Four months ago, our analysts were dealing with a barrage of questions. "What's our ARR by segment?" "Build me a dashboard for this quarter's pipeline." Quick asks piled up behind complex deep dives. Stakeholders waited for answers that should have taken seconds, and analysts spent their time fielding requests instead of doing the strategic work that creates the most value.
Today, anyone at Gorgias can ask a question in plain language and get an accurate, contextualized response in seconds. Not from a colleague or dashboard, nor from a generic answer from the internet. But a response built on our business context. We call it Cortex, our flagship internal AI agent.
In two months, Cortex went from an idea to fielding thousands of questions every week, recommending actions across the business, and deprecating the need for manual dashboard creation. While most companies right now are treating AI as an initiative — at Gorgias, AI is already part of how we work. 72% of Gorgias employees use Cortex each week, and that number is only growing.
We didn’t achieve this by simply plugging a large language model into our stack. LLMs are a critical part of the equation, but they aren't the driving force — it’s everything else under the hood: the infrastructure, context, platform architecture, and the team that brings it all together.
The framing problem most companies get wrong
The instinct across many companies today is to start with the model, pick a provider to solve a specific challenge, or invest heavily in getting the data right. All reasonable starting points, but most of them solve for one use case. Underneath that approach is a framing problem: seeing AI as an initiative — something you assign and measure. Seeing AI as another tool your company uses versus how your company operates.
We started somewhere different. Every company is built on four pillars: customers, people, product, and decisions. AI investments tend to place heavy emphasis on the first three. We started with the fourth. Our bet was that if we built everything around the need to make effective decisions first, asking what Gorgias needed to know to operate well, then our AI would become dramatically more powerful.
Cortex is that philosophy in practice
Cortex is our flagship internal AI agent, and the product where we established the tenets that now run through everything else we build: composable and modular infrastructure, governed context, and accessible from wherever decisions happen. Cortex lives in Slack, as well as across LLM vendors, in its own browser extension, and even on its own dedicated internal site.
Cortex doesn’t stop at answering questions. It can read and write to Notion, file Linear tasks, create HTML apps, automate signal delivery, and more. It operates across every layer of our stack, from dashboards to data pipelines, because we designed it as one integrated system. It is this connection that adds remarkable depth to what people can ask, and what they get in return.
A Sales Lead is pitching and asks Cortex for the full picture of the merchant. In a customized PDF, Cortex lists coverage gaps, pre-sale intent signals, and product fit options. Everything the sales lead needs to walk in with confidence.
A Senior Product leader asks, "How are we performing against OKR #1, and what can my team do to help accelerate it?" Cortex returns a full ARR breakdown, projected end-of-month attainment, segment-level findings, and connects it all back to company-level strategies. A suite of recommendations customized to the leader, the performance, and the signals that bridge how they can support our goals. The kind of answer that used to take someone a week to put together.
These aren't simple lookup queries. They require deep business context spanning multiple areas. Cortex handles these because its Decision Engine gives it the information to reason against governed data, metric definitions, and business context, turning a generic answer into a credible one.
Overnight, teams have built Cortex into how they work. They’re spending less time searching and more time finding answers, not because they were told to, but because Cortex reduced the distance between question and decision.
Flexibility as the foundation
Cortex’s modular infrastructure allows us to experiment and add new capabilities freely. We’ve already built two more internal AI agents made for entirely different use cases, but using the same Decision Engine as Cortex.
GAIA, our internal experimentation AI Agent, helps our customers identify opportunities in their AI Agent Guidance design. It takes institutional knowledge across our teams and turns it into a scalable system that drives automation and value to our customers. Our CEO, Romain Lapeyre, has been its most vocal advocate since day one.
When we needed a platform for investor readiness and board preparation, we built Oracle. Our board decks and talk tracks are informed and built with the same AI, and our numbers are validated every step of the way.
We’re continuing to expand new AI agents internally, exploring how they can create value for customers and our own teams.
AI has transformed how data teams create value, and we’ve already shifted to account for it
When AI handles thousands of analytical questions each week, the highest-value work for a data team shifts permanently. Late 2025, we repositioned from a Data Analytics function into a Decision Intelligence function — a structural change in what we own and how we operate.
Today, our analysts focus on the most sensitive, complex, and forward-looking decisions and analyses. They partner more deeply with stakeholders by driving next steps from signals. They're even building entirely new capabilities that didn't exist in their role descriptions months ago. Things like AI skills for Cortex, context curation, and insight and recommendation delivery. The role of the analyst hasn't diminished. It's expanded to encompass the most meaningful work an analyst can do: driving outcomes and ensuring those decisions can achieve them.
Our business support model has changed, too. Instead of embedding analysts and dedicated engineers within functional teams, we align capacity to the highest-impact company objectives and move fluidly across them. This model works even better because Decision Intelligence brings together both analytics and engineering teams under one roof.
Elliot Trabac leads our Data, Context and AI Engineering teams. The Decision Engine, Cortex, GAIA, and the platforms I've described exist because of the infrastructure his team innovated and built from the ground up. Noemie Happi Nono leads our Decision Strategy and Operations team, driving decision outcomes with stakeholders, advancing the development of Cortex skills and capabilities, and pushing into new areas of analysis every day.
Together, they're shaping what a modern data function looks like when AI becomes a standard building block for how a company operates.
What’s next for the Decision Intelligence team
The question of ROI is long gone. AI has opened the floodgates to more trusted and meaningful signals than ever. The natural next evolution is Proactive Intelligence, signals surfaced toward what you need to know, before you ask. And we're already building this because our architecture is designed to support it.
In the coming weeks, members of the Decision Intelligence team will go deeper into themes I've touched on here. Yochan Khoi, a Senior Analytics Engineer on our team, recently published a technical walkthrough of our context layer and will go further into building context strategies that scale. Others will cover infrastructure, analytical partnerships, evolving data assets into decision assets, and the cost and efficiency gains that make sustained AI investment viable.
AI hasn't changed the most important element of data and analytics functions — delivering outcomes — but it has raised the bar for what it looks like and how far we can take it. We’re just getting started.
Newsletter Signup
The best in CX and ecommerce, right to your inbox
Featured articles
Conversations Are Becoming a Revenue Channel: The Data Proves It
TL;DR:
- Customer journeys are collapsing to a single conversation. The traditional browse-and-buy journey is giving way to AI-guided shopping that moves from discovery to purchase in a single exchange.
- 79% of brands say AI-driven conversational commerce has increased their sales and purchase rates.
- AI-only influenced orders grew 63% in a single year, from 2.7 million in Q1 to 4.4 million in Q4.
- Brands treating conversation as a revenue channel. They’re not just a support function, generating higher AOV, shorter buying cycles, and stronger retention.
The page-based shopping experience dominated for decades. Customers would search, browse, compare, abandon, get retargeted, return, and eventually buy (sometimes).
That journey is no longer the only option.
Shoppers are turning to chat, messaging, and AI-powered tools to find what they need. Instead of clicking through product pages or reading static FAQs, they ask questions, have back-and-forth conversations, and get answers that move them closer to a purchase in real time. The path to checkout has changed, and the brands that recognize this are pulling ahead.
Read our 2026 State of Conversational Commerce Report to learn more about conversation commerce trends from 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
{{lead-magnet-1}}
The shopping journey has collapsed into a single thread
The traditional shopping journey was a solo experience. A shopper had a need, searched for options, browsed across sessions, and eventually made a decision — often days later, after being retargeted multiple times. Support only entered the picture after the purchase.
The conversation-led journey collapses that timeline:
- A shopper recognizes a need and starts a conversation via chat, messaging, or a search-triggered prompt
- An AI agent asks clarifying questions about preferences, budget, and constraints
- The AI provides personalized product recommendations in real time
- The shopper validates concerns about fit, compatibility, delivery, and returns, all inside the conversation
- The shopper completes the purchase directly within or immediately after that exchange
- The AI picks up the conversation post-purchase for order tracking and proactive support
- A human agent steps in only when the situation calls for it
What used to take days now takes minutes. Discovery, evaluation, and purchase happen in a single thread.
Conversation is a revenue strategy, not a support upgrade
79% of brands agree that AI-driven conversational commerce has increased sales and purchase rates in their business. When brands were asked to rank the highest-return areas:
- 38% cited improved customer support efficiency
- 23% pointed to higher customer retention and loyalty
- 20% saw improved purchase rates
Those numbers reflect something important: the value of conversation compounds. Faster support reduces friction. Better retention raises lifetime value. More confident shoppers buy more often and spend more per order.
The brands seeing the biggest returns aren't just using AI to deflect tickets. They're using it to create one-to-one shopping experiences at scale.
What the data shows about AI-influenced orders
Looking at AI-only influenced orders across key verticals like Apparel and Accessories, Food and Beverages, Health and Beauty, Home and Garden, and Sporting Goods, the growth across a single year was significant.
Across industries, ecommerce brands saw AI step into conversations, reduce shopper hesitation, and drive higher QoQ conversion rates.
Learn more about AI-powered revenue generation in the full 2026 Conversational Commerce Report.
Why brands are making this a strategic priority
84% of brands say the strategic importance of conversational commerce is higher than it was a year ago. 82% agree it will be mainstream in their sector within two years.
That shift is registering at the leadership level because of what conversational commerce does to the buying experience. Creating one-to-one touchpoints earlier in the journey drives higher AOV, shorter buying cycles, and stronger purchase rates. Shoppers who get real-time answers to their questions are more confident.
What this looks like in practice: TUSHY
TUSHY, known for eco-friendly bidets and bathroom essentials, is a useful example of what happens when you take conversational commerce seriously.
Bidets aren't an impulse purchase. Shoppers have real questions about fit, compatibility, and installation. Those questions used to go unanswered until the CX team could respond, often after the customer had abandoned the cart.
TUSHY used Gorgias's AI Agent and shopping assistant capabilities to automate pre-sales support. AI Agent engaged shoppers in real-time conversations, addressed their concerns directly, and built confidence at the moment of highest intent.
This resulted in a 190% increase in chat-based purchases, a 13x return on investment, and twice the purchase rate of human agents.
How to apply this to your strategy
You don't need to overhaul your entire operation to start seeing results. The most effective approach is to start where the impact is clearest and expand from there.
A few places to begin:
- Pre-sales chat. Identify your most common pre-purchase questions (sizing, compatibility, shipping timelines) and ensure your AI can answer them confidently and promptly.
- Product page engagement. Use proactive chat prompts triggered by page behavior to start conversations before shoppers leave.
- Post-purchase follow-up. Let AI pick up the conversation after checkout with order updates and proactive support, reducing inbound volume and building trust.
- Human escalation. Define clearly which situations require a human agent – complex issues, emotional exchanges, high-stakes decisions.
Want to see the full picture of where conversational commerce is headed in 2026? Read the full report to explore the data, trends, and strategies shaping the next era of ecommerce.
{{lead-magnet-1}}
AI Is Table Stakes for Ecommerce: What the Data Tells Us About 2026
TL;DR:
- AI adoption is rapidly accelerating. 96% of ecommerce professionals now use AI in their roles, up from 69% in 2024.
- AI has moved beyond support automation. Use cases have evolved into revenue generation, personalization, and logistics.
- Brands are tying AI success to profit-and-loss outcomes. 60% of brands consider AOV a top indicator of AI effectiveness.
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.
{{lead-magnet-1}}
AI adoption has reached a tipping point
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.
AI use cases now span the full ecommerce stack
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:
- Customer support automation: 96%
- Product recommendations: 88%
- Automated tracking and status updates: 69%
- Personalization: 64%
- Inventory control: 51%
- Dynamic pricing and discounting: 36%
- Order fulfillment: 18%
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.
How AI is changing CX success metrics
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.
AI makes every conversational channel a storefront
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:
- 56% of support tickets automated in 2 months
- Email response times down from 24 hours to 35 seconds
- Double-digit revenue growth without adding headcount.
What this means for your AI strategy
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:
- Start with high-volume, low-complexity tickets. WISMO (where is my order) inquiries, return policy questions, and order status updates are where AI delivers the fastest return. Automate these first.
- Expand into conversational channels. Social messaging and SMS are where AI is driving the most success right now.
- Connect AI performance to revenue metrics. If you're only measuring CSAT and response time, you're missing half the story. Add AOV, conversion rate, and incremental revenue to your reporting.
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.
{{lead-magnet-1}}
The State of Conversational Commerce: 5 Trends Reshaping Ecommerce in 2026
TL;DR:
- AI is resolving tickets, not just replying. AI now handles 31% of customer interactions for ecommerce brands, and that number is expected to nearly double within two years.
- Every channel is becoming a storefront. Conversations are replacing the traditional browse-and-buy journey, with 79% of brands reporting sales from AI-driven interactions.
- AI is shortening the buying cycle. 93% of AI-influenced purchases happen within the first 48 hours of the conversation.
- CX teams are changing, not shrinking. Ecommerce brands are actively hiring for more technical roles to implement, coach, and maintain AI.
- The winning model is hybrid. AI handles volume and speed, while humans handle complexity and judgment.
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.
{{lead-magnet-1}}
Trend 1: AI is table stakes for ecommerce and it’s no longer just about efficiency
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:
- Order tracking and status updates
- Returns, exchanges, and refund requests
- Shipping FAQs and delivery estimates
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.
Trend 2: Conversations are the new path to checkout
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.
Trend 3: AI is accelerating the purchase cycle
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.
Trend 4: AI is making CX teams more technical
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.
Trend 5: The future is hybrid: AI-first, humans when it counts
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.
Where conversational commerce is heading by 2030
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.
Start building your conversational commerce strategy today
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.
{{lead-magnet-1}}
Further reading
Best AI Helpdesk Tools: 10 Platforms Compared
TL;DR:
- The best AI helpdesks offer smart ticketing, self-service, and sales automation. They combine multi-channel support, give teams flexible AI control, and double as an upselling tool that drives revenue.
- Each tool has a unique strength. Gorgias is best for ecommerce brands , Zendesk offers enterprise-level customization, Intercom is great for SaaS engagement, and Tidio is easy for small teams.
- There are also standalone AI tools that integrate with existing helpdesks. Platforms like Ada, Siena, and Yuma offer automation without requiring a full platform switch.
- Advanced AI features vary in price and availability. Some are bundled, while others charge per resolution or limit access to higher tiers.
Every delayed reply, missed ticket, or frustrated customer costs more than just satisfaction—it hits revenue, loyalty, and your brand reputation. That’s why more and more brands are investing in AI helpdesks to automate the tedious parts of their job.
But with so many options on the market, choosing the right AI helpdesk can feel overwhelming. Should you prioritize conversational AI? Multi-channel support? No-code customization? Or pricing that scales with your team?
{{lead-magnet-1}}
We’ve reviewed the 10 best AI helpdesks available in 2025, evaluating them across AI capabilities, ease of use, integrations, analytics, and pricing.
How we evaluated the best AI helpdesks in 2025
To create this list, we evaluated each platform based on a combination of functionality, AI capabilities, usability, and industry applicability.
Our goal was to provide a resource that CX leaders, ecommerce managers, and support teams can rely on when choosing a helpdesk that fits their business needs.
Here’s how we approached the evaluation:
- Feature set assessment: Each tool was reviewed for its core helpdesk features, including ticket management, multi-channel support, workflow automation, and reporting capabilities.
- AI sophistication: Platforms were evaluated on the depth of their AI offerings. This included natural language processing (NLP), predictive analytics, proactive messaging, and automated resolution capabilities.
- Ease of use and setup: We considered setup time, onboarding complexity, and the learning curve for both agents and admins.
- Industry applicability: We examined which industries each tool serves best. Some platforms are tailored for ecommerce, while others are more enterprise or service-focused.
- Pricing transparency and scalability: We noted starting costs, AI feature availability by tier, and potential scaling considerations. Affordability and scalability were important, particularly for fast-growing teams that need to balance cost with AI functionality.
- Supporting resources: We reviewed customer support, integrations, documentation, and community resources. A strong helpdesk not only provides AI features but also ensures teams can implement and optimize them effectively.
By following this methodology, we created a balanced, objective view of each helpdesk, highlighting what makes them unique, their strengths, limitations, and who will benefit most from them.
The best AI helpdesks of 2025
Gorgias
Gorgias is an AI helpdesk designed for ecommerce brands, helping teams streamline support while boosting both efficiency and personalization.
By unifying all customer touchpoints—email, chat, social media, voice, and SMS—into a single dashboard, Gorgias allows support teams to manage interactions without toggling between platforms.
Unlike most helpdesks, its AI capabilities go beyond basic automation. In addition to support, its AI can influence sales by assisting, recommending, and upselling to customers based on their shopping behavior.
Best for: Scaling startups and mature ecommerce enterprises looking to expand support capacity without increasing headcount
Potential limitations: Gorgias is focused primarily on ecommerce brands, which means it may be less suitable for companies that don’t use ecommerce platforms.
Pricing: Starts at $10/month, with advanced AI features available as an add-on.
Main features:
- Automated ticket routing: AI triages incoming customer queries and assigns them to the right agent.
- AI-generated responses: Provides instant, context-aware replies to common questions.
- Sentiment analysis: Flags frustrated customers to prioritize urgent tickets.
- Multi-channel AI support: Integrates across email, chat, Shopify, social media, and 100+ ecommerce apps.
- Macros and workflow automation: AI suggests relevant responses and automates repetitive tasks.
AI features:
- AI Agent: Conversational AI that can update, refund, and replace orders, cancel/skip subscriptions, and even carry out custom-made actions.
- Shopping Assistant: A proactive AI tool that guides, upsells, and recommends products to shoppers through chat. It helps CX teams increase sales and AOV.
- Auto QA: Upgrades service quality by automatically evaluating 100% of private text conversations, whether handled by a human or AI. Each message is scored on metrics like Resolution Completeness, Brand Voice, and Accuracy.
Zendesk
Zendesk is a widely adopted AI helpdesk solution that caters to teams of all sizes, from small businesses to large enterprises. It’s known for its robust ticketing system, extensive integrations, and customizable workflows, making it a versatile choice for teams across industries.
Best for: Non-ecommerce enterprises and businesses like airlines and banks
Potential limitations: Advanced AI features and enterprise-level plans can be expensive for smaller teams, and some users report that customization for niche workflows can be time-consuming.
Pricing: Starts at $25/month per agent, with advanced AI features and enterprise options available on higher tiers.
Main features:
- Unified ticketing: Centralizes requests from email, chat, phone, social media, and messaging apps.
- Macros and workflow automation: Automates routine responses and processes to reduce agent workload.
- Advanced analytics: Offers real-time dashboards and reporting to track support performance and customer satisfaction.
- Multi-channel support: Integrates seamlessly with major ecommerce, CRM, and communication platforms.
AI features:
- Copilot: Assists support agents in providing consistent replies, suggests next steps, and can even perform actions on agents’ behalf.
- AI triage: Automatically categorizes tickets and routes them to the appropriate team member.
- Zendesk QA: Scores the quality of interactions to help you get an overview of support performance.
Intercom
Intercom combines live chat, messaging, and AI automation into a single platform that focuses on proactive customer engagement. Its conversational AI makes it easy for teams to interact with customers in real time, while its automation tools help reduce response times and increase efficiency.
Best for: SaaS companies, software companies, and mid-market teams
Potential limitations: Companies looking for a plug-and-play AI solution will need to invest time in setting up Intercom. Customers report a steep learning curve when creating workflows, organizing users, and implementing new automations.
Pricing: Starts at $39/month per seat. Fin AI is available as a standalone product for $0.99 per resolution (50 resolutions per month minimum) if you have an existing helpdesk.
Main features:
- Live chat and messaging: Provides instant support via website, mobile apps, and email.
- Inbox and workflow management: Centralizes customer conversations and automates repetitive tasks.
- Customer segmentation: Enables targeted messaging based on behavior, subscription plans, or engagement levels.
AI features:
- Fin AI: Intercom’s AI assistant responds to common questions, freeing agents to handle complex issues.
- Fin Tasks: Performs actions like retrieving order details, processing refunds, reorders, and more.
- Fin Insights: Provides a deep look into recurring trends and issues across conversations.
Gladly
Gladly is a customer service platform built around the concept of conversation-centric support, treating every customer interaction as a continuous dialogue rather than isolated tickets.
Best for: Customer-focused brands that prioritize personalized, ongoing conversations over transactional support—especially retail, financial services, and subscription businesses that want to strengthen loyalty.
Potential limitations: Smaller teams may find it more than they need, and advanced customization can require professional services.
Pricing: Available on request, with plans typically tailored to enterprise support teams and scaled based on users and features.
Main features:
- Unified customer timeline: Combines all interactions—email, chat, social, SMS—into a single, chronological view.
- Personalized workflows: Tailors automation and routing to individual customer needs.
- Team collaboration tools: Enables seamless handoffs and internal notes for faster issue resolution.
AI features:
- Gladly Hero: Customer profiles created from conversations that include preferences, relationships, and purchase history.
- Sidekick Chat: Instant answers to requests like returns, account updates, and refunds.
- Sidekick Voice: Real-time, AI-powered phone support with SMS follow-ups.
Kustomer
Kustomer is a CRM-centric AI helpdesk that integrates customer support and relationship management in one platform. Its AI capabilities allow teams to automate repetitive tasks, route tickets intelligently, and gain insights into customer history, making it ideal for businesses with complex support workflows.
Best for: Mid-to-large enterprises that prioritize powerful, custom reporting
Potential limitations: Users report an unintuitive and laggy interface, which can slow down large support teams that handle high support volumes.
Pricing: Starts at $89/month per seat, with AI features available as add-ons.
Main features:
- Unified customer profiles: Consolidates all interactions, purchases, and support history in one view.
- Workflow automation: Streamlines processes with rules-based ticket routing and escalation.
- Advanced reporting: Tracks key support metrics and agent performance.
AI features:
- AI Agents for Reps: Offers real-time assistance, from drafting responses to updating records and summarizing conversations.
- AI Agent for Customers: Allows the creation of multiple AI Agents for specialized tasks.
Tidio
Tidio is an AI-powered live chat and messaging platform built for small to mid-sized businesses looking to combine automation with personalized support. Its ease of setup and affordability make it a strong choice for teams new to AI helpdesks.
Best for: Small to mid-sized ecommerce or service-based businesses looking for an easy-to-use AI chat solution to automate FAQs
Potential limitations: May not scale well for large enterprise businesses.
Pricing: A free plan is available, with paid plans starting at $29/month per agent and AI features as add-ons.
Main features:
- Live chat and messenger integration: Supports website chat, email, and social messaging.
- Drag-and-drop chatbot builder: No coding required to deploy automated responses.
- Ticket management: Organizes queries for quick resolution by agents.
AI features:
- Lyro AI Agent: Conversational AI that answers questions based on support content.
Freshdesk
Freshdesk is a helpdesk platform that combines AI automation, omnichannel support, and workflow management. It’s known for ease of use and affordability, making it popular among SMBs and mid-market companies.
Best for: SMBs and mid-market companies looking for an affordable, easy-to-implement AI helpdesk
Potential limitations: Some advanced AI functionality is limited to higher-tier plans. Large enterprises may require additional configuration to fully leverage AI features.
Pricing: Plans start at $18/month per agent, with AI capabilities and advanced automation available on higher tiers.
Main features:
- Multi-channel ticketing: Consolidates email, chat, phone, and social support.
- Automation and workflows: Rules and macros automate repetitive tasks.
- Analytics and reporting: Provides insights into performance and customer satisfaction.
AI features:
- Freddy AI: Fetches order details, resolves questions, updates customer profiles, and more using approved data.
Standalone AI tools you can integrate with existing helpdesks
Not ready to move helpdesks? These standalone AI tools plug into your existing helpdesk to add automation, self-service, and conversational support.
Ada
Ada is focused on conversational automation, enabling teams to provide self-service solutions that reduce ticket volume while improving response times.
Its no-code interface makes it accessible for non-technical teams, and its AI capabilities allow for personalized customer interactions at scale.
Best for: Large enterprise businesses looking to reduce support tickets through chat-based support
Potential limitations: Basic features that are free on competitor platforms cost extra on Ada, which limits smaller businesses looking for an all-in-one solution.
Pricing: Starts at $499/month for essential AI features. Higher-tier plans are available on request.
Main features:
- No-code chatbot builder: Quickly design and deploy AI chatbots across web, mobile, and messaging apps.
- Ticket deflection: Automates repetitive queries to reduce human agent workload.
- Multi-language support: Offers conversational support in multiple languages to serve global audiences.
AI features:
- Ada Voice: AI-powered phone support that can respond to customers, take action, and escalate issues in real-time.
- Ada Email: Instant, personalized replies for email threads with the ability to hand off to agents.
Siena
Siena is focused on providing automated support for rapidly growing ecommerce and SaaS brands. With an emphasis on efficiency and self-service, Siena helps teams reduce ticket volume and respond faster, while giving managers visibility into performance metrics.
Best for: Mid-market ecommerce and SaaS companies that want to combine automation with insights
Potential limitations: Lacks clear visibility into AI performance, which can keep support teams in the dark about support performance and customer satisfaction.
Pricing: Starts at $500/month with automated tickets at $0.90 each.
Main features:
- Omnichannel support: Handles email, chat, and social media from a single dashboard.
- Custom workflows: Automates repetitive tasks and ticket routing based on rules and customer data.
- Reporting and analytics: Tracks support KPIs and team performance in real time.
AI features:
- Customer Service Agent: Provides contextual, automated responses for common queries.
- Reviews Agent: Responds to every customer review with personalized feedback.
- Siena Memory: Stores key details from customer interactions and turns them into insights reports.
Yuma
Yuma is focused on conversational automation and self-service solutions. It is designed to reduce agent workload while providing fast, personalized responses, making it appealing to growing ecommerce teams.
Best for: Established ecommerce brands looking to integrate sophisticated conversational AI alongside their current helpdesk
Potential limitations: Limited integrations with broader sales stacks mean brands prioritizing sales will have a hard time creating a smooth workflow.
Pricing: Starts at $350/month for 500 resolutions, with higher-tier plans for more resolutions.
Main features:
- Omnichannel support: Handles chat, email, and social messaging from one platform.
- Self-service portals: Allows customers to resolve common issues independently.
- Workflow automation: AI assists with repetitive tasks and ticket routing.
AI features:
- Support AI: Replies to customers on email, WhatsApp, SMS, and social media using your brand’s voice.
- Social AI: Instant responses to social media comments, DMs, and tags.
- Sales AI: Guides shoppers to the relevant product and tracks bestsellers.
What features to look for in a good AI helpdesk
The best AI helpdesk makes support efficient, personalized, and scalable.
Here’s a quick checklist of what to look for when evaluating an AI helpdesk:
- Smart ticket management
- Self-service workflows
- Multi-channel support
- Sales and upselling capabilities
- User-friendly AI controls
- Performance insights
- AI learning and improvement
Key takeaways from our review
The future of customer support is AI-driven, and the tools you choose today will define the efficiency, responsiveness, and satisfaction of your support team tomorrow.
If it's still early in your AI helpdesk journey, we have additional resources to help you learn more from the pros before getting started:
You Don’t Need More Tools: You Need Teams Who Use Them Right
TL;DR:
- Most brands underuse their support tools: Gorgias has powerful features, but many teams don't take full advantage of them.
- Atidiv’s CX experts unlock Gorgias’s full potential: From tagging and macros to dashboards and rules, Atidiv ensures every feature drives value.
- Smart tagging creates strategic insights: Agents tag every interaction to surface product feedback, customer sentiment, and emerging trends in real time.
- Macros and Rules streamline support: Atidiv builds brand-consistent Macros and uses Rules to reduce manual work and clutter.
You don’t need more software—just better usage: Atidiv transforms existing tools like Gorgias into engines for efficiency, growth, and retention.
If you’re like most ecommerce brands, you’ve invested in great tools like Gorgias to streamline support, automate workflows, and deliver personalized experiences at scale. But here’s the hard truth: Having the tools doesn’t mean you’re using them well.
We see it all the time. Gorgias is live, Macros are written, a few Rules are set, and then… chaos. Tags go unused, dashboards lack insight, and your agents are still drowning in tickets.
That’s why leading brands aren’t just buying tech, they’re partnering with teams who know how to use it. That’s where Atidiv comes in.
{{lead-magnet-1}}
The tools are there. Most teams just don’t maximize them.
Gorgias is a powerful platform. Out of the box, it gives you:
- Custom tagging and views
- Automation rules to speed up repetitive tasks
- Macros that standardize your brand voice
- Real-time dashboards and revenue attribution
But without the right people using these tools effectively, it’s just noise. Atidiv’s CX specialists are trained Gorgias power users, and they make sure every feature works hard for your brand.
What happens when CX teams know the tool inside out
Here’s how Atidiv leverages Gorgias to drive real results:
Smart tagging for strategic insights
Atidiv agents don’t just respond to tickets, they tag every interaction with purpose.
- Common product issues? Tagged.
- Pre-sale objections? Tagged.
- VIP customers? You bet—tagged.
This turns your inbox into a live dashboard of customer sentiment, product feedback, and emerging trends, no extra software required.
Macros that actually get used
Atidiv writes and maintains Macros that go beyond “Thanks for reaching out.”
- Dynamic responses tailored to each issue
- Integrated links to help center articles or policies
- Embedded personalization that keeps your brand voice consistent
These aren’t just canned replies—they’re crafted CX responses built to scale.
Enhance your Macros with tags, snooze rules, Shopify actions, and other dynamic variables.
Dashboards that drive decisions
Every Atidiv client gets a customized Gorgias dashboard. It’s built by Atidiv’s Team Leads to track what matters:
- CSAT trends
- SLA performance
- Volume by tag or channel
- Revenue generated from support
No more wondering if your support is working, now you know.
Rules that eliminate repetition
We use Gorgias Rules to route tickets, send auto-replies, and tag intents, reducing ticket clutter by up to 30%.
The result? Agents spend more time on high-impact conversations and less time chasing tracking numbers.
Run your support on autopilot with Gorgias Rules that automatically trigger based on your chosen conditions.
A real-world example: What this looks like in practice
A fast-growing superfood brand came to Atidiv with Gorgias already live, but underutilized. They were answering tickets manually, tracking performance in spreadsheets, and dealing with repeat questions daily.
Within 30 days, Atidiv helped them:
- Build >10 custom macros
- Implement >5 auto-routing and tagging rules
- Clean up and standardize 50+ tags
- Created 15+ executive views
- Launch a real-time performance dashboard
- Reduce first response time by approximately 45%
- Retention analysis using tags
- Surface batch of products with bad taste based on tag trends
And no, they didn’t need to buy any new tools.
It’s not about more tech, it’s about more leverage
Most brands think their next CX win will come from another app or integration. But the real unlock often comes from better use of what they already have.
That’s what Atidiv offers:
- CX teams that are fluent in Gorgias
- Leadership layers that manage performance and QA
- Strategic use of features you’re already paying for
- Flexibility to scale up or down without hiring overhead
The bottom line
You don’t need to overhaul your tech stack. You need a team that can turn Gorgias into a strategic engine for support, growth, and insight.
Atidiv makes it possible, with trained agents, experienced leaders, and a deep understanding of what Gorgias can do when used to its full potential.
→ Want to get more out of the tools you already have? Let’s talk about how Atidiv + Gorgias can transform your support operation.
How CX Leaders are Actually Using AI: 6 Must-Know Lessons
TL;DR:
- Train your AI like a new hire. Give it tone guidelines, review weekly, and keep refining to stay on-brand.
- Adapt AI to real customer behavior. Adjust tone and timing to improve satisfaction, even if the answer stays the same.
- Use AI to drive sales, not just support. Top brands use it to answer product questions and guide pre-purchase decisions.
- Start small and improve as you go. Begin with one common question and test often to build momentum.
If you’ve been side-eyeing AI and wondering if it’s just hype, you’re not alone. A lot of CX leaders were skeptical, too:
“I used to be the loudest skeptic,” said Amber van den Berg, Head of CX at Wildride. “I was worried it would feel cold and robotic, completely disconnected from the warm, personal vibe we’d worked so hard to build.”
But fast forward to today, and teams at Wildride, OLIPOP, bareMinerals, and Love Wellness are using AI to do more than just deflect tickets. They’re…
- Cutting costs without cutting corners
- Driving revenue before a customer even checks out
- Delivering fast, on-brand, human-feeling support at scale
Here are six lessons you can steal from the brands doing it best.
{{lead-magnet-1}}
1. Think of AI as your sidekick
We need to get one point across clearly: AI isn’t about replacing your support team.
For brands with lean CX teams, burnout is a serious problem. And it’s one of the biggest reasons AI adoption is accelerating.
“I was constantly seeing the same frustrating inquiries—sponsorship asks, bachelorette party freebies, PR requests… 45% of our tickets were these kinds of messages,” said Nancy Sayo, Director of Consumer Services at global beauty brand, bareMinerals.
“Once I realized AI could handle them with kindness and consistency without pulling in my team, I was sold.”
Instead of thinking of AI as a replacement, think of it as an enhancement.
It’s about making sure your CX team doesn’t burn out answering the same five questions 50 times a day.
With Gorgias AI Agent, Nancy’s team now uses automation to absorb the high-volume, low-conversion noise, freeing up their seasoned agents to focus on real revenue-driving moments.
“We use AI to handle low-complexity tickets. And we route higher-value customers to our human sales team—people who’ve been doing makeup for over a decade and really know what they’re doing.”
TL;DR? The smartest teams use AI to take the weight of repetitive tickets (“Do you ship internationally?” “Can I get free samples?”) off their shoulders so agents can focus on conversations that build trust, drive loyalty, and increase LTV.
2. Train your AI like a team member
While you can get started with AI quickly for simple queries, we don't recommend using it “out of the box.” And honestly, that’s a good thing.
Brands that “set it and forget it” are missing the point. Because if you want AI to sound exactly like your brand—not like every other chatbot on the internet—you need to give it the same context you’d give a new hire.
Amber van den Berg, Head of Customer Experience at baby carrier brand Wildride, wrote out detailed tone guidelines, including:
- Dos and don’ts for customer conversations
- Approved Dutch-to-English translations
- Example replies for nuanced, emotional questions
- Pre-written macros for product recs and delivery issues
“Lisa, our AI agent, is basically a super well-trained intern who never sleeps. I give her the same updates I give my human team, and I review Lisa’s conversations every week,” said Amber. “If something feels off-brand, too robotic, or just not Wildride enough, I tweak it.”
The feedback never stops, and that’s what makes Lisa so effective.
Related: Meet Auto QA: Quality checks are here to stay
3. Let AI mirror the pacing of real conversations
Even when AI gets it right, customers might not always feel like it did. Especially if the tone of voice is off or if your customer base just isn’t used to automation.
“Our CSAT was low at first,” said Nancy Sayo of bareMinerals. “Even if the response was accurate and beautifully written, our older customers just didn’t want to interact with AI.”
So Nancy’s team adapted. Rather than giving customers a blunt “no” to product requests, they restructured the flow:
“If someone asked for free product, we’d say, ‘We’ll send this to the team and follow up.’ Then, 3-5 days later, the AI would close the loop. It softened the blow and made customers feel heard—even if the answer didn’t change.”
That simple tweak raised CSAT and created a better customer experience without requiring a human to step in.
Inside Gorgias, teams like bareMinerals review AI performance weekly, not just to catch mistakes, but to optimize for tone, satisfaction, and brand feel. They use:
- CSAT reporting to spot dips in sentiment
- Conversation analytics to flag where AI may be losing trust
- Macro editing to quickly adjust common replies
AI gives you the flexibility to test, tweak, and tailor your approach in a way traditional support channels never could.
4. Use AI to drive sales—not just support
Too many CX teams still treat AI like a glorified autoresponder. But the most forward-thinking brands are using it to guide shoppers to checkout.
“Our customers often ask: ‘Which carrier is better for warm weather?’ or ‘Will this fit both me and my taller partner?’” said Amber van den Berg, Head of CX at Wildride. “Lisa doesn’t just answer—she gives context, recommends features, and highlights small touches like the fact that a diaper fits in the side pocket.”
With Gorgias Shopping Assistant, brands can turn AI into a proactive sales assistant—answering product questions in real time, referencing what’s in the customer’s cart, and nudging them toward the best option with empathy.
5. CX insights should power the rest of your business
Great support doesn’t stop at the inbox. At Love Wellness, CX is the connective tissue between ecommerce, product, and marketing.
“We meet quarterly with our CX and ecommerce teams to review top questions, objections, and patterns,” said Mckay Elliot, Director of Amazon at Love Wellness. “That feedback goes straight into product development and PDP optimizations on both DTC and Amazon.”
But it’s not just a quarterly ritual. Feedback sharing is embedded in the culture, and they do this with a Slack channel dedicated to customer feedback.
Dropping in insights is part of the team’s daily and weekly responsibilities. It helps everyone stay close to the content, and it sparks real collaboration on what we can improve. They then use those insights to improve ad messaging and content.
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.
Read more: Why customer service is important (according to a VP of CX)
6. Don’t overthink it, start small
One of the biggest mistakes brands make with AI? Trying to do too much, too soon.
Rolling out AI should feel like a phased launch, not a switch flip. The best results come from starting simple, testing often, and iterating as you go.
“We started with one simple question—‘Do you ship internationally?’—and built from there,” said Amber van den Berg of Wildride.
“And if it doesn’t work? You can always turn it off,” added Anne Dyer, Sr. Manager of CX & Loyalty Marketing at OLIPOP. “The key is to test, review, and keep iterating. AI should enhance your human experience, not replace it.”
If your helpdesk supports it, start in a test environment to preview answers before going live. Then roll out automation gradually by channel, topic, or ticket type and QA every step of the way.
For most brands, the best starting point is high-volume, low-complexity tickets like:
- “Where’s my order?”
- Subscription pauses or cancellations
- Returns and exchanges
- Store policies and FAQs
You don’t need to solve everything on day 1. Just commit to one question, one channel, and one hour per week. That’s where real momentum starts.
Related: Store policies by industry, explained: What to include for every vertical
How do you measure the impact of AI in CX?
Most CX teams are used to tracking classic metrics like ticket volume and CSAT. But when AI enters the mix, your definition of success shifts. It’s not all about how fast you handle tickets anymore—it’s about how customers feel after conversations with AI, team efficiency, and the quality of every interaction.
Here are the metric CX teams used to track without AI—and what they track now with AI:
The best use of AI makes space for human touch
AI isn’t here to replace your CX team. It’s here to free them up, so they can focus on deeper, more meaningful conversations that build loyalty and drive revenue.
So if you’re on the fence, start small. Train it. Review weekly. Build the muscle.
You’ll be surprised how quickly AI becomes your favorite intern.
If you want more tips from the experts featured today, you can:
Why Consolidated Doesn’t Mean Compromised: Top 3 Myths Debunked
TL;DR:
- Consolidation doesn’t mean giving up flexibility. The right all-in-one tools are modular and API-friendly, so teams can customize and integrate freely.
- You gain efficiency, not lose features. One platform means fewer gaps, less manual work, and faster support.
- It’s more affordable and faster than you think. Consolidation cuts hidden costs and delivers ROI quickly.
- Gorgias is built for ecommerce. With a deep Shopify integration and 100+ apps to connect to, it can scale with CX teams, no matter their size.
If your CX team is juggling a dozen different tools just to answer one support ticket, you’re not alone. According to our 2025 Ecommerce Trends report, 42.28% of ecommerce professionals use six or more tools every day. Plus, nearly 40% spend $5,000–$50,000 annually on their tech stack.
That’s a lot of money and a lot of tabs.
It’s no wonder “tech stack fatigue” is setting in. But while many brands are ready to simplify, there’s still hesitation around consolidation. The biggest fear is that all-in-one tools are too rigid or basic to handle the complexity of a growing business.
But the truth is, consolidation doesn’t mean compromise. When done right, it means clarity, speed, and control. It also means fewer tools, smoother workflows, and faster customer support.
Let’s bust some myths and show you what smart consolidation looks like.
{{lead-magnet-1}}
Myth #1: “All-in-one tools are too rigid”
One of the biggest blockers to consolidation is compatibility. Fifty-two percent of ecommerce professionals said they hesitate to consolidate because they’re worried about tools not playing nicely together.
That hesitation makes sense. In the past, “all-in-one” tools meant being locked into a single provider’s ecosystem, with limited integrations and rigid workflows. For CX teams managing fast-moving ops and dozens of tools, from email and returns to reviews and subscriptions, the idea of losing flexibility is a non-starter.
Reality: All-in-one tools are modular, not monolithic
Modern support platforms have moved away from monolithic systems and toward modular API-friendly designs that give brands control instead of constraints.
If you choose the right platform, consolidation doesn’t lead to a loss of functionality. Instead, it means getting a better-connected system that works smarter.
Just ask Audien Hearing who uses Gorgias’s open API to create an integration with its warehouse software to manage returns directly in Gorgias instead of a shared Google spreadsheet.
They also combine the power of Gorgias Voice with an integration to Aircall to resolve thousands of questions a day. This integration enables agents to access customer and order data directly from Gorgias while on a call—staying in one workspace.
“It's amazing that we're able to create any custom solutions we want with Gorgias's open API. Gorgias is way more than a typical helpdesk if you utilize the features it offers,” says Zoe Kahn, VP of Retention and Customer Experience at Audien Hearing.
Read more: The Gorgias & Shopify integration: 8 features your support team will love
Myth #2: “We’ll lose features we rely on”
Another common hesitation around consolidation is the risk of putting all your eggs in one basket. If everything runs through one tool, what happens when something breaks or you need to pivot?
It’s understandable, many teams worry that one tool can’t possibly do everything well. Maybe it won’t support their preferred channels, or the automation will be too limited. Or maybe they’ve been burned by a platform that promised too much and delivered too little.
Reality: All-in-one tools reduce gaps, not capabilities
In reality, consolidating gives CX teams more freedom, not less.
Instead of stitching together half a dozen tools and hoping they sync, teams using a single, well-integrated platform gain:
- A centralized view of the customer
- Cleaner workflows with fewer manual handoffs
- Less time spent training agents on multiple systems
- And fewer gaps in data or context
Under one system, your team doesn’t have to jump between tabs anymore. They can just focus on helping customers, quickly and consistently.
Take it from Osea Malibu, a seaweed‑infused skincare brand that transformed their support quality assurance process using Gorgias Auto QA. Their manual QA system was time-consuming and couldn’t scale as ticket volume surged. But the switch made impressive improvements:
- QA time reduced by 75%, from over an hour per week to just 15 minutes
- 100% of tickets now automatically quality‑checked, instead of a small manual sample
- CSAT increased (during BFCM) to 4.74/5, reflecting better consistency and faster resolutions
“Gorgias Auto QA saved me so much time. What used to take over an hour now only takes 15 minutes a week, and I no longer have to worry about spreadsheets.” —Sare Sahagun, Customer Care Manager at Osea Malibu
Myth #3: “Consolidation is expensive and time-consuming”
On paper, consolidation sounds smart. But 47.6% of ecommerce professionals say cost is a barrier, and 40.3% worry about the time it takes to implement a new system.
Sticking with a fragmented stack isn’t exactly cheap or quick, either. Between training new agents, managing multiple vendors, and patching together tools that don’t fully sync, the hidden costs add up fast.
Reality: Consolidation reduces overhead and busywork
It’s not actually consolidation that drains your resources—it’s complexity. And with Gorgias, simplifying pays off fast.
Trove Brands is a standout example. After centralizing their support with Gorgias, they implemented AI-powered order cancellation workflows and saw:
- 45% of tickets automated, cutting manual workload
- 70% reduction in failed order cancellations, saving costs and frustration
- 99.93% faster first response time during BFCM 2024 (from 11 hours 30 minutes to just 30 seconds)
Related: The hidden cost of not adopting AI in ecommerce
What’s the top benefit of consolidating your tech stack?
The biggest benefit of fewer tools is efficiency. It’s also a direct line to real business impact.
Constant tab-switching and duplicate data entry mean way too much time spent managing platforms instead of helping customers.
When you consolidate your tech stack, your team spends less time learning new systems, chasing down info, or waiting for one tool to sync with another.
Instead, they get everything they need in one place, faster replies, smoother workflows, and happier customers.
And that all adds up to better CSAT, lower churn, and a support team that’s finally free to focus on what matters.
What makes Gorgias different from other all-in-one platforms?
Gorgias is built specifically for ecommerce brands, with features that reflect the way CX teams actually work.
As Shopify’s only Premier Partner for customer support, we offer a native integration that pulls in key order data and context automatically, so agents have everything they need without switching platforms. That means conversations, AI, automation, revenue data, and reporting are in one place.
Our open app ecosystem allows you to connect to 100+ tools like Shopify, Klaviyo, Yotpo, and Recharge in just a few clicks. Need more customization? Our add-ons, like AI Agent and Voice let you level up at your own pace.
Whether you're handling hundreds of tickets a week or scaling globally, Gorgias adapts—so you don’t have to keep reinventing your support stack every six months.
Time to rethink your stack
Dr. Bronner’s, a globally recognized organic soap and personal care brand, made the switch from Salesforce to Gorgias to keep up with growing support demands, and it paid off fast.
Here are the results they saw with Gorgias:
- $100,000 saved in the first year by cutting licensing and developer costs
- 45% of all customer queries automated after just 2 months
- 74% reduction in ticket resolution time, powering faster support
- 11% increase in CSAT, thanks to quicker, more personalized responses
“We don’t get boxed out because we only work with Gorgias tools. Gorgias deeply understands the needs of CX, Shopify, and orders and how those tools work together so that it’s really easy for us to work across the board throughout those tools and that didn’t exist in our last setup at all,” says Emily McEnany, Senior CX Manager at Dr. Bronner’s.
If you’re still stitching together half a dozen tools to handle support, it might be time to ask: Is your tech stack helping you or holding you back?
With Gorgias, you get centralization and flexibility, so your team can move faster, serve better, and scale smarter.
Book a demo or dive into the full 2025 Ecommerce Trends report to see how other brands are rethinking their stacks.
{{lead-magnet-2}}
You’re Missing Out on Sales Without an AI Shopping Assistant—Here’s Why
TL;DR:
- Shoppers won’t wait for help—so they leave. Without instant answers, you’re losing sales to hesitation and unanswered questions.
- AI shopping assistants step in right away. They guide, recommend, and resolve concerns in real time, 24/7.
- They boost conversions and AOV. Brands like Pepper and TUSHY saw up to 62% more conversions after adding one.
- They go beyond chatbots. AI assistants proactively sell, using browsing behavior to tailor messages and close more carts.
- Gorgias Shopping Assistant is built for Shopify brands. It starts conversations, mirrors your brand voice, uses browsing data, suggests products, and sends dynamic discounts.
Shoppers aren’t always going to reach out and ask the questions they have, especially if they’re going to have to wait for a response from a CX team.
That means you’re losing sales to friction, indecision, or information gaps.
In 2025, the average cart abandonment rate is 70.19%. But if you can find an AI tool that doubles as a support and sales agent, it could make all the difference.
Gorgias’s Shopping Assistant, for example, has brought a 62% uplift in conversion rate for brands that implement it.
Ahead, learn where you can leverage an AI shopping assistant to increase conversions and craft better purchase experiences.
{{lead-magnet-1}}
What is an AI shopping assistant?
An AI shopping assistant is a chat tool powered by AI to provide pre-sales support for shoppers. It can answer questions, make product recommendations, and help guide shoppers in the right direction if they’re stuck.
Gorgias's Shopping Assistant is a powerful, hyper-personalized AI tool built for Shopify brands. Unlike other AI tools, Shopping Assistant starts conversations with customers, not the other way around. It’s uniquely tailored for each customer by tracking browsing behavior during each session and remembering what shoppers say, keeping conversations natural and recommendations relevant.
It’ll also chat with shoppers in your own brand voice, as its responses are pulled right from the knowledge you feed it.
At which point do brands lose sales in the customer journey?
The stages of the customer journey where common drop-off points occur for brands that lack proactive support include:
- Discovery (casual browsing)
- Interested (considering making a purchase)
- Ready to buy (strong purchase intent)
1) Discovery (casual browsing)
There’s a big chance that shoppers—especially first-timers—have questions, but aren’t willing to wait for a human to get back to them. And when your CX team is off the clock? Customers will likely leave altogether.
An AI shopping assistant can help you engage customers right away, even outside your business hours.
Bra brand Pepper uses Gorgias Shopping Assistant to help shoppers find their perfect size. When it detects hesitation, Shopping Assistant points customers to the sizing guide.
This proactive approach creates an easy path for conversation and sets the precedent that any questions will be answered immediately, providing a better––and less confusing––experience.
“With Shopping Assistant, we’re not just putting information in our customers’ hands; we’re putting bras in their hands,” says Gabrielle McWhirter, CX Operations Lead at Pepper.
Impact these metrics 📈
For shoppers in the Discovery stage, using a Shopping Assistant boosts clicks and time on site and reduces bounce rate. It does this by surfacing specific questions on relevant product pages. Pepper boosted their conversion rate by 19% with Gorgias Shopping Assistant.
Read more: How Pepper’s AI Agent automates 54% of support and converts 19% of conversations
2) Interested (considering making a purchase)
In a retail environment, a salesperson can give shoppers recommendations by asking a few questions, especially if they’re unsure of what to buy.
AI shopping assistants have the ability to mirror those in-person shopping experiences by interacting with customers in real-time to help them find their perfect match.
Shoppers can give as much (e.g., “Help! What dress is suitable for a wedding reception?”) or as little information as they’d like, and the AI shopping assistant will do the rest.
It’s possible even for questions that are slightly vague, like a customer who types in “how to make up” without any other context:
For example, jewelry shop Caitlyn Minimalist uses Shopping Assistant to recommend products, engaging interested customers and bringing them closer to a purchase.
“As a result of Shopping Assistant, we've seen a measurable lift in AOV through more meaningful customer interactions,” says Anthony Ponce, Head of Customer Experience at Caitlyn Minimalist.
“Our clients are provided the right information at the right time, creating a seamless experience that builds trust and drives confident purchases."
Impact these metrics 📈
According to data from Gorgias, email is the highest volume support channel, with ~25% of that tied to pre-sales. AI shopping assistants tackle these pre-sales asks and also upsell by recommending complementary products. This can lead to a boost in average order value (AOV) and conversion rate.
Read more: How Caitlyn Minimalist uses Shopping Assistant to turn single purchases into jewelry collections
3) Ready to buy (strong purchase intent)
The main reasons customers abandoned a cart in 2025 include:
- Extra costs (like shipping, fees, taxes) - 39%
- Delivery times were too slow - 21%
- Checkout was too complicated or long - 18%
- Didn’t like return policy - 15%
An AI shopping assistant can mitigate or resolve these issues. They resolve crucial questions—like delivery time or return policies—that need in-the-moment answers. By alleviating pre-sale concerns, they give customers the confidence to make a purchase.
For example, bidet brand TUSHY leverages Shopping Assistant to answer questions about toilet compatibility that might flush a pending sale.
Aside from quelling customer concerns, Shopping Assistant can also send discount codes to close deals. Unlike general discount codes you find across the internet, these discounts are uniquely generated for each customer, keeping them engaged and on your site.
Impact these metrics 📈
AI shopping assistants can reduce cart abandonment rate and increase conversion rate. Gorgias Shopping Assistant adjusts to your sales strategy by sending customers discount codes that can be the final nudge to checkout.
Why traditional chatbots don’t cut it anymore
Most AI tools are built just for support. They deflect tickets and answer FAQs, but they’re not built to sell.
Shopping Assistant proves that support teams can also drive revenue by upselling, suggesting exchanges, and giving shoppers the confidence to try a brand for the first time (or to give it another shot).
Gorgias’s AI Shopping Assistant uses context-based decision making and looks for specific behavioral signals:
- Products viewed - Which product pages have they visited?
- Pages views - What pages have they explored, like FAQs, reviews or categories?
- Current page - Which page are they currently browsing?
- Purchase history – What have they bought from this brand before?
- Cart data - What items are currently in their cart?
Improve conversions with Gorgias Shopping Assistant
Ultimately, the cost of not adopting AI can be higher than the investment of implementing it. 77.2% of ecommerce professionals use AI to improve their work. Why not extend those benefits to your customers?
AI Shopping Assistants help you create better customer experiences overall. These tools help reduce customer effort, increase average order value, save would-be-lost sales, and create more customer touchpoints.
Hire the always-on Shopping Assistant that never misses a sale.
{{lead-magnet-2}}
Guide More Shoppers to Checkout with Conversation-Led AI
TL;DR:
- Shopping Assistant is your new AI sales closer. It jumps in when shoppers hesitate, delivering real-time, personalized support that drives conversions.
- It boosts revenue by acting like your best salesperson. It knows when to recommend, upsell, or offer a discount, without being pushy.
- It remembers what shoppers do mid-session. That means smarter conversations, better suggestions, and bigger order values.
- It’s already delivering results. Brands using Shopping Assistant are seeing 62% more conversions, 10% higher AOV, and 5x ROI.
- You control the strategy. Customize how it promotes discounts, when it steps in, and how it speaks.
What’s the common factor between shoppers debating between products and considering a splurge? Hesitation.
Today’s shoppers are overwhelmed with choices. They don’t want to be left to figure things out on their own. They want guidance.
But most brands are missing that crucial piece of the puzzle. They lack a strategy that accompanies shoppers on their journey. A tool that encourages shoppers to proceed to checkout. And, ultimately, a customer experience devoid of a sales approach.
That’s why we built Shopping Assistant, an AI Agent that proactively engages browsers, offers context-aware product recommendations, and turns hesitation into conversions in real time.
And it’s working. Brands using Shopping Assistant are seeing a 62% uplift in conversion, 10% higher average order value, and 5x ROI.
Here’s a closer look at what’s behind the magic.
{{lead-magnet-1}}
AI-powered shopping, built for sales
Most traditional chatbots passively wait for questions and deliver answers that aren’t personalized to each shopper's preferences.
Unlike these bots, Shopping Assistant reads real-time signals like pages viewed, cart contents, and conversation tone. This results in a solution that not only offers support but also offers personalized, proactive selling. This enables Shopping Assistant to continuously refine and adjust its playbook, evolving with each shopper as their journey matures.
Here’s how Shopping Assistant engages with customers across the shopping journey:
- Discovery: Gathers preferences and educates.
- Interested: Makes targeted product suggestions.
- Ready to Buy: Assists with checkout, nudges purchases with discounts.
Take this example below. When a customer vaguely asks “how to make up,” Shopping Assistant interprets it as a sign of interest in makeup products and recommends a starter kit.
Personalization that understands you
Where traditional bots reset with every message, Shopping Assistant does the opposite. It has built-in context-aware intelligence that remembers what shoppers have clicked, viewed, and added to their cart during a session.
This enables natural, relevant, and persuasive conversations that truly resonate with each shopper. It goes beyond reading messages and observes behavior to adapt its responses.
That means it knows if someone has:
- Viewed three red lipsticks but didn’t add to cart
- Repeatedly checked sizing info for the same dress
- Added two serums to their cart after browsing dry skin FAQs
With plenty of context to work with, Shopping Assistant is not only smarter but also more profitable than the average chatbot. It drives more conversions with product recommendations and lifts average order value with timely upsells based on what’s been added to the cart or viewed.
Here’s what it looks like in action: When a customer engages through a product page, Shopping Assistant recommends a matching outfit, suggesting it’s aware of alternate product variants and the customer's likely interest in that style.
Dynamic discounts that convert without undercutting
Promotions are powerful, but they’re not one-size-fits-all.
With Shopping Assistant, merchants can define their discount strategy to align with their brand. These strategies can range from offering no deals to using aggressive promotions.
Once the strategy is set, Shopping Assistant waits for hesitation and customer intent to trigger a discount, firing it at the most conversion-worthy moment.
Proactive engagement in 3 ways
Shopping Assistant initiates conversations. It’s built to engage shoppers, spotting when they linger or show signs of confusion, stepping in with timely, personalized help.
Every second counts in ecommerce. If a shopper pauses on a product page or is left scrolling through an endless search results page, Shopping Assistant detects it in real-time and reaches out with a relevant prompt like:
- “Need help picking the right shade?”
- “Want to know our return policy before you buy?”
Here’s how Shopping Assistant reduces drop-off, builds confidence, and drives faster decision-making in three different ways.
1. Suggested product questions
Shopping Assistant automatically triggers commonly asked questions depending on the product currently being viewed. In one click, shoppers can get the answer to the question they’re curious about. This combats hesitation caused by a lack of information, resulting in more confident conversions.
2. Ask Anything Input
When shoppers land on the homepage, it’s easy to become overwhelmed and not know where to navigate. The Ask Anything Input provides an easy way to start a conversation with Shopping Assistant and get the guidance they need.
Shopping Assistant can refine its response to the customer based on the page context. For example, when the customer is on a product page, Shopping Assistant knows exactly what product is being asked about.
3. Trigger on Search
Shopping Assistant can step in to offer pinpointed help based on a shopper’s search query. Instead of scrolling through a results page, Shopping Assistant triggers a message based on what the shopper entered, offering an easier and faster way to find what they need.
Smart recommendations and relevant upsells
Shopping Assistant’s suggestions are rooted in real context: what the shopper has viewed, added to cart, or asked about. Whether they’re exploring a specific product line or revisiting a category they’ve shown interest in, Shopping Assistant delivers relevant upsells and complementary items that make sense for the customer.
This personalized approach to upselling increases cart size without feeling forced—it’s smart, seamless, and sales-driven.
Shopping Assistant can even turn vague product questions into upsell opportunities. By asking questions, it learns more about an individual to come up with recommendations that best fit their preferences.
Try Shopping Assistant today
Shopping Assistant is transforming the way shoppers engage and helping ecommerce brands sell more effectively. Through smarter conversations and real-time personalization, it turns every interaction into an opportunity to convert, build trust, and drive revenue.
{{lead-magnet-2}}
Coach AI Agent in One Hour a Week: SuitShop’s Guide
TL;DR:
- Don't just turn it on, coach it. Treating your AI Agent like a team member, not a plug-and-play tool, is what makes it truly helpful and memorable.
- One owner and one hour a week is enough to make a big impact. SuitShop’s Katy Eriks runs QA and training solo, using a repeatable system to log feedback and improve performance weekly.
- Don't forget to pause and evaluate. SuitShop temporarily turned off AI to improve their help content, making automation far more effective when it came back online.
- Let your best human agents guide your AI. Katie studied her top-performing teammate's tickets to teach AI the best responses and macros.
- Brand voice matters as much as accuracy. SuitShop's AI Agent "Max" is trained to sound warm, helpful, and on-brand. Customers even thank it by name.
The most coachable team member on your support team might not be human.
Brands that want to keep up with rising customer expectations are turning to AI to help meet demand. But as SuitShop’s Director of Customer Experience, Katie Eriks, will tell you, great results don’t come from flipping a switch.
They come from coaching.
Since implementing Gorgias AI Agent, SuitShop has reached a 30% automation rate, all while maintaining a lean CX team and giving every customer the tailored experience they expect (literally and figuratively).
“I consider myself its boss,” said Katie, who runs the entire coaching process solo. With under an hour of weekly maintenance now, SuitShop’s AI Agent runs efficiently, accurately, and on-brand.
Katie spoke at Gorgias Connect 2025 to share exactly how she got there. You can watch her full session below:
The case for coaching your AI Agent
When brands think about automation, they often imagine flipping a switch and watching repetitive tasks vanish. But in practice, it’s not that simple, at least not if you care about customer experience.
Gorgias encourages brands to treat their AI Agent like a junior teammate — someone you onboard, train, observe, and coach over time.
Brands that do this well are already seeing massive gains:
- 60%+ of customer conversations fully automated
- First response times under 30 seconds
- Consistent CSAT scores of 4.5 and above
- Major cost savings during high-volume seasons
For SuitShop, automation was about creating space for their small team to focus on specialized service. Space to scale without scaling headcount. And space to do it all without losing their voice.
Step-by-step: SuitShop’s AI coaching workflow
Katie and her team had been longtime Gorgias users, but when they turned on AI Agent in August 2023, the results were unremarkable. The responses weren’t inaccurate, but they weren’t helpful enough either.
What Katie learned was to “Be hands-on early. Use downtime to train. And never stop refining.”
So she got to work, not by replacing the tool, but by going deeper into it. Here are her coaching tips:
One owner, one hour a week
Katie made herself the sole point of contact for training and QA. That might sound like a lot, but over time, it became a light lift.
“At this point, it’s definitely less than one hour per week,” she said. “In the beginning, it was more time-consuming because I needed to create help center articles and Guidance regularly. Now I’ve got it down to a pretty quick thumbs-up, thumbs-down kind of process.”
Katie uses Monday mornings to review AI Agent tickets from over the weekend, when fewer human agents are available and AI takes the lead.
Read more: Why your strategy needs customer service quality assurance
Pause and perfect before scaling
Unlike many retail brands, SuitShop’s busiest time isn’t the holiday rush — it’s wedding season in the summer and fall. So when things quieted down in December, Katie used that time strategically.
She temporarily turned off the AI Agent to regroup.
“I decided to turn it off and really beef up our Help Center,” she explained. “I went back to the tickets I had to answer myself, checked what people were searching in the Help Center, and filled in the gaps.”
She built out content with a mix of blog knowledge, internal macros, and ChatGPT. Once she felt confident the content base was solid, she turned AI back on.
Read more: How to optimize your Help Center for AI Agent
Use data to guide your coaching plan
Once SuitShop’s foundational content was in place, Katie didn’t just sit back and hope for the best. Instead, she built a repeatable feedback loop grounded in data — one that helped her spot opportunities for improvement before they became issues.
Rather than combing through tickets at random, Katie created custom views inside Gorgias to zero in on the most impactful coaching moments:
- Low CSAT tickets: Any conversation that ended with a customer satisfaction score below expectations got flagged. These were clear indicators that something about the tone, accuracy, or clarity of the AI response had fallen short.
- High handover rates: Katie looked at the tickets AI Agent was regularly handing off to humans. Many of these were actually answerable. The handover just meant that guidance was missing, miscategorized, or too vague.
- Agent-tagged tickets: To make this scalable, Katie empowered her team to flag any strange or impressive responses from the AI. By using a tag like AI_agent_feedback, team members could drop tickets into a coaching queue without needing to write a full explanation.
To keep all of this actionable, Katie logs insights in a shared spreadsheet that functions as a live to-do list. Every row includes:
- A link to the ticket
- A summary of the issue
- The resolution (e.g., new Guidance or macro needed)
- A status tracker (not started / in progress / completed)
- A link to the resource she created in response
These insights are also available in Gorgias’s dashboard, where you can identify the top issues customers had.
“Sometimes I do it all in the moment. Other times I’ll log it and come back later when I can take the time to do it right.”
By combining frontline feedback with structured ticket views, Katie turned scattered QA into a consistent coaching system — one that ensures SuitShop’s AI Agent keeps getting smarter every week.
Learn from your human agents
One of Katie’s most effective strategies comes from her own team.
Like many CX leads, she noticed that some agents consistently resolved tickets in a single touch. That pattern, Katie realized, wasn’t just a win for customers, it was a roadmap for an AI-driven support strategy.
Her teammate Tacy quickly became her go-to signal for what the AI Agent needed to learn next.
“I pull her tickets often to see what she’s responded with. It helps AI learn from her directly.”
By reviewing Tacy’s ticket history, Katie identified standard replies that didn’t yet exist as macros or Guidance. If Tacy was writing the same sentence repeatedly or copy-pasting a reply manually, that meant it could (and should) be taught to the AI Agent.
She also tracked Tacy’s macro usage rate. If Tacy frequently used a macro for a certain issue, but other agents weren’t, it flagged an opportunity to standardize responses across the team and the AI.
The key insight? If it only takes one touch for a human to answer, the AI can be trained to do it too.
These small efficiency wins added up quickly, especially during peak season, when the ability to automate just a few extra conversations per day created meaningful breathing room for the rest of the team.
Related: How to automate half of your CX tasks
Make your AI sound human (and on-brand)
Automation without brand voice feels robotic. Katie made sure SuitShop’s AI Agent sounded like a natural extension of the team, and that started with a name: Max.
“We get replies like, ‘Thanks Max!’ from customers who think it’s a real person.”
Using AI Agent’s tone of voice settings, Katie went deep on personalization. She customized everything from sentence structure and greeting format to whether or not emojis and exclamation marks should be used (they shouldn’t, in SuitShop’s case).
Her AI Agent instructions include clear direction on:
- Tone: Warm, empathetic, clear, especially with high-stress wedding-related issues
- Structure: Shorter responses for chat, slightly more detailed for email
- Dos and Don’ts: Specific words or phrases to use or avoid, pulled from real team responses
- First/last name use: Always first name only, to keep things friendly but respectful
Katie also made sure she instructed AI Agent to acknowledge customer emotions — especially frustration — and to offer reassurance when things went wrong.
And because AI responses are written at lightning speed, she regularly reviewed messages to ensure they didn’t come off as cold or abrupt, especially in sensitive situations like delayed wedding orders or size issues close to the event date.
Live coaching: What it looks like in practice
In the workshop, Katie walked through two real support tickets where AI missed the mark and how she used those moments to improve.
In one case, a customer asked a common question: “The navy suit I’m looking at says ‘unfinished pant hem.’ Will the pants need to be hemmed?”
Despite having help articles and macros explaining this exact issue, AI Agent responded: “I don’t have the information to answer your question.”
That was a red flag.
Katie immediately stepped in to coach the agent by:
- Applying the correct existing resources
- Writing an ideal sample reply as an internal note
- Checking tone, empathy, and phrasing
- Testing the fix by pasting the same question into the test environment
“I like to write a short internal note, so if I see that ticket again, I know exactly how I coached it.”
In another case, AI Agent was incorrectly handing off a sizing question about jacket sleeve length. Katie realized that a previous broad handover topic ("sizing and fit questions") was causing confusion by flagging issues that the AI should have been able to handle.
So she deleted the handover topic and replaced it with a clear guidance article — complete with example questions, macros, and links to sizing resources.
“Once I added specific questions in quotes, it made a huge difference.”
What's next: AI tools that help you scale faster
SuitShop didn’t automate 100% of CX — but that’s not the point. At 30% automation (and growing), Katie gives her team more time to specialize, connect, and handle urgent or emotional conversations with care.
Here’s what Gorgias offers to help as well:
- Optimized intent dashboards: These show the most common topics customers ask about, the AI’s performance on those topics, and how much opportunity there is to increase automation.
- Auto-generated knowledge: Based on your macros, Help Center, and even Shopify data, Gorgias can now draft suggested guidance for your review, making it faster to train your AI Agent without starting from scratch.
- Auto QA: This tool scores every AI (and human) response based on resolution, accuracy, communication, and tone. It gives you full visibility across your team and automations, without needing to review each ticket manually.
Whether you’re just getting started or trying to move beyond basic automation, Katie’s approach proves that coached AI outperforms out-of-the-box tools every time.
Want to coach your AI Agent like SuitShop? Book a demo to see how Gorgias can help you scale smarter.
{{lead-magnet-1}}
Building delightful customer interactions starts in your inbox
