

TL;DR:
CSAT surveys are the fastest way to measure customer happiness after any interaction with your brand. Unlike lengthy feedback forms that customers abandon, a well-designed CSAT questionnaire captures satisfaction data in seconds while the experience is still fresh.
This guide covers the exact questions, templates, and distribution strategies that ecommerce brands use to collect actionable feedback and improve their customer experience. You'll learn how to create surveys that customers actually complete and turn those responses into real business improvements.
A CSAT survey questionnaire is a measurement tool that captures how satisfied customers are with a specific interaction, product, or service. This means you ask customers to rate their experience on a scale, usually from one to five, right after they interact with your brand.
The core of any CSAT survey is one simple rating question: "How satisfied were you with [specific interaction]?" Customers respond on a scale from Very Dissatisfied to Very Satisfied. This simplicity drives higher completion rates than complex surveys.
CSAT differs from other feedback tools in timing and focus. While relationship surveys measure long-term loyalty, CSAT captures immediate reactions to specific touchpoints like support conversations, deliveries, or product experiences. The questionnaire becomes a survey instrument when you add follow-up questions to understand the "why" behind ratings.
Different metrics serve different purposes in your customer experience strategy. Using the right tool for the job ensures you get clear, actionable data that helps you make better decisions.
CSAT excels at measuring satisfaction with specific interactions. Use it after support tickets, deliveries, or purchases when you need quick feedback on how well you performed. The 5-point scale makes it easy for customers to respond and for your team to track trends.
Key benefits of CSAT surveys:
Net Promoter Score (NPS) asks customers how likely they are to recommend your brand on a 0-10 scale. This metric predicts customer retention and word-of-mouth growth. Send NPS surveys quarterly or after customers have experienced your full product range.
Customer Effort Score (CES) measures how easy it was for customers to complete a task or resolve an issue. Low effort correlates with higher loyalty. Deploy CES after complex processes like returns, account setup, or multi-step support resolutions.
The format of your questions directly impacts response quality and completion rates. Match your question type to the data you need and make it as easy as possible for customers to respond.
Likert scales offer five to seven response options from one extreme to another, like Strongly Disagree to Strongly Agree. Use them for satisfaction ratings, agreement levels, and frequency measurements. They provide data that's easy to analyze while giving customers enough options to express their true feelings.
Yes/No or thumbs up/down questions work best for simple confirmations. Think: "Was your issue resolved?" or "Would you shop with us again?" Binary choices maximize response rates but sacrifice detail. Use them when you need high participation over deep insights.
Text responses explain the "why" behind ratings. Keep them optional and place them after rating questions with prompts like, "What's the primary reason for your score?" These insights guide improvement priorities, even with lower response rates.
These proven questions address the moments that matter most for online shoppers. Start with these templates and adapt them to your brand's specific touchpoints.
Post-purchase surveys capture satisfaction with the buying and delivery experience:
Support surveys measure how well your team resolved customer issues:
Product surveys help you understand satisfaction with your actual offerings:
Loyalty questions gauge future purchase intent and advocacy:
Building an effective CSAT survey requires strategic planning before you write a single question. Following a structured process ensures your survey delivers reliable, actionable data.
Start with the business decision your survey will influence. Are you measuring support quality to improve agent training? Tracking delivery satisfaction to evaluate shipping carriers? Clear objectives determine which questions to ask and how to analyze results.
Choose the right tool for your goal. Select CSAT for transactional feedback, NPS for relationship health, or CES for process improvement. Match your survey type to your objective: post-interaction surveys for operational metrics, periodic surveys for strategic insights.
Use simple language that customers understand immediately. Avoid leading questions like "How excellent was our service?" which bias results. Instead, use neutral phrasing like, "How would you rate our service?" Test questions internally to catch confusion before launch.
Keep surveys under two minutes. Place rating questions first, followed by optional open-ended questions. Since most customers respond on mobile, use large buttons, minimal scrolling, and responsive design. Preview on multiple devices before sending.
Pilot your survey with a small customer segment first. Monitor completion rates, response quality, and technical issues. After launch, review results weekly to identify question improvements and timing adjustments.
Timing and channel selection determine whether customers engage with your survey or ignore it. The right approach maximizes response rates and data quality.
Send transactional surveys within 24 hours of the interaction while details remain fresh. Post-purchase surveys perform best two to three days after delivery. Support surveys should trigger immediately after ticket resolution.
Avoid survey fatigue by limiting requests to once per customer per month. During peak seasons like Black Friday, increase post-purchase surveys but reduce follow-up questions to maintain completion rates.
Different channels work better for different types of feedback:
Collecting feedback without acting on it damages customer trust. Here's how to close the loop and turn scores into improvements.
Assign clear ownership for each feedback category. Support owns resolution feedback, fulfillment owns delivery ratings, product owns quality scores. Create weekly reviews where owners present trends and action plans to improve your CSAT scores.
Break down scores by customer segment, product line, and support channel. Compare new versus returning customers. Identify which segments drive low scores and prioritize improvements with highest impact.
Key segmentation approaches:
Follow up with dissatisfied customers within 48 hours. Thank satisfied customers and request reviews. Share improvements made based on feedback through email updates or Help Center articles. This shows customers their voice creates change.
Use root cause analysis on negative feedback patterns. Tag responses by theme to identify systemic issues. Create escalation workflows for scores below your threshold. Set service level agreements for follow-up based on score severity.
CSAT surveys give you the customer insights needed to improve your support, products, and overall experience. The templates and strategies in this guide provide your starting framework for collecting valuable feedback data.
Gorgias automates CSAT collection right within your helpdesk. Send surveys automatically after ticket resolution, track scores by agent and topic, and identify improvement areas through AI-powered insights. This turns feedback into a powerful tool for operational excellence and customer retention.
Book a demo to see how Gorgias turns feedback into better customer experiences.
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TL;DR:
The way shoppers buy online has shifted and customers are at the center.
They no longer want to scroll through product pages, dig through FAQs, or wait 24 hours for an email reply. They open a conversation, ask a specific question, and expect a useful answer in seconds. Brands that can’t deliver these experiences at scale are seeing customer hesitation turn into abandoned carts and lost revenue.
This shift has a name: conversational commerce. It's the practice of using real-time, two-way conversations as your primary sales channel, through chat, AI agents, messaging apps, and voice.
What started as an experiment for early adopters has become a key growth lever, with 84% of ecommerce brands treating conversational commerce as a strategic pillar this year vs. last year.

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

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

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

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

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

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

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

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

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

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

Voice-based purchasing is the biggest bet on the horizon. Only 7% of brands currently use voice assistants for commerce, but 89% expect it to be standard by 2030. The vision is a customer who can reorder a product, check their subscription status, or manage a return entirely over the phone.
Proactive AI is the other major shift. Rather than waiting for a customer to reach out, AI will anticipate needs based on browsing behavior, purchase history, and where someone is in their relationship with your brand. Think of it as the digital equivalent of a sales associate who remembers what you bought last time and knows what you're likely to need next.
Explore where ecommerce brands are allocating their AI budgets in the full report.
The brands winning in 2026 are creating smart, scalable systems where AIhandles volume and humans handle nuance. They’re treating every conversational channel as an opportunity to serve and sell.
The data is clear: AI adoption is accelerating, customer expectations are rising, and the revenue impact of getting this right is measurable.
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TL;DR:
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:
Customer education has become a critical factor in converting browsers into buyers. For wellness brands like Cornbread Hemp, where customers need to understand ingredients, dosages, and benefits before making a purchase, education has a direct impact on sales. The challenge is scaling personalized education when support teams are stretched thin, especially during peak sales periods.
Katherine Goodman, Senior Director of Customer Experience, and Stacy Williams, Senior Customer Experience Manager, explain how implementing Gorgias's AI Shopping Assistant transformed their customer education strategy into a conversion powerhouse.
In our second AI in CX episode, we dive into how Cornbread achieved a 30% conversion rate during BFCM, saving their CX team over four days of manual work.
Before diving into tactics, understanding why education matters in the wellness space helps contextualize this approach.
Katherine, Senior Director of Customer Experience at Cornbread Hemp, explains:
"Wellness is a very saturated market right now. Getting to the nitty-gritty and getting to the bottom of what our product actually does for people, making sure they're educated on the differences between products to feel comfortable with what they're putting in their body."
The most common pre-purchase questions Cornbread receives center around three areas: ingredients, dosages, and specific benefits. Customers want to know which product will help with their particular symptoms. They need reassurance that they're making the right choice.
What makes this challenging: These questions require nuanced, personalized responses that consider the customer's specific needs and concerns. Traditionally, this meant every customer had to speak with a human agent, creating a bottleneck that slowed conversions and overwhelmed support teams during peak periods.
Stacy, Senior Customer Experience Manager at Cornbread, identified the game-changing impact of Shopping Assistant:
"It's had a major impact, especially during non-operating hours. Shopping Assistant is able to answer questions when our CX agents aren't available, so it continues the customer order process."
A customer lands on your site at 11 PM, has questions about dosage or ingredients, and instead of abandoning their cart or waiting until morning for a response, they get immediate, accurate answers that move them toward purchase.
The real impact happens in how the tool anticipates customer needs. Cornbread uses suggested product questions that pop up as customers browse product pages. Stacy notes:
"Most of our Shopping Assistant engagement comes from those suggested product features. It almost anticipates what the customer is asking or needing to know."
Actionable takeaway: Don't wait for customers to ask questions. Surface the most common concerns proactively. When you anticipate hesitation and address it immediately, you remove friction from the buying journey.
One of the biggest myths about AI is that implementation is complicated. Stacy explains how Cornbread’s rollout was a straightforward three-step process: audit your knowledge base, flip the switch, then optimize.
"It was literally the flip of a switch and just making sure that our data and information in Gorgias was up to date and accurate."
Here's Cornbread’s three-phase approach:
Actionable takeaway: Block out time for that initial knowledge base audit. Then commit to regular check-ins because your business evolves, and your AI should evolve with it.
Read more: AI in CX Webinar Recap: Turning AI Implementation into Team Alignment
Here's something most brands miss: the way you write your knowledge base articles directly impacts conversion rates.
Before BFCM, Stacy reviewed all of Cornbread's Guidance and rephrased the language to make it easier for AI Agent to understand.
"The language in the Guidance had to be simple, concise, very straightforward so that Shopping Assistant could deliver that information without being confused or getting too complicated," Stacy explains. When your AI can quickly parse and deliver information, customers get faster, more accurate answers. And faster answers mean more conversions.
Katherine adds another crucial element: tone consistency.
"We treat AI as another team member. Making sure that the tone and the language that AI used were very similar to the tone and the language that our human agents use was crucial in creating and maintaining a customer relationship."
As a result, customers often don't realize they're talking to AI. Some even leave reviews saying they loved chatting with "Ally" (Cornbread's AI agent name), not realizing Ally isn't human.
Actionable takeaway: Review your knowledge base with fresh eyes. Can you simplify without losing meaning? Does it sound like your brand? Would a customer be satisfied with this interaction? If not, time for a rewrite.
Read more: How to Write Guidance with the “When, If, Then” Framework
The real test of any CX strategy is how it performs under pressure. For Cornbread, Black Friday Cyber Monday 2025 proved that their conversational commerce strategy wasn't just working, it was thriving.
Over the peak season, Cornbread saw:
Katherine breaks down what made the difference:
"Shopping Assistant popping up, answering those questions with the correct promo information helps customers get from point A to point B before the deal ends."
During high-stakes sales events, customers are in a hurry. They're comparing options, checking out competitors, and making quick decisions. If you can't answer their questions immediately, they're gone. Shopping Assistant kept customers engaged and moving toward purchase, even when human agents were swamped.
Actionable takeaway: Peak periods require a fail-safe CX strategy. The brands that win are the ones that prepare their AI tools in advance.
One of the most transformative impacts of conversational commerce goes beyond conversion rates. What your team can do with their newfound bandwidth matters just as much.
With AI handling straightforward inquiries, Cornbread's CX team has evolved into a strategic problem-solving team. They've expanded into social media support, provided real-time service during a retail pop-up, and have time for the high-value interactions that actually build customer relationships.
Katherine describes phone calls as their highest value touchpoint, where agents can build genuine relationships with customers. “We have an older demographic, especially with CBD. We received a lot of customer calls requesting orders and asking questions. And sometimes we end up just yapping,” Katherine shares. “I was yapping with a customer last week, and we'd been on the call for about 15 minutes. This really helps build those long-term relationships that keep customers coming back."
That's the kind of experience that builds loyalty, and becomes possible only when your team isn't stuck answering repetitive tickets.
Stacy adds that agents now focus on "higher-level tickets or customer issues that they need to resolve. AI handles straightforward things, and our agents now really are more engaged in more complicated, higher-level resolutions."
Actionable takeaway: Stop thinking about AI only as a cost-cutting tool and start seeing it as an impact multiplier. The goal is to free your team to work on conversations that actually move the needle on customer lifetime value.
Cornbread isn't resting on their BFCM success. They're already optimizing for January, traditionally the biggest month for wellness brands as customers commit to New Year's resolutions.
Their focus areas include optimizing their product quiz to provide better data to both AI and human agents, educating customers on realistic expectations with CBD use, and using Shopping Assistant to spotlight new products launching in Q1.
The brands winning at conversational commerce aren't the ones with the biggest budgets or the largest teams. They're the ones who understand that customer education drives conversions, and they've built systems to deliver that education at scale.
Cornbread Hemp's success comes down to three core principles: investing time upfront to train AI properly, maintaining consistent optimization, and treating AI as a team member that deserves the same attention to tone and quality as human agents.
As Katherine puts it:
"The more time that you put into training and optimizing AI, the less time you're going to have to babysit it later. Then, it's actually going to give your customers that really amazing experience."
Watch the replay of the whole conversation with Katherine and Stacy to learn how Gorgias’s Shopping Assistant helps them turn browsers into buyers.
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TL;DR:
In 2025, chat’s growth outpaced email by 2.5x quarter over quarter. Chat has become our most powerful customer experience tool for how shoppers discover products, ask questions, and decide to buy.
We knew it needed an upgrade, so we reimagined the entire experience from the ground up.
The result is 36% more engagement with product recommendations, nearly 2.25x more shoppers add-to-cart, and 7.3% more customer engagement.
In this post, we'll walk you through our thinking, what’s new in Chat, and how brands are already seeing big gains.
Chat has outpaced email support. Today’s shoppers prefer the speed of quick chat conversations over email. And when shoppers make a new move, we watch, listen, and move with them.
This behavioral shift isn’t happening in isolation. It aligns with the rise of conversational commerce and proves a universal move toward real-time conversations in ecommerce.
In fact, the signals were already there. Two years of building AI Agent showed us just how much design shapes behavior. The interface is the experience, and we knew that pushing chat experiences to closely resemble human interactions would transform how shoppers engage.
Our new and updated chat brings that vision to life. We believe that shopping is moving from static pages to conversations. This new update is built for how people actually want to shop.
The new design turns live chat into an interactive shopping surface made for modern shoppers. We've brought together multiple ways for shoppers to jump into chat, added clickable replies instead of typing, browsable product cards right in the conversation, and quick cart access.
Let's walk through what's new.
Chat now comes in a softer color palette that adapts to your store’s branding. We removed message bubbles in favor of an airy design that brings in the familiarity of speaking to your favorite conversational AI assistant. Every interaction now has the breathing room for deeper conversation and personalization.

It’s now easier for shoppers to get an answer with quick reply buttons and suggested questions in Chat. This replaces the tree-based flows of the previous Chat, removing the need to follow a fixed path. Shoppers can find answers faster without typing text-heavy explanations.

Browsing and buying within Chat is now possible. Previously, it only supported product links that would open in a new page. With the upgrade, you can view item details without leaving the conversation. Shoppers can browse, compare products, and add to cart in one place.

We’re keeping the context by removing the external redirects. The new interface lets shoppers browse product recommendations right in chat. View key product details, images, descriptions, variants, and pricing without opening a new tab.

Chat adds clickable questions on product pages — like “Is this true to size?” or “What’s the difference between shades?” — designed to match what a shopper is likely wondering in the moment. These context-aware prompts help remove buying hesitation before shoppers even think to ask.

Chat adds instant access to shopper actions, like a cart button and an orders button for returning customers. Shoppers can jump straight to their cart or check on an existing order without waiting for an agent to give them a status update.

Every update in Chat drives performance. We didn’t simply give it a makeover, we also fine-tuned its underlying mechanics.
When product suggestions are easy to browse, shoppers interact with them more. The new product cards make shopping feel natural, allowing customers to explore items at their own pace. That convenience led to a 36% increase in engagement with recommended products.
Chat keeps the entire shopping journey inside the conversation, from browsing and asking questions, to adding to cart and checking out. This new layout removes the usual tab-switching between chat and the website. Less friction has led to more than double add-to-cart actions than before the redesign.
Chat's cleaner design and contextual entry points make it easier for shoppers to start a conversation. With suggested questions on product pages and quick reply buttons, more visitors are choosing to engage earlier in their journey. This has resulted in a 7.3% lift in chat engagement.
Conversational commerce has moved from concept to reality. Chat makes it part of the everyday shopping experience, letting shoppers browse, ask questions, compare products, and check out in one interaction. It brings the ease of the in-person shopping experience into the digital world.
We built Chat to redefine the shopping experience. We hope you see it reflected in your customers’ journeys.
Book a demo to see what's possible with the new experience.

TL;DR:
Looking to grow an email list to capture leads or offer welcome incentives? These days, the default solution is to plaster a full-screen pop-up on your homepage.
It seems effective on the surface, collecting emails right off the bat, but dig deeper, and these pop-ups disrupt the shopping experience and skyrocket bounce rates—with 72% of customers exiting a website.
But how else do you get your message across?
That’s where Gorgias Convert comes in—a smarter, more customer-centric tool to drive conversions without pushing your visitors away.
Below, we’ll explore why it’s time to move on from full-screen pop-ups and how Gorgias Convert offers a better alternative for Shopify brands looking to boost engagement and revenue.
Pop-ups can be an effective marketing tool, but their full-screen counterpart often creates more problems than they solve. These intrusive overlays pose several challenges that can harm both user experience and your bottom line.
Full-screen pop-ups demand attention, often at the worst possible moment—like when a customer is browsing products or is just about to check out. This experience can frustrate visitors and lead them to abandon your site entirely.
The BBC says every extra second a page takes to load can cost you 10% of your users—and pushy pop-ups don’t help. If your pop-ups are poorly timed or overly intrusive, visitors feel unwelcome, causing them to leave before exploring your offerings.
Traditional pop-ups are static and one-size-fits-all. They can’t adjust messaging based on where the customer is in their shopping journey or their behavior on your site.
Many users employ ad blockers that filter out pop-ups altogether, meaning your message never even reaches a portion of your audience.
Gorgias Convert flips the script by offering a subtle, customer-friendly way to capture leads and drive sales without the drawbacks of full-screen pop-ups. Here’s why your Shopify brand should make the switch:
Gorgias Convert integrates seamlessly into your store, using a chat-based widget that feels like a natural part of the browsing experience. Using chat to double as a supporting and converting tool is less disruptive, allowing customers to explore your store at their own pace.

Convert makes it easy to bring any type of campaign to life. Catch the attention of the exact shoppers you want by detecting their browsing behavior, customer profile, cart attributes, and more.
For example, the exit intent campaign is the top-performing Convert campaign—it detects when a user is about to leave and displays a discount code. It’s fully customizable, allowing you to tailor offers based on how much time they’ve spent on a page, the number of items in their cart, or if they’ve visited more than three times without making a purchase.

Unlike one-size-fits-all pop-ups, Convert lets you tailor your messaging based on customer behavior, order history, and engagement. For example, if a customer is browsing a specific product, Convert can offer a relevant discount or incentive tied directly to that item.
With Convert, you’re not just collecting an email address—you’re starting a conversation. The tool allows you to engage with customers in real-time through pre-set flows that guide them toward taking action, whether it’s signing up for your newsletter, redeeming an offer, or completing a purchase.

Related: 6 types of conversational customer service + how to implement them
In 2024, smartphones were responsible for generating 68 percent of online shopping orders. To meet shoppers where they are, Convert’s chat-style interactions are optimized for mobile users. Unlike traditional pop-ups that don’t display correctly on smaller screens, Convert maintains a seamless experience for shoppers who prefer to shop on the go.

Using Convert means you can combine immediate assistance with smart marketing through its native integration with Gorgias and Shopify. For example, if a customer hesitates to make a purchase, you can intervene with a live chat offer or product recommendation in real-time.
The Shopify integration also allows you to generate unique discount codes that expire within 48 hours—preventing them from being shared on unauthorized coupon sites. These codes are automatically created with customizable thresholds, such as discounts for specific collections or individual users, without manual setup.

Convert allows you to test different messages and incentives, giving valuable insights into what resonates most with your audience. This data-driven approach ensures your lead capture strategy evolves with shoppers over time.
Read more: How campaign messaging can increase conversions
Shopify brands using Gorgias Convert have led to a conversion rate boost of 6-10% more across their website, up to a 24% click-through rate and 43% click-to-order rate, and improved customer satisfaction. By prioritizing a frictionless shopping experience, these brands are turning casual visitors into loyal customers.
Here’s what some happy brands have to say about Convert:
Haircare brand, Kreyol Essence, influenced 13% of revenue with Convert campaigns: “With Convert, we’ve not only improved our conversion rates but also created a seamless, personalized shopping experience that our customers love. It’s like having a personal assistant for each shopper. Thanks to Convert, we can interact with our customers and surface key information at the right time, turning clicks into connections."
Brands using customer service management agency, TalentPop, love how easy it is to generate revenue with Convert: “Clients are constantly surprised and delighted by how effective Gorgias Convert is for revenue generation. They especially appreciate that Convert can be used to target a diverse range of customers across the entire purchasing journey.”
In five months, yoga brand Manduka, increased revenue by 284.15% after using Convert: “Gorgias Convert has helped us make the shopping experience more intuitive. We can give a nice prompt to remind people of promotions we’re running, highlight specific product features, or just remind them we're here to help and answer questions. The chat campaigns make it easy for customers because they lead them to us, as opposed to them having to search for how to contact us for assistance.”
Shoppers want personalized experiences that respect their time and preferences. Full-screen pop-ups belong to an era of intrusive marketing that shoppers would rather leave in the past.
Gorgias Convert for your Shopify brand means delivering impactful interactions, more conversions, and an easy path to long-term customer loyalty.
Ready to make the switch? Start your effortless shopping journey today with Gorgias Convert. Chat with our team!

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:
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.


