improve the customer experience.
Here’s how AI QA and manual QA measure up to each other:
|
Feature |
AI QA |
Manual QA |
|---|---|---|
|
Number of Tickets Reviewed |
All tickets are reviewed automatically. |
Only a small sample of tickets can be reviewed. |
|
Speed of Reviews |
Reviews are completed instantly after responses. |
Reviews are time-consuming and delayed. |
|
Consistency |
Feedback is consistent and unbiased across all tickets. |
Feedback varies depending on the reviewer. |
|
Scalability |
Scales, regardless of ticket volume. |
Struggles to keep up with high ticket volumes. |
|
Agent Feedback |
Provides instant, actionable feedback for every resolved ticket. |
Feedback is delayed and limited to a few cases. |
|
Leader Advantage |
Frees up leaders to train the team and improve workflows. |
Disadvantageous, as leaders spend most time manually reviewing tickets. |
AI quality assurance helps CX leaders move beyond manual reviews by offering fast, thorough insights into performance and customer needs. Here are seven key benefits it brings to your team.
AI QA reviews every ticket, giving CX leaders a complete view of agent performance and customer trends. Nothing slips through the cracks, so you can act on real data each and every single time.
What the team wins: Key areas to focus on to improve the customer experience.
What the customer wins: A consistent support experience where their concerns are fully addressed.
Only a third of customers highly trust businesses, and without QA checks in place, that trust only deteriorates.
AI QA feedback can highlight confusing policies or common product issues that lead to unhappy customers. With instant feedback, teams can quickly make changes and create better, consistent customer experiences.
What the team wins: Faster fixes for recurring issues.
What the customer wins: A smoother, frustration-free experience.
Agents can receive feedback that instantly highlights gaps in workflows or unclear escalation steps. This is an efficient way to resolve issues within the wider team before they become more significant problems.
What the team wins: Process issues are solved quickly.
What the customer wins: Faster resolutions with little to no delays.
AI QA evaluates both Gorgias AI Agent and human agent interactions using the same criteria. This creates a level playing field and ensures all customer interactions meet the same quality standards.
What the team wins: Fair evaluations for both AI and human responses.
What the customer wins: High-quality support, no matter who handles the ticket.
With less time spent on manual reviews, leaders can dedicate more energy to team development. Training sessions guided by AI insights help agents improve quickly and ensure the team delivers support that aligns with protocols.
What the team wins: More focused skill-building based on data.
What the customer wins: Clearer and more accurate support.
AI QA is helpful for showing agents which areas they need more training on, whether it's being better about using brand voice or polishing up on product knowledge. This leads to better support processes and stronger product understanding across the team.
What the team wins: Better support tactics and product expertise.
What the customer wins: Faster resolutions due to knowledgeable agents.
Since all tickets are reviewed, teams can feel confident they’re delivering high-quality support on a regular basis. Customers get clear, helpful answers, while agents gain insights from every ticket with AI feedback.
What the team wins: Consistent support performance.
What the customer wins: Reliable support they can trust.
AI QA analyzes tickets using predefined categories to evaluate how complete and helpful agent responses are. Let’s take a closer look at how it maintains accurate ticket reviews with an AI QA tool like Gorgias’s Auto QA.
Auto QA evaluates tickets based on three key areas: Resolution Completeness, Communication, and Language Proficiency.
For Resolution Completeness, it checks if all customer concerns were fully addressed. For example, if an agent resolves only one of two issues raised, the ticket is marked incomplete. Tickets where customers resolve issues on their own or don’t respond to follow-ups can still be graded as complete if handled appropriately.
Communication quality is scored on a scale of 1 to 5, assessing clarity, professionalism, and tone. Agents earn higher scores when they provide clear solutions and remain positive throughout the interaction.
Finally, Language Proficiency evaluates whether an agent displayed high proficiency in the language of the conversation. The score considers how well spelling, grammar, and syntax were employed.

Auto QA isn’t set in stone. Team leads can expand on AI-generated feedback by adding their comments. For example, if a resolution is graded as ‘Incomplete,’ a team lead can explain why and provide additional context. This helps clarify the evaluation for the agent and also helps the AI model improve over time.
Ready to bring the benefits of AI QA to your team? Here’s how to get started with Auto QA:
AI QA isn’t just about automating ticket reviews — it empowers CX leaders to focus on what truly matters: training and improving processes.
Leave spot-checking and inconsistent application of policies and brand voice in the past. As a built-in feature of Gorgias Automate, Auto QA makes high-quality customer interactions your brand’s standard.
Book a demo now.
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TL;DR:
Nailing customer support during BFCM is all about staying ahead of the game and making smart moves—fast.
But the real key to success lies in what you do when the rush is over. Treating BFCM as a learning opportunity allows you to refine your customer experience (CX) and set yourself up for an even better performance next year.
Without a plan for what to do after Black Friday, it’s easy to repeat mistakes or overlook key trends that could make all the difference next year.
In this article, we’ll share a simple framework to help you evaluate your BFCM performance and turn insights into actionable steps for long-term CX improvement.
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It’s best to reflect on key areas like customer service, tech performance, customer behavior, and operations right after BFCM versus waiting until late next year.
By taking a closer look now, you can spot what worked, fix what didn’t, and start applying those insights to other big sales events throughout the year—not just BFCM.
A little effort now = a lot of payoff later!
By analyzing key metrics, you can identify what worked, where your team excelled, and what areas need improvement to better prepare for future busy seasons. Key metrics include:
Tools like Gorgias’s Ticket Insights can reveal which issues—like discounts, shipping policies, or damaged orders—dominated your support tickets.

For a more comprehensive view, Gorgias’s Support Performance dashboard shows how customer service influenced sales, including tickets converted, conversion ratios, and total revenue. These insights are invaluable for understanding the connection between support efficiency and revenue growth.

Brands like Obvi, a leading supplement company, have leveraged Gorgias to enhance their support strategies.
Obvi serves a large number of shoppers seeking pre-sales guidance to choose the right supplements. By using Gorgias’s Flows and Article Recommendations, they provide instant, automated answers to frequently asked questions directly within Chat.
Here’s how it works:

To fine-tune their approach, Obvi uses data from their tickets to identify recurring customer questions. By analyzing the gaps between their initial FAQs and real customer inquiries, they adjusted their automated responses to better meet customer needs.

“We thought we knew what our FAQs were, but data from Gorgias was incredibly insightful to understand which FAQs to automate. That's one reason it's really valuable to have our Helpdesk tickets and automation features in one tool.”
—Ron Shah, CEO and Co-founder at Obvi
While marketing efforts often steal the spotlight, savvy brands know that backend systems are the unsung heroes of Black Friday and Cyber Monday.
Start by auditing critical areas such as platform downtime, checkout errors, or slow response times. These issues not only frustrate shoppers but can also lead to lost revenue and customer loyalty during your busiest shopping days of the year.
Next, evaluate how well your tools were able to manage peak volumes. Did your helpdesk, CRM, and ecommerce platforms work seamlessly together, or were there gaps in your integrations?
If switching between platforms slowed your team down or caused data silos, consider streamlining your tech stack with an all-in-one CX solution.
For example, conversational AI platforms like Gorgias enable CX teams to consolidate support, sales, and automation into a single tool. Gorgias combines Helpdesk and AI Agent to resolve customer issues efficiently, while Convert supports upselling and increasing customer lifetime value.
A streamlined, integrated platform not only boosts efficiency but also helps your CX team focus on what matters most: delivering exceptional customer experiences.
Start by reviewing product demand, buying patterns, and cart-building behaviors. Were there any unexpected customer needs or shifts in preferences? Identifying these trends can help you refine your inventory planning, marketing strategies, and product offerings.
For example, here’s a detailed breakdown of what to look for:
Use these insights to adjust inventory planning for future campaigns. Ensure you have sufficient stock of trending products and create promotional bundles for underperforming items.
Tailor future cart-building promotions to encourage higher Average Order Value (AOV). For instance, highlight complementary products or offer discounts on bundles.
Incorporate these suggestions into your product development or cross-sell strategies. Highlight related products in future campaigns to meet these emerging needs.
If you have an FAQ page or Help Center, evaluate how well it performed. Did customers find the information they needed, or did they still open tickets for common questions?
Metrics like Article Views, Number of Searches, and Click-Through Rates can show how effectively your self-service resources meet customer needs.
If customers contact support for information already in your Help Center, it may indicate unclear articles or poor visibility of resources. This means you should rewrite unclear articles, optimize search terms, and ensure Help Center links are prominently displayed across your website and emails.
BFCM is a stress test for your operations, and reflecting on how well your systems handled the surge can help you uncover critical areas for improvement.
Start by reviewing your staffing during peak periods. Did your customer service and warehouse teams feel overwhelmed, or were they adequately supported?
Questions to Ask:
Next Steps:
Preparing your team with a more flexible schedule and extra resources for high-demand areas can make all the difference.
If order fulfillment workflows slowed down or became error-prone, it may be time to optimize your processes.
Questions to Ask:
Next Steps:
Stockouts or overstock situations during BFCM can directly impact both sales and customer satisfaction.
Questions to Ask:
Next Steps:
Operational challenges often have a ripple effect on customer experience. By reflecting on these areas—staffing, fulfillment, and inventory—you can identify actionable improvements that streamline operations and create a smoother experience for both your team and your customers.
Once you've reviewed the key areas of your BFCM performance, the next step is turning those insights into actionable strategies. Here’s how to build a CX improvement plan that sets you up for long-term success.
Start by centralizing everything you’ve uncovered from your retro.
Use collaborative tools like Notion, Google Docs, or Trello to organize insights across customer service, tech performance, and operations.
And don’t just focus on observations—highlight actionable takeaways. For example, instead of noting “high contact rates,” document the underlying causes, like gaps in FAQs or unclear return policies.
If you’re feeling overwhelmed by the volume of data, let AI do the heavy lifting. Use prompts like these to quickly spot patterns:
AI tools can save you time and ensure nothing slips through the cracks as you plan your next steps.
Analyzing challenges in your CX processes can reveal quick wins and long-term improvements. Here are a few common support pain points and how to address them:
A surge in customer inquiries often signals that self-service options aren’t meeting expectations.
Solution: Add or update tools like chat widgets, Help Centers, and post-purchase emails to proactively answer common questions.
This usually points to workflow inefficiencies or a lack of team bandwidth.
Solution: Use automation to prioritize urgent tickets, deflect repetitive inquiries, and ensure smoother workflows.
Frustration with slow resolutions or insufficient empathy often leads to poor satisfaction ratings.
Solution: Invest in empathy training and implement faster resolution strategies, like automating FAQs or integrating sentiment detection tools to flag unhappy customers.
While tools like Gorgias’s AI Agent can streamline support, improper setup can lead to automation loops that frustrate customers.
Solution: Define rules for when AI should escalate to a human, feed it more comprehensive data (like updated Help Center articles), and set boundaries for topics it shouldn’t handle.

For example, even with the efficiency provided by their Helpdesk, Obvi found Black Friday and Cyber Monday to be a hectic and stressful period for their small customer support team—just one full-time agent and half of another team member’s time.
The influx of customer inquiries made it difficult to focus on more complex tickets that could save sales from unhappy customers or convert inquiries into purchases. Instead, their team was bogged down by thousands of repetitive questions, like “Where is my order?”
Automating answers to repetitive questions gave the Obvi team the room to focus on personalized and revenue-driving customer interactions, like engaging with their community of 75,000 women.
“Instantly, our CX team had time to prioritize important matters, like being active in our community of 75,000 women instead of sitting answering emails.”
—Ron Shah, CEO and Co-founder at Obvi
The extra bandwidth helped Obvi drive over 3x the purchases from support conversations compared to previous years. AI Agent also enabled their team to reach inbox zero by 6 pm—during Black Friday week!
By automating 27% of their inquiries, they not only improved their response times but also handled over 150 tickets daily with just 1.5 agents, driving 10x more sales during BFCM.
Even the smallest changes can deliver a big impact.
For example, update FAQs based on ticket trends or refine chat flows to reduce repetitive questions. Consolidating your CX tools into an omnichannel helpdesk like Gorgias can also reduce agent workload while delivering consistent customer experiences.
Repetitive inquiries—like shipping updates, return questions, or product FAQs—don’t need to consume your team’s time. Automating these workflows can significantly lighten your team’s load while keeping response times quick.
Gorgias users, for example, can automate up to 60% of support tickets with conversational AI tools like AI Agent, enabling teams to focus on higher-value interactions.
Quick wins aren’t just about streamlining support—they can also drive measurable results.
For instance, Pajar, a footwear brand, leverages AI Agent to handle common inquiries in English and French. While this is a feature they use year-round, it’s handy during holiday shopping seasons when support teams are under pressure to respond quickly.

This freed up their small team of five agents to focus on complex tickets, achieving impressive results:
With tools like AI Agent and Sentiment Detection, you can automate prioritization for tickets—such as flagging urgent issues or unhappy customers—while still maintaining a personal touch.
Peak season often highlights gaps in both team training and CX tools. Addressing these areas not only improves your team’s ability to handle high-pressure situations but also fosters a stronger customer-first mindset across your organization.
Start by leveraging the feedback you’ve collected. Your team has so much data they can review between channels like email, SMS, chat, and social media—both compliments and complaints. You need to be willing to listen to every customer’s needs.
At Love Wellness, customer feedback is treated as a daily priority.
The team has a dedicated Slack channel for feedback, where team members regularly drop insights from all touchpoints. This collaborative approach helps them get familiar with recurring themes, dissect customer needs, and work together on solutions.

The Love Wellness team recommends scheduling recurring feedback share sessions with Product or Website teams—or even inviting those teams into Gorgias to create dedicated views for feedback categories like product improvements or website issues.
Beyond tools and processes, training is crucial. Their team also emphasizes the importance of fostering a customer-first mindset at all levels:
Customer service is one of the main ways they build trust with customers, especially in the personal care and women’s health niche. That’s why the Love Wellness team created an immersive customer experience training program that involves everyone—from the company's president to its office manager.
This holistic approach ensures that every team member, regardless of their role, understands the company’s purpose and how their actions contribute to a seamless customer experience.
Your customer support team isn’t just there to clear tickets—it’s a key driver of revenue, retention, and customer lifetime value (CLV). Yet, too many teams measure success based solely on metrics like response and resolution times. While these are important, they’re only part of the story.
As Zoe Kahn, Manager of Customer Experience and Retention at Chomps, explains:
“Aiming for overly broad goals of ‘surprising and delighting’ customers without a real understanding of how support impacts the whole customer journey or business ROI is a common pitfall. Customer experience, largely driven by the support team, touches every stage of the journey—from pre-sales to post-sales—and directly influences more sales and loyalty.”
To demonstrate CX’s value, it’s crucial to track metrics that reflect your team’s true impact on the business. For example:
By focusing on these KPIs, you’ll incentivize your support team to go beyond answering questions and actively contribute to business goals. This could include suggesting products during conversations, encouraging happy customers to leave reviews, or proactively addressing issues that lead to churn.

Teams using Gorgias have even greater opportunities to prove ROI through tools like the Revenue Statistics dashboard, which tracks metrics like tickets converted into sales, conversion rates, and total revenue driven by support interactions.
“Without knowing how much money your customer experience (CX) drives, you’ll never fully understand your impact on the business or have the data needed to advocate for more resources from leadership.”
—Zoe Kahn, Chomps
The best way to close out your post-BFCM retro is by setting clear, measurable goals for next year. Use this year’s insights to create actionable targets that enhance your customer support and CX strategy:
Tools like Gorgias make it easier to turn these goals into reality. With powerful automation, integrated insights, and scalable support solutions, you can transform this year’s lessons into meaningful, lasting improvements.
Start planning now to make next year’s BFCM your smoothest—and most successful—yet!
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TL;DR:
At Gorgias, we’ve embraced the concept of high talent density, introduced by Netflix co-founder and CEO Reed Hastings in No Rules Rules, as a foundation of how we operate. The idea is simple: a team is at its best when every member is highly skilled and performing at their peak.
I’ll walk you through exactly how we’ve built a workplace that prioritizes talent density by breaking down what the concept means, how it shapes our hiring process, and how we keep Gorgias a rewarding environment to grow in.
High talent density refers to having a team where each member is highly skilled and performs at their best. When a group consists of top performers, their collective effectiveness increases. Hastings notes, "Talented people make one another more effective."
For example, in a team of five exceptional employees, each individual's high performance elevates the group's overall success. If there is even one underperformer, a team's effectiveness decreases by 30 to 40 percent.
We follow three pillars to maintain and grow high talent density. These pillars guide how we build and sustain a team of exceptional performers at Gorgias.
To bring this to life, we’ll use an analogy of colors to represent different types of performers in our talent pool:

Let’s take a closer look at how we practice each of these pillars below.
Every manager wants to hire someone exceptional, but even with the best intentions, it doesn’t always work out.
To clarify, we’re looking for someone great to do the job now but has the potential to grow and stay strong as the company evolves.
Here’s how we approach it.
Let’s be upfront: great talent often comes with a higher price tag.
The first step in building high talent density is offering competitive pay. Exceptional people expect to be compensated for their contributions, and rightly so.
A single outstanding hire, even if paid 50% more than two average employees, often delivers far greater results.
This is especially true in creative roles, where the impact of a single talent can be worth that of several others. It’s certainly not easy to prioritize compensation when resources are tight, but talented people are an investment — and talent is usually expensive.
Related: How we built an international SAAS salary calculator for our distributed team
Great candidates don’t always come knocking on your door. The best talent is often already employed, not actively looking for a new role.
To hire the best, we go beyond applications and invest heavily in proactive sourcing.
At Gorgias, we rely on scorecards and standardized feedback forms to assess every applicant fairly and thoroughly. We also include role-specific assessments or assignments as part of the process.
While some argue that take-home tasks are no longer standard, we’ve found them invaluable. A strong interview doesn’t always translate into strong performance, and these assignments often reveal critical insights into a candidate’s true capabilities.
Referrals are another piece of the puzzle. A-players tend to know and recommend other A-players. While leveraging referrals, we also keep a close eye on maintaining diversity to make sure everyone gets the same chance.
Performance isn’t static. Someone who was a top performer last year might not meet expectations today, especially as the company grows and their role evolves.
To stay objective, we pair performance reviews with bi-yearly cross-evaluation talent reviews. Cross-evaluations provide a broader perspective, helping managers see beyond potential biases and assess whether a top talent has changed in performance quality.
These regular evaluations ensure we’re always aware of who is meeting expectations and who may need support or a more difficult conversation.
While Netflix's philosophy is to immediately separate with employees when they underperform, we believe in a more empathetic approach that follows our company’s core value of being 100% honest.
At Gorgias, we train managers to deliver clear, actionable feedback so team members always know where they stand and how they can improve. To us, honesty means being thoughtful, encouraging, and focused on helping people grow.
We also use Performance Improvement Plans (PIPs) as a tool for growth. We don’t simply view them as compliance tools, but as opportunities for employees to get back on their feet. In fact, 50% of our PIPs result in team members regaining performance.
Sometimes, despite feedback and coaching, parting ways becomes the best option for both the employee and company. When that happens, we believe in making the transition as respectful and fair as possible.
Offering a strong severance package not only supports employees during their transition but also empowers managers to make tough decisions confidently. It reflects our shared responsibility and ensures we treat people with dignity, even when their time with us comes to an end.
When a company grows, employees need to match that pace to keep delivering at a high level. This requires consistent learning and development to meet the challenges of each new stage.
Growth doesn’t happen by accident. As Daniel Coyle explains in The Talent Code, greatness isn’t born; it’s grown through “deep practice.”
To encourage growth, Gorgias managers hold career conversations every six weeks, focusing on the “3Es”: education, exposure, and experience. These discussions identify growth areas, leverage networks, and clarify the steps team members can take to excel.
We also reward our top performers with opportunities beyond financial incentives. From double learning stipends to travel experiences and executive mentorships, these rewards keep our “dark green” talents motivated and engaged.
Read more: Why we don’t increase salaries based on performance
In the pursuit of high talent density, results are important, but so is maintaining a positive, team-oriented environment.
A top performer with a toxic attitude can harm the environment you’re working hard to build. For that reason, we hire and nurture people who align with our values, show respect for others, and contribute to a collaborative culture. Both the what (talented employees) and the how (exemplary behavior) matter.
I believe this is one of the toughest topics when it comes to talent management.
Top performers are eager to work hard and prove their worth. Oftentimes, they approach work intensely and passionately. However, too much intensity can lead to exhaustion. And, of course, tired employees can’t deliver well.
That’s why managing pressure is crucial to maintaining high talent density. Introducing programs and initiatives that support the well-being of your employees helps prevent stress and burnout.
We take a tailored approach to prevent burnout, recognizing that one size doesn’t fit all. Having strong management training and great HRBPs (HR Business Partners) are the most impactful pieces. They help uncover the underlying issues of burnout: lack of vacation time, heavy workload, personal challenges, or misalignment.
Once the issues are clear, we provide the right tools to help. This could include coaching, training, enhanced benefits, or adjusted workloads.
We use specific metrics to gain insights into the effectiveness of our talent management strategies and refine our approach as needed.
Here are the metrics we track to evaluate talent density:
By regularly tracking these metrics, we can see where we may be falling short — whether that’s being slow to part ways with low performers, struggling to attract great talent, or losing top performers unnecessarily.
The ultimate goal of having strong talent density is to build a well-performing organization.
After each talent review, HRBPs will work hand in hand with managers to refine the organizational chart. They identify opportunities for improvement, such as promoting top talent, adjusting scopes of responsibility, or making changes to strengthen the team.
Ultimately, you should always make sure that your top performers are leading the most critical and top-priority initiatives.

In my role as VP of People at Gorgias, I’ve seen how fast growth fuels the resources and opportunities needed to attract and develop exceptional talent. High performers thrive in environments with big goals and fast results, but it’s up to us to create the right conditions for them to succeed.
Sustaining high talent density takes dedication and humility. It means holding ourselves to high standards while being transparent. While we’ve made great strides, there’s always more to learn and refine.
As we continue this journey, let us remain humble, acknowledging that there is always room for growth and improvement.


