

TL;DR:
In 2024, Shopify merchants drove $11.5 billion in sales over Black Friday Cyber Monday. Now, BFCM is quickly approaching, with some brands and major retailers already hosting sales.
If you’re feeling late to prepare for the season or want to maximize the number of sales you’ll make, we’ll cover how food and beverage CX teams can serve up better self-serve resources for this year’s BFCM.
Learn how to answer and deflect customers’ top questions before they’re escalated to your support team.
💡 Your guide to everything peak season → The Gorgias BFCM Hub
During busy seasons like BFCM and beyond, staying on top of routine customer asks can be an extreme challenge.
“Every founder thinks BFCM is the highest peak feeling of nervousness,” says Ron Shah, CEO and Co-founder of supplement brand Obvi.
“It’s a tough week. So anything that makes our team’s life easier instantly means we can focus more on things that need the time,” he continues.
Anticipating contact reasons and preparing methods (like automated responses, macros, and enabling an AI Agent) is something that can help. Below, find the top contact reasons for food and beverage companies in 2025.
According to Gorgias proprietary data, the top reason customers reach out to brands in the food and beverage industry is to cancel a subscription (13%) followed by order status questions (9.1%).
Contact Reason |
% of Tickets |
|---|---|
🍽️ Subscription cancellation |
13% |
🚚 Order status (WISMO) |
9.1% |
❌ Order cancellation |
6.5% |
🥫 Product details |
5.7% |
🧃 Product availability |
4.1% |
⭐ Positive feedback |
3.9% |
Because product detail queries represent 5.7% of contact reasons for the food and beverage industry, the more information you provide on your product pages, the better.
Include things like calorie content, nutritional information, and all ingredients.
For example, ready-to-heat meal company The Dinner Ladies includes a dropdown menu on each product page for further reading. Categories include serving instructions, a full ingredient list, allergens, nutritional information, and even a handy “size guide” that shows how many people the meal serves.

FAQ pages make up the information hub of your website. They exist to provide customers with a way to get their questions answered without reaching out to you.
This includes information like how food should be stored, how long its shelf life is, delivery range, and serving instructions. FAQs can even direct customers toward finding out where their order is and what its status is.

In the context of BFCM, FAQs are all about deflecting repetitive questions away from your team and assisting shoppers in finding what they need faster.
That’s the strategy for German supplement brand mybacs.
“Our focus is to improve automations to make it easier for customers to self-handle their requests. This goes hand in hand with making our FAQs more comprehensive to give customers all the information they need,” says Alexander Grassmann, its Co-Founder & COO.
As you contemplate what to add to your FAQ page, remember that more information is usually better. That’s the approach Everyday Dose takes, answering even hyper-specific questions like, “Will it break my fast?” or “Do I have to use milk?”

While the FAQs you choose to add will be specific to your products, peruse the top-notch food and bev FAQ pages below.
Time for some FAQ inspo:
AI Agents and AI-powered Shopping Assistants are easy to set up and are extremely effective in handling customer interactions––especially during BFCM.
“I told our team we were going to onboard Gorgias AI Agent for BFCM, so a good portion of tickets would be handled automatically,” says Ron Shah, CEO and Co-founder at Obvi. “There was a huge sigh of relief knowing that customers were going to be taken care of.”
And, they’re getting smarter. AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT score.

Here are the specific responses and use cases we recommend automating:
Get your checklist here: How to prep for peak season: BFCM automation checklist
With high price reductions often comes faster-than-usual sell out times. By offering transparency around item quantities, you can avoid frustrated or upset customers.
For example, you could show how many items are left under a certain threshold (e.g. “Only 10 items left”), or, like Rebel Cheese does, mention whether items have sold out in the past.

You could also set up presales, give people the option to add themselves to a waitlist, and provide early access to VIP shoppers.
Give shoppers a heads up whether they’ll be able to cancel an order once placed, and what your refund policies are.
For example, cookware brand Misen follows its order confirmation email with a “change or cancel within one hour” email that provides a handy link to do so.

Your refund policies and order cancellations should live within an FAQ and in the footer of your website.
Include how-to information on your website within your FAQs, on your blog, or as a standalone webpage. That might be sharing how to use a product, how to cook with it, or how to prepare it. This can prevent customers from asking questions like, “how do you use this?” or “how do I cook this?” or “what can I use this with?” etc.
For example, Purity Coffee created a full brewing guide with illustrations:

Similarly, for its unique preseasoned carbon steel pan, Misen lists out care instructions:

And for those who want to understand the level of prep and cooking time involved, The Dinner Ladies feature cooking instructions on each product page.

Interactive quizzes, buying guides, and gift guides can help ensure shoppers choose the right items for them––without contacting you first.
For example, Trade Coffee Co created a quiz to help first timers find their perfect coffee match:

The more information you can share with customers upfront, the better. That will leave your team time to tackle the heady stuff.
If you’re looking for an AI-assist this season, check out Gorgias’s suite of products like AI Agent and Shopping Assistant.
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When Rhoback introduced an AI Agent to its customer experience team, it did more than automate routine tickets. Implementation revealed an opportunity to improve documentation, collaborate cross-functionally, and establish a clear brand tone of voice.
Samantha Gagliardi, Associate Director of Customer Experience at Rhoback, explains the entire process in the first episode of our AI in CX webinar series.
With any new tool, the pre-implementation phase can take some time. Creating proper documentation, training internal teams, and integrating with your tech stack are all important steps that happen before you go live.
But sometimes it’s okay just to launch a tool and optimize as you go.
Rhoback launched its AI agent two weeks before BFCM to automate routine tickets during the busy season.
Why it worked:
Before turning on Rhoback’s AI Agent, Samantha’s team reviewed every FAQ, policy, and help article that human agents are trained on. This helped establish clear CX expectations that they could program into an AI Agent.
Samantha also reviewed the most frequently asked questions and the ideal responses to each. Which ones needed an empathetic human touch and which ones required fast, accurate information?
“AI tells you immediately when your data isn’t clean. If a product detail page says one thing and the help center says another, it shows up right away.”
Rhoback’s pre-implementation audit checklist:
Read more: How to Optimize Your Help Center for AI Agent
It’s often said that you should train your AI Agent like a brand-new employee.
Samantha took it one step further and recommended treating AI like a toddler, with clear, patient, repetitive instructions.
“The AI does not have a sense of good and bad. It’s going to say whatever you train it, so you need to break it down like you’re talking to a three-year-old that doesn’t know any different. Your directions should be so detailed that there is no room for error.”
Practical tips:
Read more: How to Write Guidance with the “When, If, Then” Framework
For Rhoback, an on-brand Tone of Voice was a non-negotiable. Samantha built a character study that shaped Rhoback’s AI Agent’s custom brand voice.
“I built out the character of Rhoback, how it talks, what age it feels like, what its personality is. If it does not sound like us, it is not worth implementing.”
Key questions to shape your AI Agent’s tone of voice:
Once Samantha started testing the AI Agent, it quickly revealed misalignment between Rhoback’s teams. With such an extensive product catalog, AI showed that product details did not always match the Help Center or CX documentation.
This made a case for stronger collaboration amongst the CX, Product, and Ecommerce teams to work towards their shared goal of prioritizing the customer.
“It opened up conversations we were not having before. We all want the customer to be happy, from the moment they click on an ad to the moment they purchase to the moment they receive their order. AI Agent allowed us to see the areas we need to improve upon.”
Tips to improve internal alignment:
Despite the benefits of AI for CX, there’s still trepidation. Agents are concerned that AI would replace them, while customers worry they won’t be able to reach a human. Both are valid concerns, but clearly communicating internally and externally can mitigate skepticism.
At Rhoback, Samantha built internal trust by looping in key stakeholders throughout the testing process. “I showed my team that it is not replacing them. It’s meant to be a support that helps them be even more successful with what they’re already doing," Samantha explains.
On the customer side, Samantha trained their AI Agent to tell customers in the first message that it is an AI customer service assistant that will try to help them or pass them along to a human if it can’t.
How Rhoback built AI confidence:
Read more: How CX Leaders are Actually Using AI: 6 Must-Know Lessons
Here is Rhoback’s approach distilled into a simple framework you can apply.
Watch the full conversation with Samantha to learn how AI can act as a catalyst for better internal alignment.
📌 Join us for episode 2 of AI in CX: Building a Conversational Commerce Strategy that Converts with Cornbread Hemp on December 16.
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TL;DR:
As holiday season support volumes spike and teams lean on AI to keep up, one frustration keeps surfacing, our Help Center has the answers—so why can’t AI find them?
The truth is, AI can’t help customers if it can’t understand your Help Center. Most large language models (LLMs), including Gorgias AI Agent, don’t ignore your existing docs, they just struggle to find clear, structured answers inside them.
The good news is you don’t need to rebuild your Help Center or overhaul your content. You simply need to format it in a way that’s easy for both people and AI to read.
We’ll break down how AI Agent reads your Help Center, finds answers, and why small formatting changes can help it respond faster and more accurately, so your team spends less time on escalations.
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Before you start rewriting your Help Center, it helps to understand how AI Agent actually reads and uses it.
Think of it like a three-step process that mirrors how a trained support rep thinks through a ticket.
Your Help Center is AI Agent’s brain. AI Agent uses your Help Center to pull facts, policies, and instructions it needs to respond to customers accurately. If your articles are clearly structured and easy to scan, AI Agent can find what it needs fast. If not, it hesitates or escalates.
Think of Guidance as AI Agent’s decision layer. What should AI Agent do when someone asks for a refund? What about when they ask for a discount? Guidance helps AI Agent provide accurate answers or hand over to a human by following an “if/when/then” framework.
Finally, AI Agent uses a combination of your help docs and Guidance to respond to customers, and if enabled, perform an Action on their behalf—whether that’s changing a shipping address or canceling an order altogether.
Here’s what that looks like in practice:

This structure removes guesswork for both your AI and your customers. The clearer your docs are about when something applies and what happens next, the more accurate and human your automated responses will feel.
A Help Center written for both people and AI Agent:
Our data shows that most AI escalations happen for a simple reason––your Help Center doesn’t clearly answer the question your customer is asking.
That’s not a failure of AI. It’s a content issue. When articles are vague, outdated, or missing key details, AI Agent can’t confidently respond, so it passes the ticket to a human.
Here are the top 10 topics that trigger escalations most often:
Rank |
Ticket Topic |
% of Escalations |
|---|---|---|
1 |
Order status |
12.4% |
2 |
Return request |
7.9% |
3 |
Order cancellation |
6.1% |
4 |
Product - quality issues |
5.9% |
5 |
Missing item |
4.6% |
6 |
Subscription cancellation |
4.4% |
7 |
Order refund |
4.1% |
8 |
Product details |
3.5% |
9 |
Return status |
3.3% |
10 |
Order delivered but not received |
3.1% |
Each of these topics needs a dedicated, clearly structured Help Doc that uses keywords customers are likely to search and spells out specific conditions.
Here’s how to strengthen each one:
Start by improving these 10 articles first. Together, they account for nearly half of all AI Agent escalations. The clearer your Help Center is on these topics, the fewer tickets your team will ever see, and the faster your AI will resolve the rest.
Once you know how AI Agent reads your content, the next step is formatting your help docs so it can easily understand and use them.
The goal isn’t to rewrite everything, it’s to make your articles more structured, scannable, and logic-friendly.
Here’s how.
Both humans and large language models read hierarchically. If your article runs together in one long block of text, key answers get buried.
Break articles into clear sections and subheadings (H2s, H3s) for each scenario or condition. Use short paragraphs, bullets, and numbered lists to keep things readable.
Example:
How to Track Your Order
A structured layout helps both AI and shoppers find the right step faster, without confusion or escalation.
AI Agent learns best when your Help Docs clearly define what happens under specific conditions. Think of it like writing directions for a flowchart.
Example:
This logic helps AI know what to do and how to explain the answer clearly to the customer.
Customers don’t always use the same words you do, and neither do LLMs. If your docs treat “cancel,” “stop,” and “pause” as interchangeable, AI Agent might return the wrong answer.
Define each term clearly in your Help Center and add small keyword variations (“cancel subscription,” “end plan,” “pause delivery”) so the AI can recognize related requests.
AI Agent follows links just like a human agent. If your doc ends abruptly, it can’t guide the customer any further.
Always finish articles with an explicit next step, like linking to:
Example: “If your return meets our policy, request your return label here.”
That extra step keeps the conversation moving and prevents unnecessary escalations.
AI tools prioritize structure and wording when learning from your Help Center—not emotional tone.
Phrases like “Don’t worry!” or “We’ve got you!” add noise without clarity.
Instead, use simple, action-driven sentences that tell the customer exactly what to do:
A consistent tone keeps your Help Center professional, helps AI deliver reliable responses, and creates a smoother experience for customers.
You don’t need hundreds of articles or complex workflows to make your Help Center AI-ready. But you do need clarity, structure, and consistency. These Gorgias customers show how it’s done.
Little Words Project keeps things refreshingly straightforward. Their Help Center uses short paragraphs, descriptive headers, and tightly scoped articles that focus on a single intent, like returns, shipping, or product care.
That makes it easy for AI Agent to scan the page, pull out the right facts, and return accurate answers on the first try.
Their tone stays friendly and on-brand, but the structure is what shines. Every article flows from question → answer → next step. It’s a minimalist approach, and it works. Both for customers and the AI reading alongside them.

Customer education is at the heart of Dr. Bronner’s mission. Their customers often ask detailed questions about product ingredients, packaging, and certifications. With Gorgias, Emily and her team were able to build a robust Help Center that helped to proactively give this information.
The Help Center doesn't just provide information. The integration of interactive Flows, Order Management, and a Contact Form automation allowed Dr. Bronner’s to handle routine inquiries—such as order statuses—quickly and efficiently. These kinds of interactive elements are all possible out-of-the-box, no IT support needed.


When Ekster switched to Gorgias, the team wanted to make their Help Center work smarter. By writing clear, structured articles for common questions like order tracking, returns, and product details, they gave both customers and AI Agent the information needed to resolve issues instantly.
"Our previous Help Center solution was the worst. I hated it. Then I saw Gorgias’s Help Center features, and how the Article Recommendations could answer shoppers’ questions instantly, and I loved it. I thought: this is just what we need." —Shauna Cleary, Head of Ecommerce at Ekster
The results followed fast. With well-organized Help Center content and automation built around it, Ekster was able to scale support without expanding the team.
“With all the automations we’ve set up in Gorgias, and because our team in Buenos Aires has ramped up, we didn’t have to rehire any extra agents.” —Shauna Cleary, Head of Ecommerce at Ekster
Learn more: How Ekster used automation to cover the workload of 4 agents
Rowan’s Help Center is a great example of how clear structure can do the heavy lifting. Their FAQs are grouped into simple categories like piercing, shipping, returns, and aftercare, so readers and AI Agent can jump straight to the right topic without digging.
For LLMs, that kind of consistency reduces guesswork. For customers, it creates a smooth, reassuring self-service experience.

TUSHY proves you can maintain personality and structure. Their Help Center articles use clear headings, direct language, and brand-consistent tone. It makes it easy for AI Agent to give accurate, on-brand responses.

“Too often, a great interaction is diminished when a customer feels reduced to just another transaction. With AI, we let the tech handle the selling, unabashedly, if needed, so our future customers can ask anything, even the questions they might be too shy to bring up with a human. In the end, everybody wins!" —Ren Fuller-Wasserman, Senior Director of Customer Experience at TUSHY
Ready to put your Help Center to the test? Use this five-point checklist to make sure your content is easy for both customers and AI to navigate.
Break up long text blocks and use descriptive headers (H2s, H3s) so readers and AI Agent can instantly find the right section.
Spell out what happens in each scenario. This logic helps AI Agent decide the right next step without second-guessing.
Make sure your Help Center includes complete, structured articles for high-volume issues like order status, returns, and refunds.
Close every piece with a call to action, like a form, related article, or support link, so neither AI nor customers hit a dead end.
Use direct, predictable phrasing. Avoid filler like “Don’t worry!” and focus on steps customers can actually take.
By tweaking structure instead of your content, it’s easier to turn your Help Center into a self-service powerhouse for both customers and your AI Agent.
Your Help Center already holds the answers your customers need. Now it’s time to make sure AI can find them. A few small tweaks to structure and phrasing can turn your existing content into a powerful, AI-ready knowledge base.
If you’re not sure where to start, review your Help Center with your Gorgias rep or CX team. They can help you identify quick wins and show you how AI Agent pulls information from your articles.
Remember: AI Agent gets smarter with every structured doc you publish.
Ready to optimize your Help Center for faster, more accurate support? Book a demo today.
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TL;DR:
Getting ready for that yearly ticket surge isn’t only about activating every automation feature on your helpdesk, it’s about increasing efficiency across your entire support operations.
This year, we’re giving you one less thing to worry about with our 2025 BFCM automation guide. Whether your team needs a tidier Help Center or better ticket routing rules, we’ve got a checklist for every area of the customer experience brought to you by top industry players, including ShipBob, Loop Returns, TalentPop, and more.
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Your customer knowledge base, FAQs, or Help Center is a valuable hub of answers for customers’ most asked questions. For those who prefer to self-serve, it’s one of the first resources they visit. To ensure customers get accurate answers, do the following:
Take stock of what’s currently in your database. Are you still displaying low-engagement or unhelpful articles? Are articles about discontinued products still up? Start by removing outdated content first, and then decide which articles to keep from there.
Related: How to refresh your Help Center: A step-by-step guide
Are you missing key topics, or don’t have a database yet? Look at last year’s tickets. What were customers’ top concerns? Were customers always asking about returns? Was there an uptick in free shipping questions? If an inquiry repeats itself, it’s a sign to add it to your Help Center.
An influx of customers means more people using your shipping, returns, exchanges, and discount policies. Make sure these have accurate information about eligibility, conditions, and grace periods, so your customers have one reliable source of truth.
Personalization tip: Loop Returns advises adjusting your return policy for different return reasons. With Loop’s Workflows, you can automatically determine which customers and which return reasons should get which return policies.
Read more: Store policies by industry, explained: What to include for every vertical
Customers want fast answers, so ensure your docs are easy to read and understand. Titles and answers should be clear. Avoid technical jargon and stick to simple sentences that express one idea. To accelerate the process, use AI tools like Grammarly and ChatGPT.
No time to set up a Help Center? Gorgias automatically generates Help Center articles for you based on what people are asking in your inbox.

Think of ticket routing like running a city. Cars are your tickets (and customers), roads are your inboxes, and traffic lights are your automations and rules. The better you maintain these structures, the better they can run on their own without needing constant repairs from your CX team.
Here’s your ticket routing automation checklist:
Instead of asking agents to tag every ticket, set rules that apply tags based on keywords, order details, or message type. A good starting point is to tag tickets by order status, returns, refunds, VIP customers, and urgent issues so your team can prioritize quickly.
Luckily, many helpdesks offer AI-powered tags or contact reasons to reduce manual work. For example, Gorgias automatically detects a ticket’s Contact Reason. The system learns from past interactions, tagging your tickets with more accuracy each time.

Custom or filtered inbox views give your agents a filtered and focused workspace. Start with essential views like VIP customers, returns, and damages, then add specialized views that match how your team works.
If you’re using conversational AI to answer tickets, views become even more powerful. For example, you might track low CSAT tickets to catch where AI responses fall short or high handover rates to identify AI knowledge gaps. The goal is to reduce clutter so agents can focus on delivering support.
Don’t get bogged down in minor issues while urgent tickets sit unanswered. Escalation rules make sure urgent cases are pushed to the top of your inbox, so they don’t risk revenue or lead to unhappy customers.
Tickets to escalate to agents or specialized queues:
Ticket Fields add structure by requiring your team to capture key data before closing a ticket. For BFCM, make fields like Contact Reason, Resolution, and Return Reason mandatory so you always know why customers reached out and how the issue was resolved.
For CX leads, Ticket Fields removes guesswork. Instead of sifting through tickets one by one, you’ll have clean data to spot trends, report on sales drivers, and train your team.
Pro Tip: Use conditional fields to dig deeper without overwhelming agents. For example, if the contact reason is “Return,” automatically prompt the agent to log the return reason or product defect.
Macros and AI Agent are your frontline during BFCM. When prepped properly, they can clear hundreds of repetitive tickets. The key is to ensure that answers are accurate, up-to-date, and aligned with what you want AI to handle.
Customers will flood your inbox with the same questions: “Where’s my order?” “When will my discount apply?” “What’s your return policy?” Write macros that give short, direct answers up front, include links for details, and use placeholders for personalization.
Bad macro:
Good macro:
Pro Tip: Customers expect deep discounts this time of year. BPO agency C(x)atalyze recommends automating responses to these inquiries with Gorgias Rules. Include words such as “discount” AND “BFCM”, “holiday”, “Thanksgiving”, “Black Friday”, “Christmas”, etc.
AI is only as good as the information you feed it. Before BFCM, make sure it’s pulling from:
Double-check a few responses in Test Mode to confirm the AI is pulling the right information.

Edge cases and urgent questions need a human touch, not an automated reply. Keep AI focused on quick requests like order status, shipping timelines, or promo eligibility. Complex issues, like defective products, VIP complaints, and returns, can directly go to your agents.
Pro Tip: In Gorgias AI Agent settings, you can customize how handovers happen on Chat during business hours and after hours.
Too few agents and you prolong wait times and miss sales. Too many and you’ll leave your team burned out. Capacity planning helps you find the balance to handle the BFCM surge.
Use your ticket-to-order ratio from last year as a baseline, then apply it to this year’s forecast. Compare that number against what your team can realistically handle per shift to see if your current staffing plan holds up.
Read more: How to forecast customer service hiring needs ahead of BFCM
You still have options if you don’t have enough agents helping you out. Customer service agency TalentPop recommends starting by identifying where coverage will fall short, whether that’s evenings, weekends, or specific channels. Then decide whether to increase automation and AI use or bring in temporary assistance.
Before the holiday season, run refreshers on new products, promos, and policy changes so no one hesitates when the tickets roll in. Pair training with cheat sheets or an internal knowledge base, giving your team quick access to the answers they’ll need most often.
Expect late shipments, low inventory, and more returns than usual during peak season. With the proper logistics automations, you can stay ahead of these issues while reducing pressure on your team.
ShipBob and Loop recommend the following steps:
Shipping costs add up fast during peak season. Work with your 3PL or partners like Loop Returns to take advantage of negotiated carrier rates and rate shopping tools that automatically select the most cost-effective option for each order.
To maintain a steady supply of products, set automatic reorder points at the SKU level so reorders are triggered once inventory dips below a threshold. More lead time means fewer ‘out of stock’ surprises for your customers.
Bad weather, delays, or unexpected demand can disrupt shipping timelines. Create a playbook in advance so your team knows exactly how to respond when things go sideways. At minimum, your plan should cover:
Customers want to know when their order will arrive before they hit checkout. Add estimated delivery dates and 2-day shipping badges directly on product pages. These cues help shoppers make confident decisions and reduce pre-purchase questions about shipping times.
Pro Tip: To keep those timelines accurate, build carrier cutoff dates into your Black Friday logistics workflows with your 3PL or fulfillment team. This allows you to avoid promising delivery windows your carriers can’t meet during peak season.
You’ve handled the basics, from ticket routing to staffing and logistics. Now it’s time to go beyond survival. Upselling automations create an end-to-end experience that enhances the customer journey, shows them products they’ll love, and makes it easy to buy more with confidence. To put them to work:
BFCM puts pressure on customers to find the right deal fast, but many don’t know what they’re looking for. Make it easier for them with macros that point shoppers to bestsellers or curated bundles. For a more advanced option, conversational AI like Gorgias Shopping Assistant can guide browsers on their own, even when your agents are offline.
No need to damage your conversion rate just because customers missed the items they wanted. Automations can recommend similar or complementary products, keeping customers engaged rather than leaving them empty-handed.
If an item is sold out, set up automations to:
Automations can detect hesitation through signals like abandoned carts, long checkout times, or even customer messages that mention keywords such as “too expensive” or “I’ll think about it.” In these cases, trigger a small discount to encourage the purchase.
You can take this a step further with conversational AI like Gorgias Shopping Assistant, which detects intent in real time. If a shopper seems uncertain, it can proactively offer a discount code based on the level of their buying intent.
During BFCM, speed alone is not enough. Customers expect accurate, helpful, and on-brand responses, even when volume is at its highest. QA automations help you prioritize quality by reviewing every interaction automatically and flagging where standards are slipping. To make QA part of your automation prep:
Manual QA can only spot-check a small sample of tickets, which means most interactions go unreviewed. AI QA reviews every ticket automatically and delivers feedback instantly. This ensures consistent quality, even when your team is flooded with requests.
Compared to manual QA, AI QA offers:

Customers should get the same level of quality no matter who replies. AI QA evaluates both human and AI conversations using the same criteria. This creates a fair standard and gives you confidence that every interaction meets your brand’s bar for quality.
QA automation is not just about grading tickets. It highlights recurring issues, unclear workflows, or policy confusion. Use these insights to guide targeted coaching sessions and refine AI guidance so both humans and AI deliver better results.
Pro Tip: Pilot your AI QA tool with a small group of agents before peak season. This lets you validate feedback quality and scale with confidence when BFCM volume hits.
The name of the game this Black Friday-Cyber Monday isn’t just to get a ton of online sales, it’s to set up your site for a successful holiday shopping season.
If you want to move the meter, focus on setting up strong BFCM automation flows now.
Gorgias is designed with ecommerce merchants in mind. Find out how Gorgias’s time-saving CX platform can help you create BFCM success. Book a demo today.
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TL;DR:
Shopping today isn’t a linear funnel. It’s a fluid conversation. Browse → question → help → buy → return → repeat.
Every step is a dialogue between the shopper’s intent and the brand’s response.
But what bridges the gap between “just looking” and “I’m buying” isn’t persuasion or urgency — it’s suggestion: the subtle design, timing, and language cues that guide action without forcing it.
When done well, suggestion becomes the architecture of trust. It’s also the best way to make AI-powered experiences feel human-first, not tech-first.
This article explores how the power of suggestion — rooted in behavioral psychology and UX design — shapes modern conversational commerce.
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The average ecommerce shopper faces thousands of micro-decisions from the moment they land on a site. Which product? Which variant? Which review to trust? Which shipping method? Each one adds cognitive weight.
Psychologist Barry Schwartz coined the term The Paradox of Choice to describe how abundance often leads to paralysis. In his research, participants faced with too many options were less likely to make a choice and less satisfied when they did.
In ecommerce, that means overload costs conversions. When shoppers must evaluate too many variables, they hesitate, second-guess, or abandon.
Shoppers today expect empathy and ease, not persuasion. When you suggest rather than push, you signal empathy and support.
This is especially important for conversational commerce. Suggestion humanizes automation by making AI interactions feel like conversations rather than transactions.
When you push and persuade, you create a memorable experience for customers — but it’s not the kind you want them to remember.
One Reddit thread perfectly captures the problem: a user tried to cancel their Thrive Market membership and had to ask nine times before the chatbot complied.

Each time, the AI assistant tried to talk them out of it (offering deals, guilt-tripping responses, or irrelevant messages) until the customer’s frustration boiled over.
The thread exploded not just because it was mildly infuriating, but because it illustrated what customers fear most about automation: a lack of empathy.
Suggestion is how you design for trust, ease, and interaction. And for ecommerce and CX professionals, suggestion bridges browsing and buying by prompting dialogue in a gentle, psychologically sound way.
The magic of suggestion is that it works with human psychology, not against it. It bridges the space between what a shopper wants to do and what helps them do it.
That’s the foundation of the Fogg Behavior Model, developed by Stanford’s Dr. BJ Fogg. The model states that behavior happens when three things intersect:
When these three align, the likelihood of action skyrockets.
In conversational commerce, suggestion is the gentle push that turns intent into interaction.
Below are five ways to apply suggestion with agentic AI (think chat, assistants, and marketing tools) to drive trust, dialogue, and conversion.
A first impression shapes the entire interaction.
A greeting like “Need help?” or “Looking for something special?” signals availability without applying pressure. It’s the digital equivalent of a store associate smiling and saying, “Let me know if you need anything.”
This works because of linguistic framing, which is a form of persuasive language that subtly shapes how people interpret intent.
In practice, this means:
Take a look at Glamnetic. Its shopping assistant sits at the bottom-right corner of every page. While shoppers scroll on the homepage, a prompt appears: “Shop with AI.” It’s transparent about being an AI chat, but subtle enough to be there for shoppers when they’re ready to use it at their own leisure.

Gorgias Shopping Assistant is an easy way to do this. At the right moment, Shopping Assistant appears with a greeting such as “Need help?” or “Chat with our AI!” It’s friendly, low-pressure, optional, more “Hey I’m here if you need” than “Buy now!”
If you’ve ever scrolled through 80 product filters and given up, you’ve experienced choice overload. This is the Paradox of Choice in action:
More options = higher cognitive effort = lower satisfaction.
Suggestion works because it reduces mental effort. When an AI assistant limits quick-reply options to just a few (say, “Long sleeve,” “Short sleeve,” “Sleeveless”), it transforms chaos into clarity.
Each small tap provides forward momentum, a concept known as the goal-gradient effect: the closer we feel to completing a goal, the faster and more positively we act.
How can you apply this to agentic AI?
Gorgias’s Shopping Assistant does this well, surfacing only the most relevant next steps. Instead of forcing open-ended typing, it guides shoppers through mini-decisions that build confidence. Here’s an example from Okanui, showing four clear options to reply to Shopping Assistant.

Before a shopper reads a single word of text, their brain has already judged whether your interface feels safe to engage with.
That’s the Aesthetic–Usability Effect — when people perceive something as visually appealing, they assume it will be easier and more trustworthy to use.
Design psychologist Don Norman put it best: “Attractive things work better because they make people feel better.”
Here’s why visual subtlety matters:
OSEA’s product description page is a beautiful example of unintrusive design in action. The buttons have rounded edges, the 10% offer isn’t covering other page elements, and the chat sits in the bottom-right corner, making it easily accessible if a shopper has questions about the product.

Timing is everything in suggestion-based design. Even the most thoughtful interaction will fail if it appears at the wrong moment.
That’s where the Fogg Behavior Model becomes tactical: Behavior = Motivation × Ability × Prompt
When shoppers are motivated (interested in a product) and able (engaging is easy), a well-timed prompt (chat bubble, message, or offer) turns potential into action.
But mistime it, and you risk the opposite. A chat that appears too early feels like spam. Too late, and the user’s interest window closes.
Here’s how to align the timing sweet spot:
Gorgias Shopping Assistant does all of the above. Using context — such as the current page, conversational context, and cart behavior — helps the AI trigger prompts like “Need help choosing a size?” or “Have questions about shipping?”

Every small suggestion — a phrase, a button shape, a pause, a tone — creates what behavioral economists call a moment of micro-trust.
Individually, these moments may feel insignificant. But together, they turn a static interface into a relationship.
When greeting, choices, design, and timing align, conversation becomes the natural outcome — not the goal. That’s what conversational commerce gets right: it reframes success from “did they convert?” to “did they connect?”
For CX teams, this shift requires designing for the emotional continuity of the experience:
We love this example from Perry Ellis to drive this tip home:

As AI continues to shape how people shop, brands face a choice: Design for control, or design for trust.
Suggestion is the path to the latter.
The right cue, delivered at the right time, reminds people that even in automated spaces, there’s still room for empathy and understanding.
Gorgias was built on the belief that great commerce starts with conversation, not conversion.
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TL;DR:
Handing trust over to AI can be intimidating. One off-brand reply and you undo the reputation and customer loyalty you’ve worked so hard to build.
That’s why we’ve made accuracy our top priority with Gorgias AI Agent.
For the past year, the Gorgias team has been hard at work fulfilling the pressing demand for accuracy and speed. AI Agent is getting smarter, faster, and more reliable, and merchants and their customers are happier with the output.
Here’s the data.
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This year, AI Agent’s accuracy rose from 3.55 to 4.08 out of 5, a 14.9% improvement from January. This average score is based on CX agents' ratings of AI Agent responses in the product, on a scale of 1 to 5.

In the past year, we’ve improved knowledge retrieval, added new integrations, expanded reporting features, and asked for more feedback in-product.
We saw the steadiest leap in July, right after the release of GPT-5. AI Agent began reaching levels of consistency and accuracy that agents could trust.
Clear, easy-to-understand language helps people trust what they’re reading. Website Planet found that 85% more visitors bounced from a page when typos were present. That’s why we’ve made it a priority for AI Agent to respond to customers with correct grammar, syntax, and tone of voice.
The efforts have paid off: AI Agent scores a high 4.77 out of 5 in language proficiency compared to 4.4 for human agents. The result is error-free messages that are easy to read and consistent with your brand vocabulary.

Accuracy isn’t just about saying the right thing; it’s also about how a message lands. For that reason, we track AI Agent’s communication quality. Did it reply with empathy? Did it exhibit active listening and respond with clear phrasing?
Recently, AI Agent is even scoring slightly above humans with 4.48 out of 5 in communication, compared to 4.27. This means AI Agent captures the nuance of every message by considering the background context and acknowledging customer frustration before it gives customers a solution.
What happens when a ticket ends without a clear answer? Customers feel neglected and leave the chat still unsure. This can make your brand look out of touch, leaving customers with the lingering feeling that you don’t care.
But don’t worry, we built AI Agent to close that loop every time: AI Agent’s resolution completeness score sits at a perfect 1 out of 1, compared to 0.99 out of 1 for human agents.
In practice, this means customers feel cared for and understood, while your team receives fewer follow-ups, giving them more time to focus on strategic, high-priority tasks.
Read more: A guide to resolution time: How to measure and lower it
Building a great product is a two-way conversation between our engineers and the people who use it. We listen, review feedback, ship changes, and measure what improves.
From January to November 2025, AI Agent quality rose from about 57% to 85%. August was the first big step up, and September kept climbing. Brands are seeing fewer low-quality or incorrect answers and more steady decisions.
This is proof that merchants and their shoppers are witnessing the improvements we’ve been making, for the better.

Related: The engineering work that keeps Gorgias running smoothly
At the end of the day, what matters is how customers feel when they talk to support. Do they trust the answer? Do they find it helpful? Are they running into more friction with AI than without it?
Our data shows that customers are appreciating AI assistance more and more. Since the start of 2025, AI Agent on live chat has gotten a CSAT score 40% closer to the average CSAT of human agents. For email, the gap has narrowed by about 8%.
The goal is to eventually achieve a gap of zero. At this point, AI’s support quality is indistinguishable from that of humans. To get there, we’re focusing on practical improvements like accuracy, clear language, complete answers, and better handoff rules.

How we measure CSAT gap: The CSAT gap is calculated by subtracting AI CSAT from human CSAT. When the number is closer to zero, AI is catching up. When it’s negative, AI is still below human results.
Behind every accurate AI reply is a team that cares about the details. AI Agent doesn’t make up answers—it follows what you teach it. The more effort your team puts into maintaining an up-to-date Help Center and Guidance, the better the customer experience becomes.
As we look ahead to 2026, we’re focused on fine-tuning knowledge retrieval logic, refining Guidance rules, and continuously learning from feedback from you and your customers.
We’re proud of the strides AI Agent continues to make, and can’t wait for more brands to experience the accuracy for themselves.
Want to see how AI Agent delivers exceptional accuracy without sacrificing speed? Book a demo or start a trial today.
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TL;DR:
Sizing has long been a friction point for ecommerce fashion shoppers.
Without the ability to try items on, 58% of shoppers resort to "bracketing"—ordering multiple sizes of the same piece and returning what doesn’t fit.
While it gives customers a temporary fix, it ultimately creates frustration for them and logistical headaches for brands.
The result is rising return rates, higher costs, and wasted resources. To break this cycle, ecommerce brands need to rethink how they guide shoppers toward the perfect fit. The good news is that many brands are already showing the way by using AI-powered tools and smarter product experiences to replicate the fitting room from the comfort of home.
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Recent data highlights just how severe the return challenge has become for fashion and apparel retailers:
In addition, rapidly rising concerns around sustainability and climate change, as well as heightened awareness around over-consumption, are prompting consumers to make changes in their purchasing habits.
Brands who prioritize well-fitting, long-lasting pieces and reduce carbon footprints and the amount of clothing diverted to landfills by lowering returns can actually benefit from a strategic edge.
“Those who choose to approach sustainability with a long-term mindset even while battling short-term problems will be rewarded with more efficient business operations and a competitive advantage,” writes McKinsey in its State of Fashion 2025 report.
Most brands already have size charts, but shoppers don’t want to measure themselves, or find those charts to be inaccurate.
When shoppers lack confidence in choosing the right fit, they either abandon their carts or rely on bracketing, both of which lower profitability and customer trust.
Forward-looking fashion and apparel brands are solving sizing issues by using tools for a more intuitive shopping experience. This ultimately helps them build loyalty, increase retention, and reduce returns.
Rather than purely providing static size charts on your website, opt for AI-generated personalized fit recommendations instead.
For example, European fashion retailer Zalando reduced size-related returns by 10% using AI-driven advice.

The brand flags whether an item is true to size or not. It also offers the ability for customers to see recommendations based on logged fit-based return reasons, past purchases, and other clothing items that fit them well.
Zalando also launched a body measurement feature in 2023 where shoppers can actually scan themselves for more accurate size advice.

As AI grows in proficiency, there are more tools than ever to help shoppers visualize product scale and fit.
For example, accessory shop LeSportsac uses Tangiblee, a product experience tool, to help customers understand scale and what fits inside each bag.

Performance hunting gear shop KUIU takes another approach. It uses a photo-based layering guide, so shoppers can see how the size and fit look with multiple layers on a model. Different model stats shown within product photography give contextual sizing cues.

Sleep shop Cozy Earth takes a similar route, stating model height and size on product photos.

Some brands are helping shoppers pick the right size with interactive quizzes based on factors like height, weight, and the sizes of other clothing items that fit well. SuitShop is among those brands using a Fit Finder quiz on its website.

Similarly, Psycho Bunny leverages the AI tool True Fit as a size finder on product pages.

Ergonomic shoe brand Orthofeet eliminates sizing qualms altogether by including customizable inserts inside each box. Fitting spacers ensure a snug fit and arch enhancement for those who need it, helping shoppers get comfortable shoes that fit.

Jonas Paul Eyewear shares the “try it on at home” approach, offering a free or low-cost home try-on kit.

Gorgias Shopping Assistant helps brands meet that need by delivering human-like guidance at scale, giving shoppers instant answers that feel personal.
For example, VESSEL uses Shopping Assistant in chat to provide real-time support on sizing and inventory, helping customers choose with confidence. By addressing fit questions directly, Shopping Assistant reduces returns and builds trust at the point of purchase.

Similarly, outdoor clothing retailer Arc‘teryx provides an “ask me anything” AI chat where shoppers can confirm any questions they have around fit or sizing.

Sizing for ecommerce fashion and apparel brands has become a business-critical challenge. With 70% of returns tied to fit issues and nearly half of shoppers abandoning purchases over inconvenient returns, brands that replicate the fitting room online stand to gain a competitive advantage.
From Zalando’s 10% reduction in size-related returns to VESSEL’s use of AI-powered chat, the path is clear: investing in smarter size chart solutions pays off with higher retention, lower costs, and stronger sustainability.
The brands that provide fitting room-level experiences online now will set themselves apart from the rest.
Book a demo to see how Gorgias, the leading conversational commerce platform, helps fashion brands cut returns, drive sales, and deliver fitting-room level experiences online.
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TL;DR:
While your competitors are still making customers wait days for email replies, the smartest brands are having conversations that close sales in real time.
Instead of forcing customers to search through FAQs or go through an automation loop, conversational commerce lets you have instant chats through live chat, messaging apps, and even AI assistants.
In this guide, we’ll explain conversational commerce, where it delivers the most value, and how to start using it to drive revenue and improve CX without overwhelming your team.
Conversational commerce means using real-time, two-way conversations as your storefront. Rather than bottling up questions in FAQ pages or forcing customers to wait for your support team to respond, you can instantly connect via:
Maybe someone is on your product page and asks a question like, “Does this jacket run large?”. Through chat, they get an instant answer, increasing the chance of a sale. Or a shopper receives personalized recommendations via WhatsApp and checks out, all without leaving the app.
These channels allow you to meet customers where they already are, effortlessly. When paired with AI chatbots, you can deliver fast, accurate responses 24/7, even while your team is off the clock. That means better experiences for your customers and more sales captured for your brand.
Conversational commerce bridges the gap between shopping and support. It turns your support team (and AI tools) into revenue drivers by helping shoppers feel seen, heard, and ready to buy.
Conversational commerce means bringing your storefront into the flow of conversation, wherever that happens for your customers.
Here’s where those conversations typically happen:
This is a chat widget on your site, often in the bottom right corner, where shoppers can ask questions and receive immediate answers from a human agent or automation.
It’s a quick path to support or purchase, which one agent can manage multiple chats from simultaneously, boosting efficiency and keeping things personal.
These smart helpers use Natural Language Processing (NLP) to understand what shoppers mean beyond what they type. They guide customers through questions, offer product suggestions, handle FAQs, and can sometimes complete transactions right in the chat, even handling post‑purchase support like order status or returns.
Natural Language Processing (NLP): The processing of understanding and interpreting natural language using computers. NLP is used in tasks such as sentiment analysis, summarization, speech recognition, and more.
Think WhatsApp, Facebook Messenger, WeChat, and SMS—the apps where customers already spend their time in their day-to-day. Instead of sending them to shop on your website, you bring the shopping to them. Answer their questions, provide recommendations, and win purchases in a channel they already trust.
Voice assistance isn’t limited to smart speakers like Siri and Alexa anymore.
Now, AI voice support lets brands deliver natural conversations over the phone, without needing a massive contact center team. These AI voice agents can:
AI-powered voice support combines the human feel of a phone call with the speed and accuracy of automation. It's especially useful for high-ticket products, customers who prefer calling, or peak season overflow when your human team is maxed out.
Conversational commerce isn’t a CX buzzword. When done right, it directly impacts your bottom line.
Here’s how it pays off for ecommerce brands:
When customers can ask questions and get answers in real time, whether it's sizing info, shipping details, or help choosing between products, they’re far more likely to hit “buy.”
Success story: Clothing brand Tommy John generated $106K+ in sales in just two months through conversation-led upselling and cross-selling, with a 15% conversion rate.
Conversational commerce tools like AI agents help offload the repetitive support tasks, including answering questions like “Where’s my order?” or “What’s your return policy?”
With that time back, agents get time back to:
Instead of getting buried in basic tickets, your team gets to do the work that really moves the needle for your customers and your business.
Related: Every successful marketing campaign starts with a customer question
The right nudge at the right moment, like a personalized recommendation from an AI shopping assistant, can turn a single item into a full cart. You can also recover more abandoned checkouts by re-engaging customers directly through chat or a messaging app.
Read more: You’re missing out on sales without an AI shopping assistant—here’s why
Conversational commerce lets you meet customers with a human (or human-like) touch. When your brand is helpful, fast, and easy to talk to, shoppers remember and return.
In the long run, that means better customer retention, higher lifetime value, and more organic growth through word of mouth.
Conversational commerce shines brightest when the stakes are high or when the moment is just right.
Here are the critical moments where a real-time conversation can make all the difference:
A customer’s on your product page, they’ve added an item to their cart, but are hesitating. Maybe they’re unsure about sizing, shipping time, or which variation to choose. This is where a quick, helpful chat, automated or human, comes in and becomes the difference between bounce and conversion.
Pro tip: Use proactive chat prompts based on page behavior to start the conversation before the shopper leaves.
After a customer hits “place order,” expect more questions to roll into your inbox. Where’s my order? How do I track it? What’s your return policy? Post-purchase excitement—and anxiety—is normal, and a smart AI agent helps you get ahead of these questions while putting customers at ease.
Black Friday. Holiday rush. Product drops. These are prime opportunities to boost revenue—but they also flood your support team. Conversational commerce tools help you scale without sacrificing quality, keeping shoppers happy and sales flowing.
If you sell skincare, supplements, tech, or anything that requires a bit of education, your customers likely need guidance before they commit. A personalized conversation helps them find the right fit and feel more confident in their purchase.
Conversational commerce sounds exciting, and it is. But before you dive in, it’s worth thinking through a few key factors to set your team (and your customers) up for success.
You don’t need a full-blown chatbot army on Day 1. Start with your highest-impact touchpoints, like pre-sale FAQs or WISMO questions, and layer in automation over time. The goal is to generate clear ROI early, then expand once you see traction.
Here’s how to gradually implement automation into your CX process:
The goal isn’t to automate everything, it’s to automate smartly so your team can spend time where it counts: high-touch sales, VIP support, and strategic growth.
Do you have in-house agents ready to handle live chat? Or do you need automation to handle the bulk of it? Make sure your setup aligns with your team’s bandwidth.
Pro tip: Tools like Gorgias AI Agent and Shopping Assistant can handle the support and sales heavy lifting, making them perfect for lean CX teams.
Your customers aren’t just on your website. They’re messaging on Instagram, browsing via mobile, or checking their texts. To deliver great conversational commerce, you’ll want to show up in the places your shoppers already use.
Pro tip: Don’t spread your efforts too thin. Start with the channel that aligns with your goals and customer behavior, live chat, SMS, or social DMs, and build from there.
Ready to make conversational commerce part of your CX strategy? You don’t need to overhaul your tech stack or hire a whole new team. With Gorgias, you can start fast, stay lean, and scale smart.
Here’s how:
Gorgias AI Agent is designed to take repetitive tickets off your team’s plate, from “Where’s my order?” to “How do I make a return?” It understands natural language, pulls in relevant customer data, and responds in seconds—all using your brand’s approved knowledge.
The result is faster responses, fewer tickets, and more time back for your team.

While AI Agent, covers the support front, Shopping Assistant is your digital salesperson. It engages high-intent shoppers in real time, recommends the right products, and even upsells or cross-sells based on what the customer is browsing.
Whether it’s helping someone choose the perfect shade or nudging them to complete their cart, Shopping Assistant is designed to increase AOV and reduce abandonment.

Every time a shopper lands on your site, scrolls through Instagram, or replies to a shipping update, they’re opening the door to a conversation. The brands that show up quickly, helpfully, and with the right message, are the ones winning loyalty and revenue.
With AI Agent, you can automate accurate responses to common questions, giving your team time back without sacrificing customer experience. And with Shopping Assistant, you can turn those conversations into conversions, offering personalized recommendations, upsells, and discounts based on shopper intent.
You don’t need a massive team or months of setup to start. Just the right tools, and a strategy built for your customers.
Book a demo and learn how Gorgias helps you turn every conversation into an opportunity to grow.
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TL;DR:
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?
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We’ve reviewed the 10 best AI helpdesks available in 2025, evaluating them across AI capabilities, ease of use, integrations, analytics, and pricing.
Helpdesk |
AI Features |
Main Strength |
Potential Limitation |
Best For |
Starting Price |
|---|---|---|---|---|---|
Gorgias |
AI Agent, Shopping Assistant, Auto QA |
Multi-channel ecommerce support, AI shopping assistant |
Ecommerce-focused |
Scaling and enterprise ecommerce brands |
$10/month per agent |
Zendesk |
Copilot, AI triage, Zendesk QA |
Enterprise-grade omnichannel support |
Can be complex for smaller teams |
Large enterprises like banks and airlines |
$25/month per agent |
Intercom |
Fin AI, Fin Tasks, Fin Insights |
Conversational AI, proactive support |
Higher learning curve for complex workflows |
SaaS and mid-to-large businesses |
$39/month per agent |
Gladly |
Gladly Hero, Sidekick Chat, Sidekick Voice |
Conversation-centric support, loyalty focus |
Complex implementation onboarding process |
Customer-focused businesses that prioritize loyalty |
Custom pricing |
Kustomer |
AI Agents for Reps, AI Agents for Customers |
CRM-centric support |
Unintuitive and laggy user interface |
Mid-to-large enterprises |
$89/month per agent |
Tidio |
Lyro AI Agent |
Easy-to-use automation for small teams |
May not scale for large enterprise workflows |
Small to mid-sized ecommerce/service businesses |
Free, $29/month per agent |
Freshdesk |
Freddy AI |
Affordable multi-channel support |
Advanced AI limited to higher tiers |
SMBs and mid-market companies |
$18/month per agent |
Ada |
Ada Voice, Ada Email |
Self-service chat automation |
Basic features cost extra |
Large enterprise businesses |
$499/month |
Siena |
Customer Service Agent, Reviews Agent, Siena Memory |
Automated support |
Lack of visibility into support and AI performance |
Mid-market ecommerce and SaaS |
$500/month |
Yuma |
Support AI, Sales AI, Social AI |
Self-service & automation for growing teams |
Limited integrations with broader sales stacks |
Established ecommerce brands |
$49/month per agent |
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:
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.
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:
AI features:
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:
AI features:
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:
AI features:
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:
AI features:
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:
AI features:
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:
AI features:
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:
AI features:
Not ready to move helpdesks? These standalone AI tools plug into your existing helpdesk to add automation, self-service, and conversational support.
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:
AI features:
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:
AI features:
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:
AI features:
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:
|
Feature |
What It Is |
Benefit to CX Team |
|---|---|---|
|
Smart ticket management |
AI that deflects repetitive tickets and routes complex issues to agents via macros, recommendations, and copilots |
Frees up time for higher-value tasks like customer retention and streamlined experiences |
|
Self-service workflows |
Automated execution of order edits, address changes, refunds, and cancellations—whenever customers ask |
Eliminates time spent on repetitive requests while offering 24/7 support |
|
Multi-channel support |
All-in-one platform consolidating email, chat, SMS, social media, and phone interactions |
Eliminates the need to switch between platforms while giving customers a variety of contact options |
|
Sales and upselling capabilities |
AI that analyzes shopper behavior and delivers targeted assistance, product recommendations, and offers |
Maximizes revenue impact for CX teams by directly influencing customer buying decisions |
|
User-friendly AI controls |
Intuitive tools and toggles for adjusting AI behavior through knowledge bases |
Allows teams to test and deploy AI quickly without technical expertise |
|
Performance insights |
Dashboards displaying performance metrics, support KPIs, revenue impact, plus custom reporting |
Maintains support quality while providing scalable insights that grow with your business |
|
AI learning and improvement |
Quality assurance features that improve AI through feedback, corrections, and knowledge updates |
Enables accurate responses that lead to consistent support quality and increased customer satisfaction |
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:

TL;DR:
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.
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Gorgias is a powerful platform. Out of the box, it gives you:
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.
Here’s how Atidiv leverages Gorgias to drive real results:
Atidiv agents don’t just respond to tickets, they tag every interaction with purpose.
This turns your inbox into a live dashboard of customer sentiment, product feedback, and emerging trends, no extra software required.
Atidiv writes and maintains Macros that go beyond “Thanks for reaching out.”
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.
Every Atidiv client gets a customized Gorgias dashboard. It’s built by Atidiv’s Team Leads to track what matters:
No more wondering if your support is working, now you know.
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 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:
And no, they didn’t need to buy any new tools.
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:
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.

TL;DR:
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…
Here are six lessons you can steal from the brands doing it best.
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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.
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:

“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
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:
AI gives you the flexibility to test, tweak, and tailor your approach in a way traditional support channels never could.

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.
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)
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:
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
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:
|
Metrics Tracked Before AI |
Metrics Tracked After AI |
|---|---|
|
Total ticket volume |
% of tickets resolved by AI |
|
Average first response time |
Response time by channel (AI vs. human) |
|
CSAT (overall) |
CSAT + sentiment on AI-resolved tickets |
|
Tickets per agent/hour |
Time saved per agent + resolution quality |
|
Burnout rate or turnover |
Agent satisfaction or eNPS |
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:

TL;DR:
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.
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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.
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
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.
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:
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:

“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
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.
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:

Related: The hidden cost of not adopting AI in ecommerce
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.
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.
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:
“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.
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TL;DR:
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.
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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.
The stages of the customer journey where common drop-off points occur for brands that lack proactive support include:
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.

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
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."
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
The main reasons customers abandoned a cart in 2025 include:
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.
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.
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:
|
Feature |
Traditional Chatbot |
AI Shopping Assistant |
|---|---|---|
|
Deflect tickets |
✅ |
✅ |
|
Answer frequently asked questions |
✅ |
✅ |
|
Upselling |
❌ |
✅ |
|
Proactively reaching out to offer support |
❌ |
✅ |
|
Use context-based signals to guide shoppers to checkout |
❌ |
✅ |
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.
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TL;DR:
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.
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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:
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.

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:
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.

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.
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:
Here’s how Shopping Assistant reduces drop-off, builds confidence, and drives faster decision-making in three different ways.
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.
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.
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.
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.
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.
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