

TL;DR:
You’ve chosen your AI tool and turned it on, hoping you won’t have to answer another WISMO question. But now you’re here. Why is AI going in circles? Why isn’t it answering simple questions? Why does it hand off every conversation to a human agent?
Conversational AI and chatbots thrive on proper training and data. Like any other team member on your customer support team, AI needs guidance. This includes knowledge documents, policies, brand voice guidelines, and escalation rules. So, if your AI has gone rogue, you may have skipped a step.
In this article, we’ll show you the top seven AI issues, why they happen, how to fix them, and the best practices for AI setup.
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AI can only be as accurate as the information you feed it. If your AI is confidently giving customers incorrect answers, it likely has a gap in its knowledge or a lack of guardrails.
Insufficient knowledge can cause AI to pull context from similar topics to create an answer, while the lack of guardrails gives it the green light to compose an answer, correct or not.
How to fix it:
This is one of the most frustrating customer service issues out there. Left unfixed, you risk losing 29% of customers.
If your AI is putting customers through a never-ending loop, it’s time to review your knowledge docs and escalation rules.
How to fix it:
It can be frustrating when AI can’t do the bare minimum, like automate WISMO tickets. This issue is likely due to missing knowledge or overly broad escalation rules.
How to fix it:
One in two customers still prefer talking to a human to an AI, according to Katana. Limiting them to AI-only support could risk a sale or their relationship.
The top live chat apps clearly display options to speak with AI or a human agent. If your tool doesn’t have this, refine your AI-to-human escalation rules.
How to fix it:
If your agents are asking customers to repeat themselves, you’ve already lost momentum. One of the fastest ways to break trust is by making someone explain their issue twice. This happens when AI escalates without passing the conversation history, customer profile, or even a summary of what’s already been attempted.
How to fix it:
Sure, conversational AI has near-perfect grammar, but if its tone is entirely different from your agents’, customers can be put off.
This mismatch usually comes from not settling on an official customer support tone of voice. AI might be pulling from marketing copy. Agents might be winging it. Either way, inconsistency breaks the flow.
How to fix it:
When AI is underperforming, the problem isn’t always the tool. Many teams launch AI without ever mapping out what it's actually supposed to do. So it tries to do everything (and fails), or it does nothing at all.
It’s important to remember that support automation isn’t “set it and forget it.” It needs to know its playing field and boundaries.
How to fix it:
AI should handle |
AI should escalate to a human |
|---|---|
Order tracking (“Where’s my package?”) |
Upset, frustrated, or emotional customers |
Return and refund policy questions |
Billing problems or refund exceptions |
Store hours, shipping rates, and FAQs |
Technical product or troubleshooting issues |
Simple product questions |
Complex or edge‑case product questions |
Password resets |
Multi‑part or multi‑issue requests |
Pre‑sale questions with clear, binary answers |
Anything where a wrong answer risks churn |
Once you’ve addressed the obvious issues, it’s important to build a setup that works reliably. These best practices will help your AI deliver consistently helpful support.
Start by deciding what AI should and shouldn’t handle. Let it take care of repetitive tasks like order tracking, return policies, and product questions. Anything complex or emotionally sensitive should go straight to your team.
Use examples from actual tickets and messages your team handles every day. Help center articles are a good start, but real interactions are what help AI learn how customers actually ask questions.
Create rules that tell your AI when to escalate. These might include customer frustration, low confidence in the answer, or specific phrases like “talk to a person.” The goal is to avoid infinite loops and to hand things off before the experience breaks down.
When a handoff happens, your agents should see everything the AI did. That includes the full conversation, relevant customer data, and any actions it has already attempted. This helps your team respond quickly and avoid repeating what the customer just went through.
An easy way to keep order history, customer data, and conversation history in one place is by using a conversational commerce tool like Gorgias.
A jarring shift in tone between AI and agent makes the experience feel disconnected. Align aspects such as formality, punctuation, and language style so the transition from AI to human feels natural.
Look at recent escalations each week. Identify where the AI struggled or handed off too early or too late. Use those insights to improve training, adjust boundaries, and strengthen your automation flows.
If your AI chatbot isn’t working the way you expected, it’s probably not because the technology is broken. It’s because it hasn’t been given the right rules.
When you set AI up with clear responsibilities, it becomes a powerful extension of your team.
Want to see what it looks like when AI is set up the right way?
Try Gorgias AI Agent. It’s conversational AI built with smart automation, clean escalations, and ecommerce data in its core — so your customers get faster answers and your agents stay focused.
TL;DR:
While most ecommerce brands debate whether to implement AI support, customers already rate AI assistance nearly as highly as human support. The future isn't coming. It's being built in real-time by brands paying attention.
As a conversational commerce platform processing millions of support tickets across thousands of brands, we see what's working before it becomes common knowledge. Three major shifts are converging faster than most founders realize, and this article breaks down what's already happening rather than what might happen someday.
By the end of 2026, we predict that the performance gap between ecommerce brands won't be determined by who adopted AI first. It will be determined by who built the content foundation that makes AI actually work.
Right now, we're watching this split happen in real time. AI can only be as good as the knowledge base it draws from. When we analyze why AI escalates tickets to human agents, the pattern is unmistakable.
The five topics triggering the most AI escalations are:
These aren’t complicated questions — they're routine questions every ecommerce brand faces daily. Yet some brands automate these at 60%+ rates while others plateau at 20%. The difference isn't better AI. It's better documentation.
Take SuitShop, a formalwear brand that reached 30% automation with a lean CX team. Their Director of Customer Experience, Katy Eriks, treats AI like a team member who needs coaching, not a plug-and-play tool.
When Katy first turned on AI in August 2023, the results were underwhelming. So she paused during their slow season and rebuilt their Help Center from the ground up. "I went back to the tickets I had to answer myself, checked what people were searching in the Help Center, and filled in the gaps," she explained.
The brands achieving high automation rates share Katie's approach:
AI echoes whatever foundation you provide. Clear documentation becomes instant, accurate support. Vague policies become confused AI that defaults to human escalation.
Read more: Coach AI Agent in one hour a week: SuitShop’s guide
Two distinct groups will emerge next year. Brands that invest in documentation quality now will deliver consistently better experiences at lower costs. Those who try to deploy AI on top of messy operations will hit automation plateaus and rising support costs. Every brand will eventually have access to similar AI technology. The competitive advantage will belong to those who did the unexciting work first.
Something shifted in July 2025. Gorgias’s AI accuracy jumped significantly after the GPT-5 release. For the first time, CX teams stopped second-guessing every AI response. We watched brand confidence in AI-generated responses rise from 57% to 85% in just a few months.
What this means in practice is that AI now outperforms human agents:
For the first time, AI isn't just faster than humans. It's more consistent, more accurate, and even more empathetic at scale.
This isn't about replacing humans. It's about what becomes possible when you free your team from repetitive work. Customer expectations are being reset by whoever responds fastest and most completely, and the brands crossing this threshold first are creating a competitive moat.
At Gorgias, the most telling signal was AI CSAT on chat improved 40% faster than on email this year. In other words, customers are beginning to prefer AI for certain interactions because it's immediate and complete.
Within the next year, we expect the satisfaction gap to hit zero for transactional support. The question isn't whether AI can match humans. It's what you'll do with your human agents once it does.
The brands that have always known support should drive revenue will finally have the infrastructure to make it happen on a bigger scale. AI removes the constraint that's held this strategy back: human bandwidth.
Most ecommerce leaders already understand that support conversations are sales opportunities. Product questions, sizing concerns, and “just browsing” chats are all chances to recommend, upsell, and convert. The problem wasn't awareness but execution at volume.
We analyzed revenue impact across brands using AI-powered product recommendations in support conversations. The results speak for themselves:
It's clear that conversations that weave in product recommendations convert at higher rates and result in larger order values. It’s time to treat support conversations as active buying conversations.
If you're already training support teams on product knowledge and tracking revenue per conversation, keep doing exactly what you're doing. You've been ahead of the curve. Now AI gives you the infrastructure to scale those same practices without the cost increase.
If you've been treating support purely as a cost center, start measuring revenue influence now. Track which conversations lead to purchases, which agents naturally upsell, and where customers ask for product guidance.
We are now past the point where response time is a brand's key differentiator. It is now the use of conversational commerce or systems that share details and context across every touchpoint.
Today, a typical customer journey looks something like this: see product on Instagram, ask a question via DM, complete purchase on mobile, track order via email. At each step, customers expect you to remember everything from the last interaction.
The most successful ecommerce tech stacks treat the helpdesk as the foundation that connects everything else. When your support platform connects to your ecommerce platform, shipping providers, returns portal, and every customer communication channel, context flows automatically.
A modern integration approach looks like this. Your ecommerce platform (like Shopify) feeds order data into a helpdesk like Gorgias, which becomes the hub for all customer conversations across email, chat, SMS, and social DMs. From there, connections branch out to payment providers, shipping carriers, and marketing automation tools.
As Dr. Bronner’s Senior CX Manager noted, “While Salesforce needed heavy development, Gorgias connected to our entire stack with just a few clicks. Our team can now manage workflows without needing custom development — we save $100k/year by switching."
As new channels emerge, brands with flexible tech stacks will adapt quickly while those with static systems will need months of development work to support new touchpoints. The winners will be brands that invest in their tools before adding new channels, not after customer complaints force their hand.
Start auditing your current integrations now. Where does customer data get stuck? Which systems don’t connect to each other? These gaps are costing you more than you realize, and in the future, they'll be the key to scaling or staying stagnant.
Post-purchase support quality will be a stronger predictor of customer lifetime value than any email campaign. Brands that treat support as a retention investment rather than a cost center will outperform in repeat purchase rates.
Returns and exchanges are make-or-break moments for customer lifetime value. How you handle problems, delays, and disappointments determines whether customers come back or shop elsewhere next time. According to Narvar, 96% of customers say they won’t repurchase from a brand after a poor return experience.
What customers expect reflects this reality. They want proactive shipping updates without having to ask, one-click returns with instant label generation, and notifications about problems before they have to reach out. When something goes wrong, they expect you to tell them first, not make them track you down for answers.
The quality of your response when things go wrong matters more than getting everything right the first time. Exchange suggestions during the return flow can keep the sale alive, turning a potential loss into loyalty.
Brands that treat post-purchase as a retention strategy rather than a task to cross off will see much higher repeat purchase rates. Those still relying purely on email marketing for retention will wonder why their customer lifetime value plateaus.
Start measuring post-return CSAT scores and repeat purchase rates by support interaction quality. These metrics will tell you whether your post-purchase experience is building loyalty or quietly eroding it.
After absorbing these predictions about AI accuracy, content infrastructure, revenue-centric support, context, and post-purchase tactics, here's your roadmap for the next 24 months.
Now (in 90 days):
Next (in 6-12 months):
Watch (in 12-24 months):
The patterns we've shared, from AI crossing the accuracy threshold to documentation quality, are happening right now across thousands of brands. Over the next 24 months, teams will be separated by operational maturity.
Book a demo to see how leading brands are already there.
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TL;DR:
Customer education has become a critical factor in converting browsers into buyers. For wellness brands like Cornbread Hemp, where customers need to understand ingredients, dosages, and benefits before making a purchase, education has a direct impact on sales. The challenge is scaling personalized education when support teams are stretched thin, especially during peak sales periods.
Katherine Goodman, Senior Director of Customer Experience, and Stacy Williams, Senior Customer Experience Manager, explain how implementing Gorgias's AI Shopping Assistant transformed their customer education strategy into a conversion powerhouse.
In our second AI in CX episode, we dive into how Cornbread achieved a 30% conversion rate during BFCM, saving their CX team over four days of manual work.
Before diving into tactics, understanding why education matters in the wellness space helps contextualize this approach.
Katherine, Senior Director of Customer Experience at Cornbread Hemp, explains:
"Wellness is a very saturated market right now. Getting to the nitty-gritty and getting to the bottom of what our product actually does for people, making sure they're educated on the differences between products to feel comfortable with what they're putting in their body."
The most common pre-purchase questions Cornbread receives center around three areas: ingredients, dosages, and specific benefits. Customers want to know which product will help with their particular symptoms. They need reassurance that they're making the right choice.
What makes this challenging: These questions require nuanced, personalized responses that consider the customer's specific needs and concerns. Traditionally, this meant every customer had to speak with a human agent, creating a bottleneck that slowed conversions and overwhelmed support teams during peak periods.
Stacy, Senior Customer Experience Manager at Cornbread, identified the game-changing impact of Shopping Assistant:
"It's had a major impact, especially during non-operating hours. Shopping Assistant is able to answer questions when our CX agents aren't available, so it continues the customer order process."
A customer lands on your site at 11 PM, has questions about dosage or ingredients, and instead of abandoning their cart or waiting until morning for a response, they get immediate, accurate answers that move them toward purchase.
The real impact happens in how the tool anticipates customer needs. Cornbread uses suggested product questions that pop up as customers browse product pages. Stacy notes:
"Most of our Shopping Assistant engagement comes from those suggested product features. It almost anticipates what the customer is asking or needing to know."
Actionable takeaway: Don't wait for customers to ask questions. Surface the most common concerns proactively. When you anticipate hesitation and address it immediately, you remove friction from the buying journey.
One of the biggest myths about AI is that implementation is complicated. Stacy explains how Cornbread’s rollout was a straightforward three-step process: audit your knowledge base, flip the switch, then optimize.
"It was literally the flip of a switch and just making sure that our data and information in Gorgias was up to date and accurate."
Here's Cornbread’s three-phase approach:
Actionable takeaway: Block out time for that initial knowledge base audit. Then commit to regular check-ins because your business evolves, and your AI should evolve with it.
Read more: AI in CX Webinar Recap: Turning AI Implementation into Team Alignment
Here's something most brands miss: the way you write your knowledge base articles directly impacts conversion rates.
Before BFCM, Stacy reviewed all of Cornbread's Guidance and rephrased the language to make it easier for AI Agent to understand.
"The language in the Guidance had to be simple, concise, very straightforward so that Shopping Assistant could deliver that information without being confused or getting too complicated," Stacy explains. When your AI can quickly parse and deliver information, customers get faster, more accurate answers. And faster answers mean more conversions.
Katherine adds another crucial element: tone consistency.
"We treat AI as another team member. Making sure that the tone and the language that AI used were very similar to the tone and the language that our human agents use was crucial in creating and maintaining a customer relationship."
As a result, customers often don't realize they're talking to AI. Some even leave reviews saying they loved chatting with "Ally" (Cornbread's AI agent name), not realizing Ally isn't human.
Actionable takeaway: Review your knowledge base with fresh eyes. Can you simplify without losing meaning? Does it sound like your brand? Would a customer be satisfied with this interaction? If not, time for a rewrite.
Read more: How to Write Guidance with the “When, If, Then” Framework
The real test of any CX strategy is how it performs under pressure. For Cornbread, Black Friday Cyber Monday 2025 proved that their conversational commerce strategy wasn't just working, it was thriving.
Over the peak season, Cornbread saw:
Katherine breaks down what made the difference:
"Shopping Assistant popping up, answering those questions with the correct promo information helps customers get from point A to point B before the deal ends."
During high-stakes sales events, customers are in a hurry. They're comparing options, checking out competitors, and making quick decisions. If you can't answer their questions immediately, they're gone. Shopping Assistant kept customers engaged and moving toward purchase, even when human agents were swamped.
Actionable takeaway: Peak periods require a fail-safe CX strategy. The brands that win are the ones that prepare their AI tools in advance.
One of the most transformative impacts of conversational commerce goes beyond conversion rates. What your team can do with their newfound bandwidth matters just as much.
With AI handling straightforward inquiries, Cornbread's CX team has evolved into a strategic problem-solving team. They've expanded into social media support, provided real-time service during a retail pop-up, and have time for the high-value interactions that actually build customer relationships.
Katherine describes phone calls as their highest value touchpoint, where agents can build genuine relationships with customers. “We have an older demographic, especially with CBD. We received a lot of customer calls requesting orders and asking questions. And sometimes we end up just yapping,” Katherine shares. “I was yapping with a customer last week, and we'd been on the call for about 15 minutes. This really helps build those long-term relationships that keep customers coming back."
That's the kind of experience that builds loyalty, and becomes possible only when your team isn't stuck answering repetitive tickets.
Stacy adds that agents now focus on "higher-level tickets or customer issues that they need to resolve. AI handles straightforward things, and our agents now really are more engaged in more complicated, higher-level resolutions."
Actionable takeaway: Stop thinking about AI only as a cost-cutting tool and start seeing it as an impact multiplier. The goal is to free your team to work on conversations that actually move the needle on customer lifetime value.
Cornbread isn't resting on their BFCM success. They're already optimizing for January, traditionally the biggest month for wellness brands as customers commit to New Year's resolutions.
Their focus areas include optimizing their product quiz to provide better data to both AI and human agents, educating customers on realistic expectations with CBD use, and using Shopping Assistant to spotlight new products launching in Q1.
The brands winning at conversational commerce aren't the ones with the biggest budgets or the largest teams. They're the ones who understand that customer education drives conversions, and they've built systems to deliver that education at scale.
Cornbread Hemp's success comes down to three core principles: investing time upfront to train AI properly, maintaining consistent optimization, and treating AI as a team member that deserves the same attention to tone and quality as human agents.
As Katherine puts it:
"The more time that you put into training and optimizing AI, the less time you're going to have to babysit it later. Then, it's actually going to give your customers that really amazing experience."
Watch the replay of the whole conversation with Katherine and Stacy to learn how Gorgias’s Shopping Assistant helps them turn browsers into buyers.
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TL;DR:
Rising customer expectations, shoppers willing to pay a premium for convenience, and a growing lack of trust in social media channels to make purchase decisions are making it more challenging to turn a profit.
In this emerging era, AI’s role is becoming not only more pronounced, but a necessity for brands who want to stay ahead. Tools like Gorgias Shopping Assistant can help drive measurable revenue while reducing support costs.
For example, a brand that specializes in premium outdoor apparel implemented Shopping Assistant and saw a 2.25% uplift in GMV and 29% uplift in average order volume (AOV).
But how, among competing priorities and expenses, do you convince leadership to implement it? We’ll show you.
Shoppers want on-demand help in real time that’s personalized across devices.
Shopping Assistant recalls a shopper’s browsing history, like what they have clicked, viewed, and added to their cart. This allows it to make more relevant suggestions that feel personal to each customer.
The AI ecommerce tools market was valued at $7.25 billion in 2024 and is expected to reach $21.55 billion by 2030.
Your competitors are using conversational AI to support, sell, and retain. Shopping Assistant satisfies that need, providing upsells and recommendations rooted in real shopper behavior.
Conversational AI has real revenue implications, impacting customer retention, average order value (AOV), conversion rates, and gross market value (GMV).
For example, a leading nutrition brand saw a GMV uplift of over 1%, an increase in AOV of over 16%, and a chat conversion rate of over 15% after implementing Shopping Assistant.
Overall, Shopping Assistant drives higher engagement and more revenue per visitor, sometimes surpassing 50% and 20%, respectively.

Shopping Assistant engages, personalizes, recommends, and converts. It provides proactive recommendations, smart upsells, dynamic discounts, and is highly personalized, all helping to guide shoppers to checkout.
After implementing Shopping Assistant, leading ecommerce brands saw real results:
Industry |
Primary Use Case |
GMV Uplift (%) |
AOV Uplift (%) |
Chat CVR (%) |
|---|---|---|---|---|
Home & interior decor 🖼️ |
Help shoppers coordinate furniture with existing pieces and color schemes. |
+1.17 |
+97.15 |
10.30 |
Outdoor apparel 🎿 |
In-depth explanations of technical features and confidence when purchasing premium, performance-driven products. |
+2.25 |
+29.41 |
6.88 |
Nutrition 🍎 |
Personalized guidance on supplement selection based on age, goals, and optimal timing. |
+1.09 |
+16.40 |
15.15 |
Health & wellness 💊 |
Comparing similar products and understanding functional differences to choose the best option. |
+1.08 |
+11.27 |
8.55 |
Home furnishings 🛋️ |
Help choose furniture sizes and styles appropriate for children and safety needs. |
+12.26 |
+10.19 |
1.12 |
Stuffed toys 🧸 |
Clear care instructions and support finding replacements after accidental product damage. |
+4.43 |
+9.87 |
3.62 |
Face & body care 💆♀️ |
Assistance finding the correct shade online, especially when previously purchased products are no longer available. |
+6.55 |
+1.02 |
5.29 |
Shopping Assistant drives uplift in chat conversion rate and makes successful upsell recommendations.
“It’s been awesome to see Shopping Assistant guide customers through our technical product range without any human input. It’s a much smoother journey for the shopper,” says Nathan Larner, Customer Experience Advisor for Arc’teryx.
For Arc’teryx, that smoother customer journey translated into sales. The brand saw a 75% increase in conversion rate (from 4% to 7%) and 3.7% of overall revenue influenced by Shopping Assistant.

Because it follows shoppers’ live journey during each session on your website, Shopping Assistant catches shoppers in the moment. It answers questions or concerns that might normally halt a purchase, gets strategic with discounting (based on rules you set), and upsells.
The overall ROI can be significant. For example, bareMinerals saw an 8.83x return on investment.
"The real-time Shopify integration was essential as we needed to ensure that product recommendations were relevant and displayed accurate inventory,” says Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations, UK at bareMinerals.
“Avoiding customer frustration from out-of-stock recommendations was non-negotiable, especially in beauty, where shade availability is crucial to customer trust and satisfaction. This approach has led to increased CSAT on AI converted tickets."

Shopping Assistant can impact CSAT scores, response times, resolution rates, AOV, and GMV.
For Caitlyn Minimalist, those metrics were an 11.3% uplift in AOV, an 18% click through rate for product recommendations, and a 50% sales lift versus human-only chats.
"Shopping Assistant has become an intuitive extension of our team, offering product guidance that feels personal and intentional,” says Anthony Ponce, its Head of Customer Experience.

Support agents have limited time to assist customers as it is, so taking advantage of sales opportunities can be difficult. Shopping Assistant takes over that role, removing obstacles for purchase or clearing up the right choice among a stacked product catalog.
With a product that’s not yet mainstream in the US, TUSHY leverages Shopping Assistant for product education and clarification.
"Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models,” says Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY.
“Expanding our product catalog has given customers more choices than ever, which can overwhelm first-time buyers. Now, they’re increasingly looking to us for guidance on finding the right fit for their home and personal hygiene needs.”
The bidet brand saw 13x return on investment after implementation, a 15% increase in chat conversion rate, and a 2x higher conversion rate for AI conversations versus human ones.

Customer support metrics include:
Revenue metrics to track include:
Shopping Assistant connects to your ecommerce platform (like Shopify), and streamlines information between your helpdesk and order data. It’s also trained on your catalog and support history.
Allow your agents to focus on support and sell more by tackling questions that are getting in the way of sales.
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TL;DR:
Most shoppers arrive with questions. Is this the right size? Will this match my skin tone? What’s the difference between these models? The faster you can guide them, the faster they decide.
As CX teams take on a bigger role in driving revenue, these moments of hesitation are now some of the most important parts of the buying journey.
That’s why more brands are leaning on conversational AI to support these high-intent questions and remove the friction that slows shoppers down. The impact speaks for itself. Brands can expect higher AOV, stronger chat conversion rates, and smoother paths to purchase, all without adding extra work to your team.
Below, we’re sharing real use cases from 11 ecommerce brands across beauty, apparel, home, body care, and more, along with the exact results they saw after introducing guided shopping experiences.
When you’re shopping for shoes similar to an old but discontinued favorite, every detail counts, down to the color of the bottom of the shoe. But legacy brands with large catalogs can be overwhelming to browse.
For shoppers, it’s a double-edged sword: they want to feel confident that they checked your entire collection, but they also don’t want to spend time looking for it.
How Shopping Assistant helps:
Shopping Assistant accelerates the process, turning hazy details into clear, friendly guidance.
It describes shoe details, from colorways to logo placement, compares products side by side, and recommends the best option based on the shopper’s preferences and conditions.
The result is shoppers who feel satisfied and more connected with your brand.

Results:
Big events call for great outfits, but putting one together online isn’t always easy. With thousands of options to scroll through, shoppers often want a bit of styling direction.
How Shopping Assistant helps:
Shoppers get to chat with a virtual stylist who recommends full outfits based on the occasion, suggests accessories to complete the look, and removes the guesswork of pairing pieces together.
The result is a fun, confidence-building shopping experience that feels like getting advice from a stylist who actually understands their plans.

Results:
Shade matching is hard enough in-store, but doing it online can feel impossible. Plus, when a longtime favorite gets discontinued, shoppers are left guessing which new shade will come closest. That uncertainty often leads to hesitation, abandoned carts, or ordering multiple shades “just in case.”
How Shopping Assistant helps:
Shoppers find their perfect match without any of the guesswork. The assistant asks a few quick questions, recommends the closest shade or formula, and offers smart alternatives when a product is unavailable.
The experience feels like chatting with a knowledgeable beauty advisor — someone who makes the decision easy and leaves shoppers feeling confident in what they’re buying.
Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations at bareMinerals UK says, “What impressed me the most is the AI’s ability to upsell with a conversational tone that feels genuinely helpful and doesn't sound too pushy or transactional. It sounds remarkably human, identifying correct follow-up questions to determine the correct product recommendation, resulting in improved AOV. It’s exactly how I train our human agents and BPO partners.”

Results:
When shoppers are buying gifts, especially for someone else, they often know who they’re shopping for but not what to buy. A vague product name or a half-remembered scent can quickly make the experience feel overwhelming without someone to guide them.
How Shopping Assistant helps:
Thoughtful guidance goes a long way. By asking clarifying questions and recognizing likely mix-ups, Shopping Assistant helps shoppers figure out what the recipient was probably referring to, then recommends the right product along with complementary gift options that make the choice feel intentional.
It brings the reassurance of an in-store associate to the online experience, helping shoppers move forward with confidence.

Results:
Finding the right bra size online is notoriously tricky. Shoppers often second-guess their band or cup size, and even small uncertainties can lead to returns — or abandoning the purchase altogether.
Many customers just want someone to walk them through what a proper fit should actually feel like.
How Shopping Assistant helps:
Searching for products is no longer a time-consuming process. Shopping Assistant detects a shopper’s search terms and sends relevant products in chat. Like an in-store associate, it uses context to deliver what shoppers are looking for, so they can skip the search and head right to checkout.

Results:
For shoppers buying personalized jewelry, the details directly affect the final result. That’s why customization questions come up constantly, and why uncertainty can quickly stall the path to purchase.
How Shopping Assistant helps:
Shopping Assistant asks about the shopper’s style preferences and customization needs, then recommends the right product and options so they can feel confident the final piece is exactly their style. The experience feels quick, helpful, and designed to guide shoppers toward a high investment purchase.

Results:
Decorating a home is personal, and shoppers often want reassurance that a new piece will blend with what they already own. Questions about color palettes, textures, and proportions come up constantly. And without guidance, it’s easy for shoppers to feel unsure about hitting “add to cart.”
How Shopping Assistant helps:
Giving shoppers personalized styling support helps them visualize how pieces will work in their home.
Shoppers receive styling suggestions based on their existing space as well as recommendations on pieces that complement their color palette.
It even guides them toward a 60-minute virtual styling consultation when they need deeper help. The experience feels thoughtful and high-touch, which is why shoppers often spend more once they feel confident in their choices.

Results:
When shoppers discover a new drink mix, they’re bound to have questions before committing. How strong will it taste? How much should they use? Will it work with their preferred drink or routine? Uncertainty at this stage can stall the purchase or lead to disappointment later.
How Shopping Assistant helps:
Clear, friendly guidance in chat helps shoppers understand exactly how to use the product. Shopping Assistant answers questions about serving size, flavor strength, and pairing options, and suggests the best way to prepare the mix based on the shopper’s preferences.

Results:
Shopping for health supplements can feel confusing fast. Customers often have questions about which formulas fit their age, health goals, or daily routine. Without clear guidance, most will hesitate or pick the wrong product.
How Shopping Assistant helps:
Shopping Assistant detects hesitation when shoppers linger on a search results page. It proactively asks a few clarifying questions, narrows down product options, and points shoppers to the best product or bundle for their needs.
The entire experience feels supportive and gives shoppers confidence they’ve picked the right option.

Results:
Shopping for kids’ furniture comes with a lot of “Is this the right one?” moments. Parents want something safe, sturdy, and sized correctly for their child’s age. With so many options, it’s easy to feel unsure about what will actually work in their space.
How Shopping Assistant helps:
Shopping Assistant guides parents toward the best fit right away. It asks about their child’s age, room layout, and safety considerations, then recommends the most appropriate bed or furniture setup. The experience feels like chatting with a knowledgeable salesperson who understands what families actually need as kids grow.

Results:
Even something as simple as choosing a toothbrush can feel complicated when multiple models come with different speeds, materials, and features. Shoppers want to understand what matters so they can pick the one that fits their routine and budget.
How Shopping Assistant helps:
Choosing between toothbrush models shouldn’t feel like decoding tech specs. When shoppers can see the key differences in plain language, including what’s unique, how each model works, and who it’s best for, they can make a decision with ease.
Suddenly, the whole process feels simple instead of overwhelming.

Results:
Across all 11 brands, one theme is clear. When shoppers get the guidance they need at the right moment, they convert more confidently and often spend more.
Here’s what stands out:
What this means for you:
Look closely at your most common pre-purchase questions. Anywhere shoppers hesitate from fit, shade, technical specs, styling, bundles is a place where Shopping Assistant can step in, boost confidence, and unlock more sales.
If you notice the same patterns in your own store, such as shoppers hesitating over sizing, shade matching, product comparisons, or technical details, guided shopping can make an immediate impact. These moments are often your biggest opportunities to increase revenue and improve the buying experience.
Many of the brands in this post started by identifying their most common pre-purchase questions and letting AI handle them at scale. You can do the same.
If you want to boost conversions, lift AOV, and create a smoother path to purchase, now is a great time to explore guided shopping for your team.
Book a demo or activate Shopping Assistant to get started.
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Quick summary:
Gross Merchandise Value (GMV) is a useful metric to monitor when running an ecommerce site. Traditionally, it’s one of the first numbers online merchants try to improve sales. It sounds simple enough: If you increase GMV, you’ll make more money, right?
Not so fast.
Like any single metric, GMV has its shortcomings, too. Below we’ll explain the right way to think about GMV and ways to increase GMV that can lead to more profit, not just more revenue.
Gross merchandise value measures the total value of goods sold on a platform or marketplace over a specific period of time. GMV is the full amount customers pay before deductions like fees, discounts, or returns.
GMV and revenue are not interchangeable. Revenue is what remains after subtracting deductions from the GMV.
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You can use the following formula to calculate GMV:
Gross merchandise value = sales price of goods x number of items sold
If you sell something for $100 through Etsy and Etsy takes a 10% commission, that’s $100 GMV for Etsy.
In terms of revenue, $90 of revenue is for you and $10 of revenue for Etsy.
If you sell something for $100 on your own website, your GMV and revenue are $100.
GMV provides insight into a platform's sales strength before considering deductions, but it doesn't reflect actual revenue or profit.
In this section, we'll examine the advantages, limitations, and risks of depending solely on GMV to evaluate your business' performance.
GMV is a versatile metric that can be used for more than just evaluating how profitable your business is. Here are the five benefits of using GMV:
Although GMV offers valuable insights, it falls short of capturing a complete financial overview of your business. Let's look at some drawbacks of relying on GMV alone.
The best way to use GMV is to complement it with other essential key performance indicators (KPIs). Here's how you can use GMV in tandem with other metrics:
If you’re looking for ways to improve GMV for your ecommerce website, here are four ways to do that.
Free shipping is a popular option for online shopping, where customers don’t have to pay for delivery. Free shipping is attractive to customers who are sensitive to price and prefer a simple pricing structure.
Here is a good example from Teddy Fresh:

Two different ways to offer free shipping to increase GMV:
🛒 Setting up an ecommerce store? Check out our list of the best Shopify themes.
Upselling is a strategy to sell a superior, more expensive version of a product that a customer already owns (or just bought). Meanwhile, cross-selling means selling related products to the one a customer already owns (or just bought).
To upsell products, you can offer larger sizes, adding more features, or increasing performance. For example, if a customer wants a 4GB graphics card, upsell them to 16GB with a limited-time discount and a slightly higher price than their previous choice.
For cross-sell, you can add a “frequently bought with this item” or “who bought this bought this” section on your product pages. Or promote accessories on the cart page as Cariuma does in the below example:

Product bundling is when you package complimentary products as a group of items that can be purchased together at a discount or a lower price than when purchased separately.
You can bundle products together as an upsell or a cross-sell. Alternatively, you can create a unique product bundle, either in a gift box or special wrapping.
Winc is just one example of an online store that has capitalized on an opportunity for product education and curation with subscription boxes. The brand uses a quiz to help customers determine the right bottle of wine that satisfies their tastes. Then, offer curated boxes of items that meet their preferences.

When you have a lot of slow-moving inventory products, it’s a great idea to bundle them with popular items. Doing that will help freshen up your old or overstocked inventory and increase sales.
By offering bundles, you can also make customers feel that they got a good deal — even though they’ve likely spent more than they planned to.
Setting up your Shopify store? See our list of the best Shopify apps for ecommerce merchants.
Bulk discount (also known as bulk pricing or volume discount) is a sales strategy that encourages customers to purchase more and with higher quantities at a lower price. This is particularly useful if you’re selling items that are typically bought in bulk.
Note that you can also use free gifts or free products to incentivize customers who spend more on your store. Cotopaxi did a great job of using this tactic. This store offers customers free masks if they spend beyond a certain threshold.

Approximately 95% of customers say that customer service is important to their choice of and loyalty to a brand. And 80% of customers consider the experience a company provides as important as its products.
These are just a few of many key customer service statistics, but enough to prove that an excellent customer service experience impacts your bottom line.
When you take time to answer customers’ questions on social media and live chat, you build trust with them and make them feel safe to buy from you.
When you’re proactive in reducing returns, you have a chance to turn them into new sales. Your customer might be satisfied with an exchange instead of asking for a refund.
That strengthens your brand confidence and encourages customers to come back to your store.
After all, retaining an existing customer is five times cheaper than finding a new one. By delivering exceptional customer service, you give your customers a convincing reason to stay with your business forever.
GMV is helpful if you’re selling on marketplaces like Etsy, Amazon, or Alibaba. But as said earlier, you shouldn’t focus too much on improving GMV. There are more important ecommerce KPIs you should follow to measure how your store performs.
Also, it’s one thing to increase GMV; it’s another thing to maintain excellent customer service when you have more orders. Take care of your customers first to create an incredible shopping experience for them, and you’ll improve your bottom line sooner or later.
If you’re looking for a solution to help you handle a flood of customer requests, let Gorgias lend you a hand.
Sign up for a Gorgias account and enjoy all the features you need in an ecommerce help desk in a 7-day free trial.
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You went back to check your store and noticed an error in the checkout page settings, preventing customers from making payments on your store.
Do you think you would experience the moment of dread in that situation?
I bet you would.
When you’re launching an online store, there are many details to remember—and those details can make or break your business's success.
However, by having a rock-solid ecommerce launch checklist in place, you can eliminate errors and rid yourself of “dread” moments forever.
The following checklist will help you figure out the key things you need to get ready when launching your online store. Think of it as a quality-assurance check for your ecommerce launch.
Let’s jump in.
Your ecommerce website is where customers will visit to learn more about what you’re offering. It’s also where shopping activities happen.

Hence, ensure your website includes these most recommended standard pages:
A worthy note is that your ecommerce website doesn’t have to include a blog page. It depends on your marketing strategy, product types, and target audience (more on that later).
A listing page or a category page is where customers discover your products associated with a specific category. It’s useful for keeping your website coherent and helping customers find what they’re looking for quickly. You can take listing pages to a whole new level by using them to increase conversions and enhance your overall SEO.

Ensure you include the following elements in your listing pages:
Product pages are where the buy buttons show up. But they’re also where many other things can go wrong: lack of trust, unclear information about products, etc. That’s why each product page must be optimized as much as possible.

Keep in mind the following:
The shopping cart is where shoppers review their selected items and make the purchasing decision. The goal of this page is to lead shoppers to the checkout page.
Follow these tips to create an effective shopping cart:
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The checkout page is where cart abandonment often happens. So ensure you review it carefully as much as possible.

Remember these to build a high-converting checkout page:
Many ecommerce websites rely on social media or paid advertising to drive conversions. They ignore entirely or put together with little consideration of search engine optimization (SEO).
But ecommerce SEO is worth investing in because 44% of people start their online shopping journey with a Google search. Also, 37.5% of all traffic to ecommerce sites comes from search engines.

Keep in mind the following:
Recommended reading: SEO for ecommerce, Dominate Google in 10 Easy Steps.

On an ecommerce website, conversions are critical. Check out the following to make sure your store is optimized for high conversion rates:

Every ecommerce platform offers an app store filled with amazing apps to extend your commerce store’s functionality and grow your business. That’s why you should find the most essential apps and install them into your store:
Here are some app types you should consider:
Good customer service means better customer retention and more sales. That’s why choosing the right helpdesk is crucial for your online business. It’ll not only help you provide the best customer support, increase engagement, and convert more sales in the process but also seamlessly integrate with your current ecommerce platform.
For ecommerce businesses, Gorgias is an ideal solution as it’s an ecommerce-dedicated ticketing system and has tight integration with Shopify, BigCommerce, and Magento.

Here is what Gorgias offers:

Using email marketing is one of the best ways to develop and maintain a good relationship with customers. If your ecommerce business hasn’t taken the time to adopt email marketing, you’re likely leaving money on the table.
Here are the eight most important emails for ecommerce:
The U.S. now has over 230 million active social media users, with nearly 7 million added in 2019. That doesn’t mention the fact that ecommerce sales are heavily influenced by social media. Since your customers are very likely already on some social platforms, you might want to go where they are.

Keep the following in mind:
Recommended reading: Master Social Media Marketing for Ecommerce in 10 Easy Steps
It’s essential to set up analytics tracking and monitoring from day one because doing that will give you valuable insights into your visitors and customers.

Your ecommerce platform has its own set of analytics reporting built-in, but you may also want to consider trying these tips:
Also, be sure you understand the importance of the following ecommerce metrics:
The secret to ecommerce success isn’t just to get your products out there and see how they perform. You need a marketing plan to bring your products to potential customers and convince them to buy.
Without a marketing plan, you might miss out on the fact that “More and more brands are competing for the same eyes. Facebook’s algorithm rewards video and motion-based creative that are more likely to hook your audience quickly. And customers are also more demanding, impatient and curious than ever before,” as Scott Ginsberg, Head of Content, Metric Digital says.
Ensure your marketing plan includes:
One of the best ways to reduce abandoned carts is by providing as many payment methods as possible since everyone has different preferences.

Consider integrating these payment options:
Regarding credit cards, you need to set up payment authorization to capture payment from your customers. You can do this by accessing your ecommerce platform admin. For example, in Shopify, you can set up automatic or manual capture of credit card payments. Shopify Payments provides an authorization period of 7 days.
To avoid errors and remove common online shopping hassles, you need to carefully test your ecommerce website before launching it. Also, run continuous A/B testing to identify what makes your customers happy and what brings conversions to your store.
Ensure you do the following tests:
This ecommerce launch checklist represents a roadmap for online merchants looking to start their business from scratch. Mastering the basics, and you’ll avoid all the hassles along the way.
Let’s wrap up:
And once your store is up and running, check out these 13 ecommerce growth tactics to take your store to the next level.
Looking for a customer support app for your ecommerce store? Sign up for a Gorgias account and enjoy all the premium features for free in 7 days. Gorgias is an ecommerce-focused helpdesk solution that will help you create the best experience for your customers, improve your support team’s performance, and eventually drive sales.
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The overall best customer support metrics to track:
Most brands keep a close eye on sales numbers, marketing performance, and other parts of the business that generate revenue. But they don’t do a great job measuring customer support performance, usually because they don’t understand the link between customer experience and revenue.
Your customer support team might already measure how quickly you respond to support tickets, which is a great start. The list of metrics we share below paint a fuller picture of the larger impact customer support has on business growth. And once you can demonstrate your impact on business growth, you can start making the case for better tools and more staff.
Track these customer support metrics, improve them, and watch your customer loyalty, repeat purchases, and revenue rise.
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Below, we describe 25 of the most essential customer service metrics, organized into six categories. Some metrics have to do with your team's performance — like how quickly and well you respond to tickets. Other metrics look deeper at your team's impact on larger company goals, like customer retention and revenue generation.
We’ll also share how to calculate each of these metrics. For some, a simple formula will suffice. For others, a dedicated tool like a helpdesk or survey automation tool will save tons of time.
That said, here are the top customer support metrics to track:
Response time metrics
Customer satisfaction metrics
Conversation metrics
Agent performance metrics
Churn & retention metrics
Revenue-related metrics

First response time (FRT) is a metric that tracks how long it takes for you to reply to the first message in a conversation with a customer.
Top performing companies using Gorgias have an average first response time of .54 hours. However, the benchmark varies per channel: aim to respond to email tickets within 24 hours and live chat messages within 90 seconds, according to Klipfolio.
Calculating your average first response time is relatively simple — most helpdesks will report this number for you. If you don’t have a helpdesk, you can find first response times for tickets by comparing the time stamp when you first received the customer request with the timestamp of the first response. If you received the message at 8 AM on Monday and respond at 8 AM on Tuesday, your first response time is one day.
Add up all of your first response times from the period of time you’re looking to analyze — for example, one month — and then divide that number by the total number of resolved tickets during that same time frame:
Total first response times during chosen time period / total # of resolved tickets during chosen time period = Average first response time
Using real numbers, here’s an example of what this calculation looks like:
74,000 seconds / 800 resolved tickets = 92.5 seconds (average first response time)
Your average reply time (or average response time) refers to how long it takes for you to respond to any customer support message, not just the first message of a ticket. Your average response time should be similar to the first response time. You don’t want to keep customers waiting, even in prolonged conversations.
To find your average response time, add up the total time your team has taken to respond to requests during a specific time period. Then, divide that number by the total number of responses your team sent during that time period:
Total time taken to respond during chosen time period / number of sent responses = Average response time


Average resolution time (ART) refers to the amount of time it takes for your customer support team to fully solve the customer’s problem and close the ticket. We analyzed data across about 6,000 ecommerce companies using Gorgias to provide customer support and we found that the top-performing companies have an average resolution time of 1.67 hours.
Inside Gorgias, your average resolution time is automatically tracked. In your account, you’ll get visual reports showing your average resolution time in a given time period.
To calculate average resolution time, also sometimes referred to as “mean time,” begin by choosing a specific time period to analyze. Then, total up the length of all of your resolved conversations with customers during that time period. Once you have that number, divide it by the number of conversations had during the time period you’ve chosen to analyze:
Total duration of resolved conversations / # of customer conversations = Average resolution time
You know what customers absolutely love? When they can get their issues resolved with a single interaction. Single-reply resolution rate calculates what percentage of your tickets are handled with the first reply. It’s also known as the first contact resolution rate or FCR.
Single-reply resolution rate = Total number of requests resolved with one interaction in a single time period divided by the total number of requests in the same time period.
To find your single-reply resolution rate, you can simply divide the number of support issues that were resolved on the first reply by the total number of tickets that are FCR-eligible (FCR-eligible means only including tickets that are possible to give a resolution in one response). As a formula, it would look like this:
Number of support issues resolved on first contact / total number of FCR-eligible support tickets = FCR rate
The average handle time (AHT) is an important metric to track if you offer customer service via phone. In today’s online world, most ecommerce companies handle tickets only with chat and email. However, very large ecommerce brands may choose to provide phone call support as well.
The average ticket handline time includes the total talk time and total hold time for that caller. You can calculate the average for larger periods of time to get better insights, such as per week or per month.
Not using voice support? Learn about 4 benefits of adding voice support to your ecommerce store.
To find your average ticket handling time, add up the total time spent on all voice tickets within the time period you’re analyzing, including talk time, hold time, and follow-up time. Then, divide that number by the number of tickets a customer support agent handled on all channels within that same period of time:
Total voice ticket time / # of total tickets touched = Average handle time

Customer satisfaction (CSAT) is a metric to measure your customer base’s level of satisfaction with their experience. CSAT is one of the most important measurements because satisfied customers return to your store, refer friends, leave reviews, and unlock reliable revenue for your brand.
CSAT compiles responses to a very simple question: “How would you rate the help [Agent] gave you?” You can use a survey or a website feedback widget to ask customers to rate on a scale of 1 to 5 how satisfied they are with a support experience.
CSAT aims to get an overall benchmark for your team’s performance, plus information about the service experience each agent provides. If this score suddenly drops or peaks, you should act fast to see what happened. For example, you may be sending delayed or unhelpful responses after launching a new product, getting a spike in ticket volume, or changing a policy like refunds and returns.
Read our in-depth guide to CSAT score for more tips on improving your CSAT score and CSAT survey response rates.
Calculate your customer satisfaction score by asking a question like, “How would you rate your satisfaction with the goods/services you received?” Then, you would give the customer the option to respond on a scale of 1-5. The scale would look something like this:
With Gorgias, you can automatically send one of these surveys after each interaction with customer support:

Once your customers respond, you’ll need to use the responses in this formula if you don’t have a helpdesk that does it automatically:
(Total number of 4 and 5 responses, or “satisfied customers” / number of total responses) x 100 = CSAT
An example of this could look like this:
(126 4 and 5 responses) / (300 total responses) x 100 = 42% CSAT, which indicates you aren’t doing a great job of satisfying customers.
If you use Gorgias, you can automatically send customer satisfaction surveys and track your scores over time. Learn more about our satisfaction survey and dashboard:


Support performance score is a metric Gorgias created that combines average first response time, average resolution time, and CSAT for a single score out of five that concisely represents your customer service performance. If you could only track one customer service metric — which we do not recommend — it would be this one.
Support performance score balances these three metrics to represent three of the most important elements of quality support:

Support performance score is calculated with a series of thresholds for CSAT, FRT, and resolution time. You have to meet the threshold in each category to reach the next level. Here are the thresholds for FRT, for example:
If you use Gorgias, you’ll see your support performance score over time, plus a breakdown of each metric that makes up your score.
According to The Effortless Experience, 96% of high-effort customer experiences drive customer disloyalty. In other words, the amount of effort across your entire customer journey has a huge bearing on the success of your customer experience and, by extension, your brand’s revenue.

By measuring CES, you and your team members can work towards reducing customer effort, which in turn will increase the lifetime customer value and the likelihood of word-of-mouth referrals.
You may be wondering what exactly is considered “high effort.” This could include long wait times when a customer calls in or reaches out via email, or not getting a concise response — which leads to time-consuming back-and-forth. Of course, “effort” is subjective and highly dependent on the individual customer and their expectations.
To measure CES, you’ll need to utilize another survey. The questionnaire should ask the customer how much effort they had to exert in order to get their question answered.
For example, “[insert company name] made it easy for me to handle my issue.” Then, you’d provide a scale of 1 to 10. A score of 1 would be “strongly disagree,” while 10 would be “strongly agree.”
Once you’ve collected the data, you can calculate your average customer effort score:
Total sum of all responses / total number of responses = CES

Customer contact rate measures the percentage of active customers who contact support each day, month, or year.
A high customer contact rate is an indicator that your customer experience is confusing and unclear. It also means your agents will be swamped with tickets and may not have enough time to provide quality responses.
A high contact rate might also drive down revenue: a customer support interaction is 4x more likely to drive disloyalty than it is to drive loyalty, according to The Effortless Experience. While you want to make your interactions as helpful as possible, you’re better off giving customers a clear, effortless experience without having to reach out to support in the first place.

You can drive down customer contact rate with clearer self-service resources, like an FAQ page and shipping and returns policies.
Divide the number of customers who contact your customer service team for help over the course of a month by the number of total customers. Then, multiply that number by 100.
Contact rate = (Number of customers who contact you in a month / Total number of customers) x 100

Similar to the CSAT, the NPS is a common metric for measuring customer satisfaction. Customers will rate on a scale from 1 to 10 how likely they are to recommend your business to a friend. It’s best to measure this regularly, so you can determine your company’s benchmark and look for any drops or spikes in the average rating.
You can use a feedback widget on your website to collect this data, or include the quick survey at the bottom of emails for transaction or shipping updates.
To calculate net promoter score, you first need to gather data using a customer survey. Send a survey to customers after they make a purchase that asks them, “On a scale of 0 to 10, how likely are you to recommend [products or service] to a friend or colleague?” On this scale, 0 would be not at all likely, and 10 would be extremely likely.
Customers fall into three categories based on their responses to these surveys: promoters (scores 9 or 10), passives (scores 7 or 8), and detractors (scores 0 to 6). Once you have all the data collected, you can apply the numbers to this formula:
Total % of promoters - total % of detractors = Net promoter score

See our best practices for getting the best NPS response rate.
Conversation abandonment rate is a metric to understand how frequently your customers abruptly end interactions with customer support before reaching a clear resolution.
Whether the conversation is happening via email, chat, or phone call, conversation abandonment signals something larger is wrong. Most conversation abandonment happens after customers wait too long or become frustrated by poor service.
To calculate this metric, all you need to track is the number of abandoned incidents and the total number of incidents. In this context, “incidents” refers to either calls, emails, or live chat sessions. Once you have those two numbers, you can plug them into the following formula:
Conversation abandonment rate = (Number of abandoned incidents / Total number of incidents) x 100

Your average number of unresolved tickets is a very important metric to track because unresolved tickets are a leading indicator of unhappy customers. You don’t want too many unresolved tickets piling up. Set a company-wide goal for the maximum number of unresolved tickets per day, week, and month.
Your unresolved ticket rate includes all abandoned conversations, which you read about in the above section. They also include any tickets where the support team couldn’t provide a real solution, plus tickets that your support team forgot to follow up on.
Similarly to ticket volume, you don’t need a specific formula to calculate your number of unresolved tickets. Rather, all you need is a reliable system (whether it’s a helpdesk or a process) for keeping track of how many tickets are left unresolved after a certain length of time.
Want to know how well your self-service strategy — whether that’s automated chat conversations, self-service chat flows, a blog, or any other self-service resource — lowers customer and agent effort?
You can separate out tickets that did not have a customer support representative work on them, and that were resolved only with automation. You can also track the amount of views your self-service resources get to understand how many tickets they deflect entirely.

Finding your total self-service resolution rate is a bit difficult because you don’t have a ticket to open or close. You can track views on your self-service resources to understand whether they’re being adopted, and track changes to your contact rate to see if they reduce the number of tickets coming in.
Automated support resolution rate is a little easier to calculate:
Automated support resolution rate = Total number of requests resolved with only automation in a single time period divided by the total number of requests resolved with automation, manual support, and a combination of both (in the same time period).
(Solved tickets with automation / total tickets received) x 100 = Resolution rate
Customers’ issues do not only exist in your desired support channels like email and chat. Do you get support tickets on social media? Rather than fight against this trend and attempt to ask customers to submit a ticket via chat, you should respond and help them. Just don’t share sensitive data, of course.
Measure the number of social media support tickets that you get every day, week, month, and quarter. When that number grows, it’s not necessarily a bad thing. It could mean that more of your customers are interacting with your social media profiles. However, it’s still important to pay attention to the benchmark metrics and key performance indicators (KPIs). Sudden changes could represent an issue with your product or shipping speeds.
With Gorgias, you can track and respond to every support ticket that comes through social media — or any channel — from within the helpdesk:

Learn more about Gorgias’ social media customer service features.
Unfortunately, there isn’t a clear-cut way to measure and analyze social media support tickets, so we encourage you to use a social listening tool that allows you to do a number of things. For instance, tracking brand mentions on social media, as well as how many tickets are coming in through your social platforms during various periods of time. Having all of your social metrics in one place will make them much easier to analyze than pulling them one-by-one out of several different spreadsheets.
How frequently your brand is mentioned on social media is a critical metric to track if you want to provide incredible support and get on top of PR disasters. You should have a good benchmark for how often your brand is mentioned per day and per week. If the number spikes, then one of your products might have gone viral, or you’ve got a PR nightmare happening.
You can pay attention to brand mentions with a social listening and brand monitoring software. It’s also smart to use a helpdesk built to manage social comments.
To keep an eye on your social media brand mentions, you’ll need to tap into a social listening tool, as mentioned above. You can certainly try to do this manually and track it all in a spreadsheet, but similar to tracking the volume of tickets, digital software will make this process easier and more efficient.
You might also want to measure the number of tickets closed per agent for a certain time period. For example, you could look at the number of tickets each agent is closing per day to spot differences in productivity. You could look at a longer period of time, such as per month, to find which agents are consistently closing more tickets, assuming they each work the same number of hours.
This will help you discover the agents who deserve praise and bonuses, and which ones might need training. If you find an agent that is always closing too few tickets, it may be time to let them go, unfortunately.
With Gorgias, this metric is automatically tracked in your account:

Plus, you can zoom out to understand trends among agents over time, to compare performance or plan your weekly coverage schedules:

To calculate the number of tickets closed per agent, take the total number of tickets closed during a certain time period and then divide it by the number of agents working during that same time period:
Total # tickets closed / # of agents = Tickets closed per agent
Ticket quality isn’t a metric on its own, but it’s a metric you can create to score your agents’ tickets and work toward a consistent quality of response.
We recommend all customer support teams develop a sort of rubric that defines, in objective terms, what a “good” response looks like. The rubric can include things like:
Your agents will appreciate having concrete goals for their tickets. Plus, you will have an easier time holding agents accountable to standards if they’re written down. You can, and should, regularly update your rubric as you dig into data to understand what ticket qualities actually produce the best results.
As we said, this isn’t exactly a metric to measure. So instead, we’ll recommend that you spot check each agent’s tickets against this rubric. This doesn’t have to be an intimidating process. Some support companies have weekly ticket breakdowns where the entire team — or team leadership, for larger companies — discuss and score tickets against the rubric to get on the same page about ticket quality.
Templated responses save your agents a lot of time and, by extension, mean customers get answers faster. If you don’t have a customer support platform, you can create templated responses in Gmail to answer common questions like, “Where is my order?” (WISMO). If you use helpdesk software, you can also likely add pre-written responses agents can use for each channel. At Gorgias, we call these Macros.

You can get statistics on the utilization of your Macros in any given time period. You can then compare this to the use of tags. For example, if the tag “Cancel Order” was used 100 times in one week, but the Macro was only used 50 times, then that means that your reps only used the Macro half the time.
Talk with your reps about why they’re underutilizing certain Macros. You might need to improve the copy of the Macros or add more variables to make it more useful. Or, you might simply need to remind new reps about the Macros feature.
If you don’t use a helpdesk, you’ll likely have to manually review tickets to see when the template was and wasn’t used. Helpdesk software will automatically report on template utilization.
Your company will always have two types of customers: new customers and repeat customers. Tracking both is important, but tracking repeat customers specifically will help you determine if your retention efforts are working. Repeat customers also have a larger impact on overall revenue: Repeat customers generate 300% more revenue than first-time customers, according to data from Gorgias merchants.

The value of repeat customers is compounded by the fact that retaining a current customer is five times less expensive for a business than finding a brand new customer.
To calculate your repeat customer rate (RCR), you can divide your number of repeat customers by your total number of customers, then multiply that by 100. This means that in order to calculate the RCR properly, you need to already be tracking repeat customers versus new customers. The formula for RCR is as follows:
(Total repeat customers / total paying customers) x 100 = RCR
Using real numbers, here’s an example of what the RCR calculation looks like:
(80 repeat customers / 230 paying customers) x 100 = 34.78%

As mentioned previously, retaining customers is always less expensive than finding new customers. That’s why customer retention rate (CRR) is a vital metric. Ecommerce companies in particular have an average CRR of about 30%, according to Omniconvert, so if your company’s CRR is lower than that, it could be a sign that your customer support isn’t as effective as it could be.
To calculate CRR, you will need the following information: number of customers at the end of a given time period (E), number of customers gained within that time period (N), number of customers at the beginning of the time period (S).
Then, plug those numbers into this formula:
CRR = [(E-N)/S] x 100
Tools like Mixpanel, Qualtrics, and Optimove can also help you automatically track this metric.
Net retention rate, sometimes called net dollar retention (NDR) or net revenue rate, measures the percentage of recurring revenue retained from your existing customers over a month, quarter, or year. Klipfolio reports that a good NRR is anywhere between 90% and 125%, depending on your brand’s niche, product, and total addressable market (TAM).
This metric is most common among SaaS companies and subscription-based ecommerce companies, but it can absolutely apply to all types of ecommerce brands and even other industries.
Net revenue retention depends on your business model — it’s easier to calculate for subscription companies than companies that sell standalone products. That said, here’s the formula for net retention rate:
NRR = [(Monthly recurring revenue (MRR) at the start of a month + expansions + upsells - churn - contractions) / MRR at the start of the month] x 100

Customer churn rate measures the amount of customers your business loses over a given time period.
Customer churn is a more common metric for SaaS businesses and other subscription-based business models because those business models can easily spot the moment when an active customer cancels their subscription, or churns.
However, all businesses, including ecommerce businesses without subscription-based products can track churn rate. But ecommerce businesses might find revenue churn rate, which we discuss below, easier to track.
To calculate customer churn rate calculation, gather the total number of customers who were with your business at the beginning of a time frame and the number of active customers at the end of the time you’re analyzing. Then, use this formula:
[(Customers at the beginning of the time period - customers at the end of the time period) / Customers at the beginning of the time period] x 100 = Customer churn rate (%)
Revenue churn measures changes in your store’s incoming revenue from existing customers. Businesses that sell standalone products might find this more simple to track than customer churn rate, which is better geared toward subscription-based businesses.
Revenue churn rate is easier to conceptualize and measure because you’re measuring changes in revenue from existing customers, which is a clear-cut number for every type of store, not changes in existing customers themselves.
First, find your monthly recurring revenue (MRR) — or the incoming revenue you got from existing customers — at the beginning of the month and subtract that from your MRR at the end of the month. Divide that amount by the total MRR at the beginning of the month. Here’s the formula:
[(Revenue from at the beginning of the time period - revenue from customers at the end of the time period) / Customers at the beginning of the time period] x 100 = Churn rate (%)
The number of support tickets your customer support team converts into a purchase shows the value of your customer support team in cold, hard cash. We count a ticket as converted whenever a customer places an order within five days of contacting customer support.
Customer support agents can provide helpful pre-sales answers to new customers asking about things like product sizing or your returns policy. Likewise, a helpful interaction after a purchase could make a customer feel confident and loyal enough to place a repeat purchase.
With Gorgias, you can measure your converted tickets and other revenue statistics in a convenient dashboard. Converted tickets can be from self-service, or automated, and manual responses.

Before you start calculating, make sure that both numbers are from the same time period. Then use this simple formula to calculate your converted tickets:
Total number of sales within five days of a customer support interaction / total number of tickets = Ticket conversion rate
Read more about how to optimize your conversion rate (CRO).
Revenue backlog helps you measure how much revenue your business will see in a coming period. This metric is especially for ecommerce brands with a subscription-based model.
Keeping tabs on your revenue is vital to ensuring your brand's growth and continued success. By tracking your revenue backlog, you’ll be able to see if revenue is going to drop before it actually does.
To determine your revenue backlog, you’ll just need the sum of the values of your customers’ subscriptions. If you don’t exclusively sell subscription packages, you’ll need to use tools like Dataweave or Y42 to measure upcoming revenue.
Happy customers are the best fuel for growth. In other words, the performance of your customer support team (and overall customer experience) directly impacts your bottom line. Customer service metrics help you understand — and improve — the value that customer service brings to your business.

90% of American consumers say that customer service is a deciding factor in whether or not they will do business with a company. Potential customers might ask a question about delivery or the product before making a purchase. And shoppers depend on quality support experiences after the purchase for a great end-to-end experience. If you flub that chance, they may never come back.
Existing customers are also your biggest spenders, and they rely on quality customer support to stay loyal. According to Gorgias research, repeat customers generate 300% more revenue than first-time customers of ecommerce brands. We estimate that by increasing your repeat customer base by 20%, you could increase your revenue up to 6%.
Customer experience is mission-critical — see above for its impact on your revenue — but it isn’t easy to measure. That’s because it encapsulates your on-site shopping experience, customer support interactions across many channels, post-purchase interactions like shipping and returns, and so much more.
Customer support metrics help you evaluate your support program and the customer experience across all those touchpoints so you can benchmark your team’s performance, communicate your performance with company leaders, and find opportunities for improvement.
As we just mentioned, tracking a full suite of customer support metrics can also help you find specific areas of improvement. If you don’t keep track of many customer support metrics, you’ll only have extremely high-level impressions and small samples of customer feedback to paint a picture of your strengths and weaknesses.
But if you have real-time tracking for a wide range of metrics, you can better diagnose the problem and find a strategic solution. For example:
Concrete metrics are great ammunition for your customer service team when making the case to business leaders for more budget to hire additional agents, purchase additional tools, and ramp up training.
To argue for more investment, you can communicate which projects have produced early improvements. For example, if you set up an FAQ page and see lower contact rates, you can expand the page to a fully-fledged help center.
You can also quantify challenges to make a case for more tools. For example, say your agents often ask customers to repeat information or lose time copy/pasting order information from your ecommerce platform to customer support conversations. You could make the case a helpdesk that unifies all your customer support channels and store data in one platform.
Likewise, metrics can help you forecast your customer service staffing needs and proactively hire customer service agents before it’s too late.
Now that you have all the important customer service metrics and formulas to support your customer success program, you may be ready to explore a product to help make tracking it all easier. A centralized customer service software like Gorgias can help save you and your team hours upon hours of time. That time you can spend getting back to what you do best: great customer support.

The Gorgias platform connects all of your integrations and allows for robust analytics tracking, so you can:
If you’re on a mission to measure how your customer service team performs (and stacks up against the rest of your industry), check out our benchmark report.
If you want to improve your metrics with the ecommerce platform custom-built for ecommerce customer service teams, book a demo with us or try Gorgias for free today.
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As you hire more customer service agents, providing quality support across the entire team becomes a major challenge. Without clear rules, agents may each handle key tasks — like building self-service resources or handling refund requests — in different ways.
Fortunately, a good customer service policy helps avoid these problems. But to be truly effective, your policy needs more than platitudes like “Be friendly” or “Respond quickly.” Instead, it should include specific and actionable information.
In this guide, we’ll help you create a useful customer service policy by sharing the five key topics it needs to cover. We’ll also discuss how to write and enforce your policy.
First, let’s start with the basics. Or, you can skip straight to the advice for writing a useful policy.
A customer service policy is a document containing a set of guidelines, rules, and standards for customer service teams. Its goal is to help agents handle day-to-day tasks and set benchmarks for great customer service.
Customer service policies are among the first documents provided to new agents during their training. They act as cornerstone documents for a business's entire customer service team, since agents can use them during difficult or process-heavy interactions, like customer complaints, order cancellations, and so on.
A customer service policy is an internal document, so you won’t share it publicly. However, you can use it as a foundation and repurpose parts of it into various customer-facing policies (like cancellation or refund policies). These policies help you set customer expectations and reduce repetitive inquiries like "What's your return policy?"
Take a look at how Marine Layer does this in a concise way:

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

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

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

Here are three prioritization factors to include in your policy:

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

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


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

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

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

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

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

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

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

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

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

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

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

TL;DR:
Ecommerce merchandising is the strategic presentation of products to drive sales and create better shopping experiences.
With online shopping more competitive than ever, how you showcase products can make or break a sale.
This guide shows you how to optimize product discovery, improve the customer experience, and boost revenue.
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Ecommerce merchandising is the practice of strategically presenting products to drive sales and improve the shopping experience.
Think about a physical store. Products aren't randomly thrown on shelves — merchandisers place bestsellers at eye level, create enticing displays, and use signage to grab attention. Ecommerce merchandising works the same way, just digitally.
The goal is to put the right product in front of the right customer at the right time. The advantage? You can optimize in real-time based on customer behavior, purchase history, and browsing patterns — something brick-and-mortar stores can't easily do.
This includes organizing your product catalog, optimizing search and filters, creating compelling visuals, personalizing recommendations, and fine-tuning your product pages to convert browsers into buyers.
Merchandising directly affects your revenue because it influences every step of the customer journey from product discovery to checkout. Here's why it should be a top priority:
Your customers expect personalization. They don't want to dig through generic product pages or wrestle with basic search. They expect experiences that adapt to their preferences and recommendations that feel hand-picked. If your site feels one-size-fits-all, you're already behind.
Your competition isn't just down the street. It's everywhere. Customers can comparison shop across dozens of stores in minutes. If they can't quickly find what they want on your site, they'll bounce to a competitor who makes it easier. You're not just competing locally anymore. You're up against every online retailer worldwide.
You have data physical stores can only dream of. You can test product arrangements, track which layouts convert better, and adjust your strategy in real-time based on actual behavior. That's a massive advantage, but only if you use it.
Effective merchandising has four foundational building blocks. Here's what you need:
Building an effective merchandising strategy requires a systematic approach, not guesswork. Follow these five steps.
Review your catalog organization, search performance, and conversion data. Identify which products are easy to find and which are buried. Check search analytics to see where customers struggle and where they drop off. This baseline shows you where to focus.
Establish what success looks like. Choose 3-5 key metrics—conversion rate, average order value, search exit rate—that align with your business objectives. Clear KPIs let you measure impact and prove ROI.
Identify key touchpoints: homepage, category pages, search, product pages, checkout. Understanding this flow helps you prioritize which areas to optimize first and where merchandising has the biggest impact.
Start with high-impact, low-effort improvements like fixing broken search, adding recommendations, or streamlining category navigation. Quick wins build momentum and show stakeholders what's possible.
Set up a testing framework with regular analytics reviews, A/B testing processes, and customer feedback channels. Merchandising isn't one-and-done. It requires continuous refinement.
These are the foundational must-haves for any ecommerce store:
✅ Optimize your search functionality – Implement autocomplete, synonym mapping, and smart filters so high-intent shoppers can actually find what they're looking for.
✅ Use high-quality product media – Include multiple angles, zoom functionality, videos, and lifestyle shots. Customers can't touch products online—visuals bridge that gap.
✅ Display social proof prominently – Add reviews, ratings, customer photos, and trust badges on product pages. Customers trust other customers more than your marketing copy.
✅ Ensure mobile responsiveness – Make sure you have responsive design, touch-friendly navigation, and fast loading. 61% of searches happen on mobile.
✅ Show real-time inventory – Display accurate stock levels and low-stock alerts. Nothing kills trust faster than letting customers buy unavailable products.
✅ Optimize checkout flow – Offer guest checkout, multiple payment options, transparent pricing, and progress indicators. Every friction point increases abandonment.
✅ Track Core Web Vitals – Monitor LCP, INP, and CLS. Aim for sub-3-second page loads. Slow pages kill conversions.
Track these six KPIs to understand how your merchandising impacts revenue. Metrics turn opinions into data-driven decisions.
The percentage of visitors who buy something. This is your most direct measure of merchandising success.
Example: If 100 people visit your site and 3 buy, your conversion rate is 3%. Track this by traffic source, device, and product category to spot where you can improve.
The average dollar amount customers spend per transaction. Growing AOV through bundles and recommendations increases revenue without needing more traffic.
Example: If you make $5,000 from 100 orders, your AOV is $50. If product recommendations bump that to $55, you've added $500 in revenue from the same number of customers.
Total revenue divided by total visitors. This combines conversion rate and AOV into one number that shows overall merchandising effectiveness.
Example: 1,000 visitors generate $3,000 in sales = $3 RPV. If your merchandising gets that to $3.50, you've gained $500 per thousand visitors.
The percentage of people who leave after viewing just one page. High bounce rates mean navigation problems or customers not finding what they expected.
Example: If 60% of homepage visitors bounce immediately, something's wrong. It could be unclear navigation, slow loading, or irrelevant content.
The percentage of customers who search and then leave without clicking any products. This directly measures search quality.
Example: If 40% of people search for "running shoes" and then exit, your search isn't showing them relevant results. Fix this by improving synonym coverage and result relevance.
Total revenue a customer generates over their entire relationship with your brand. Good merchandising makes repeat purchases easy through personalization and seamless experiences.
Example: A customer makes their first $50 purchase, then returns for three more $40 purchases over two years. Their CLV is $170—much more valuable than a one-time buyer.
Testing and optimization approach:
Pro Tip: Your support team sees patterns that metrics can't capture. Combine quantitative data with qualitative feedback from customer conversations. Pre-sales customer support can go a long way toward boosting sales by assisting customers with issues that might otherwise prevent them from converting.
Once your foundation is solid, these tactics drive growth. Use them to differentiate your store and boost conversions beyond the basics.
Show "Because you bought X" recommendations, tailor homepages by customer segment, and use dynamic content based on browsing history.
Guide uncertain shoppers with quizzes that recommend products based on their needs and preferences.
Create thematic collections ("Summer Essentials," "Work From Home Setup") that reduce decision fatigue and inspire purchases.
Use product bundles, tiered discounts, and free shipping thresholds to increase average order value without constant discounting.
Trigger automated chats based on behavior like reaching out when someone views high-value products or lingers on checkout.
Let customers "try on" products virtually or see 360-degree views to boost confidence and reduce returns.
Extend your merchandising to Instagram, TikTok, and other platforms where customers already shop.
Use machine learning to adjust product rankings, predict demand trends, and personalize at scale.
Organizing your store and displaying products to customers is just one element of creating a customer experience optimized for revenue generation.
Gorgias extends your merchandising strategy through three key capabilities:
AI Agent answers product questions instantly, provides recommendations, and handles order inquiries without human agents.
Customer data integration means agents see browsing history, cart contents, and past purchases to make personalized suggestions during support conversations.
Proactive engagement through chat campaigns can re-engage cart abandoners or offer help at key decision points in the customer journey.
When merchandising and support work together, you reduce pre-purchase support inquiries because product pages answer common questions. You turn support conversations into sales opportunities by equipping agents with context and product knowledge.
See how Gorgias helps ecommerce brands turn support into a revenue driver. Book a demo.
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