TL;DR
At Gorgias, we work with over 16,000 ecommerce brands and one common challenge emerges over and over:
Ecommerce tools are essential, but too many tools becomes a burden.
With different teams responsible for different functions, brands risk creating a disconnected tech stack that causes inefficiencies, reduces productivity, and ultimately impacts profitability.
Ecommerce teams are shuffling between tabs, copying and pasting order numbers, searching for customer data, and trying to piece it all together. It’s not only inefficient—it’s expensive, frustrating, and unsustainable as you scale.
So we dug into that data.
Our 2025 Ecommerce Trends Report surveyed ecommerce professionals across industries and job roles to understand what they really think about tech stacks and AI’s role in it.
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There is now an ecommerce app for every possible use case a brand could need. But as businesses adopt new technologies for each part of their customer journey, their teams end up working out of dozens of platforms.
The study found that 42.28% of ecommerce pros use at least six apps daily to perform their role. Regardless of the number of apps used, integration and compatibility are a must. When technologies don’t talk to each other, you spend time context-switching instead of focusing on customer experience.
For Audien Hearing, Gorgias’s open API allowed them to create an integration with its warehouse software to manage returns directly in Gorgias rather than a shared Google spreadsheet. This integration helped them reduce returns by 5%, protecting their margins and leading to higher customer satisfaction.
Read more: How Audien Hearing Increased Efficiency for 75 Agents and Reduced Product Returns by 5%
The most successful ecommerce brands aren’t necessarily using more tools—they’re using smarter tools. Leading businesses are opting for platforms that are deeply integrated, AI-compatible, and built specifically for ecommerce needs.
A growing tech stack also comes with a growing tech budget. Each new app has new costs, including subscriptions, set-up, management, and development fees. They quickly add up.
Nearly 40% of ecommerce professionals spend $5,000 to $50,000 annually on their tech stack.
We asked ecommerce professionals what they actually value in their tools. Unsurprisingly, the answer changed based on who we were talking to.
Top tool benefits included:
There’s a clear difference between what ecommerce leaders and agents value in a tool and considering both is key to success.
Despite the benefits of using fewer, well-integrated tools, there are a few things that hold brands back from consolidating their tech stacks.
We asked respondents:
What, if any, are the biggest deterrents to consolidating your tech stack?
Top concerns are:
AI is dominating the world of ecommerce. It impacts every aspect of the customer journey, from brand discovery to the post-purchase experience. AI is actively reshaping the way ecommerce professionals work, so we wanted to know how they feel about it.
Despite growing usage and excitement, teams still have their concerns with AI:
Read more: 8 AI Trends in Ecommerce: What’s Changing and How to Prepare
The most impactful use cases we’ve seen aren’t just about reducing support ticket volume. AI is now driving revenue, increasing conversion rates, and enabling 24/7 coverage without expanding headcount.
Gorgias’s AI Agent is now capable of virtual sales assistance through personalized product recommendations, dynamic discounts to reduce cart abandonment, and cross-sells and upsells.
Top brands are already leveraging these new capabilities and seeing results. For example:
We asked one final question to make ecommerce folks really reflect on how they work:
How many tabs do you currently have open?
The average ecommerce professional works with 22 open tabs. We’re not here to judge, but if you’re looking to close a few of those tabs, Gorgias might be what you’re missing.
Gorgias replaces all that complexity with a single workspace. From support to sales, order management to automation, it all happens inside one platform.
Ecommerce businesses can now leverage Gorgias’s Advanced AI for both support and sales. Within the same AI Agent, ecommerce brands can
This blog just skims the surface of what we uncover in our 2025 Ecommerce Trends report.
Want the full story?
Download the complete 2025 Ecommerce Trends: AI Adoption & Smarter Tech Stacks report to access:
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TL;DR:
When customer service teams are at their busiest, they need a helpdesk that keeps up. That’s exactly why our Site Reliability Engineering (SRE) team has been working behind the scenes to make the Gorgias platform faster than ever.
Over the past year, we've made remarkable improvements to our platform to eliminate bottlenecks, speed up data retrieval, and reduce incidents. For you, this means fewer disruptions, faster load times, and a more reliable helpdesk experience.
Here's how we did it.
Our platform relied on a single, shared database connection pool to manage all queries. Think of it as having just one pipe handling all the water flowing through your house — when too much water rushes in at once, the whole system backs up.
In practice, this meant a single surge in database requests could clog the entire system. When lower-priority background tasks got stuck, they could prevent high-priority operations (like loading tickets or running automations) from working properly. This would cause the entire helpdesk to slow down or, worse, become completely unresponsive.
Using PgBouncer, a tool that manages database connections and reduces the load on a server, we implemented multiple connection pools. Instead of relying on a single pipeline to stream all requests, we created separate "pipes" for different requests.
Like how road traffic picks up again after an exit, routing our database traffic into separate connection pools makes sure high-priority customer interactions don’t lag behind automated background tasks.
This solution is future-proof. In the event that a lower-priority task is delayed in one connection pool, other functionalities of the helpdesk will continue working because of the remaining connection pools.
The results speak for themselves:
We've eliminated incidents caused by connection pool issues in the helpdesk completely. This reduced major helpdesk outage incidents by around four per year and maintained an average uptime of over 99.99%.
As Gorgias grew to over 15,000 customers, so did the volume of data. We’re talking data from tickets, integrations, automations, and many more. The combination of more users and data meant slower searches within the helpdesk.
However, the amount of data was not the problem — it was how our data was organized.
Imagine this: An enormous storage room full of file cabinets containing every piece of data. Sure, those file cabinets kept data organized, but you would still need to spend time searching through the entire room, running up and down aisles of cabinets, to find your desired file. This method was cumbersome.
We needed a more efficient way to keep our data easy to find, especially as more customers used our platform.
The answer was database partitioning — breaking our large datasets into smaller, more manageable segments. Using Debezium, Kafka, and Kafka-connect JDBC, all managed by Terraform, we migrated over 40TB of data, including 3.5 billion tickets, without a moment of downtime for our merchants.
Instead of a giant room with thousands of file cabinets, we divided that giant room into 128 smaller rooms. So now, instead of looking for a file in one room, you know you just need to go into room number 102, which has a much smaller area to search.
This approach allows our system to quickly pinpoint the location of data, significantly reducing the time it takes to find and deliver information to users.
Additionally, database maintenance has become more efficient. Some of the partitions can probably sit without needing to be changed at all. We just have to maintain the partitions that are getting new files, which cuts down on maintenance time.
Better database partitioning provides several benefits:
When incidents occurred in the past, our response process was inconsistent, leading to delays in resolution. It was sometimes unclear who should take the lead, what immediate actions were required, and how to effectively communicate with affected customers.
Additionally, post-incident reviews varied in quality, making it difficult to prevent similar issues from happening again. We needed a standardized framework to address incidents in a timely fashion.
To streamline incident management, we introduced a replicable, automated process:
With our improved incident management process:
With more brands catching on to how essential a solid CX platform is, our team's got our work cut out for us. Here's what's on the way:
Gorgias will inevitably face new challenges in performance — no system is completely immune to downtime.
But we've built our architecture with the future in mind, and it’s more resilient than ever as more and more brands realize the power of conversational AI CX platforms.
The result? A platform you can count on to help you deliver exceptional customer service, without technical issues getting in the way.
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TL;DR:
AI is no longer a futuristic concept associated with sci-fi movies and robots. It’s driving real change in ecommerce right now. Currently, 84% of ecommerce businesses list AI as their top priority. And it’s only getting bigger. By 2034, the ecommerce AI market is expected to hit $62.64 billion.
Brands that use AI to improve personalization, automate customer support, and refine pricing strategies will have a major competitive edge.
The good news? Most brands are still figuring it out, which means there’s huge potential for early adopters to stand out.
Let’s dive into the key AI trends shaping ecommerce in 2025, and how you can use them to future-proof your business.
Instead of searching for keywords, shoppers can upload a photo and instantly find similar or matching products. Visual search eliminates the guesswork of finding the right words to describe an item and reduces friction in the search process.
In 2025, improvements in computer vision and machine learning will make visual search faster. AI will better recognize patterns, colors, and textures, delivering more precise results in real-time.
For customers, visual search simplifies product discovery while brands benefit from increased average order values. Visual search creates more opportunities to surface related products that customers might miss during manual searches, ultimately boosting conversion and revenue.
Pinterest is already doing it. With Pinterest Lens, users can take a picture on the spot to find similar products or ideas to help them with easier purchases or creative projects.
Pro Tip: Optimize product images and metadata (like color, size, and material) so your products appear accurately in visual search results. Clean, high-quality images and detailed tagging will make your catalog easier for AI to process and match.
Conversational AI, like Gorgias’s AI Agent, already handles 60% of customer conversations. Brands that adopt it often see more than a 25% improvement in customer satisfaction, revenue, or cost reduction.
Soon, advanced natural language processing (NLP) will make it easier for customers to use text, voice, and images to find exactly what they’re looking for. These multimodal capabilities will elevate support conversations, resulting in fewer abandoned carts and support teams that can focus on more complex issues.
For example, Glamnetic uses AI Agent to manage customer inquiries across multiple channels, resolving 40% of requests automatically while maintaining a personalized touch. Their AI can automate responses to common questions, recommend products based on browsing history, and even track orders in real-time.
Pro Tip: Invest in AI chat tools that integrate with your customer support system and sync with real-time product and order data. Your responses will be accurate and timely, without losing the personal touch.
Read more: The Gorgias & Shopify integration: 8 features your support team will love
According to McKinsey, omnichannel personalization strategies, including tailored product recommendations, have a 10-15% uplift potential in revenue and retention. But with only 1 in 10 retailers fully implementing personalization across channels, there’s a massive opportunity for brands to innovate.
In 2025, AI-driven product recommendations will become even more precise by analyzing customer behavior, preferences, and purchase history in real-time. Predictive AI will adjust recommendations on the fly, showing customers the right products at the right moment.
Take Kreyol Essence as an example. They use Gorgias Convert to track customer behavior and recommend products based on past purchases and browsing patterns. When a customer buys a hair mask, AI suggests complementary products like scalp oil or leave-in conditioner — increasing average order value without feeling pushy.
Personalization boosts sales by helping customers discover products they actually want. Plus, it creates a more tailored shopping experience, which encourages customers to return.
Pro Tip: Test different recommendation strategies, like “frequently bought together” or “you may also like,” to see which ones drive the most conversions.
Learn more: Reduce Customer Effort with AI: A Smarter Approach Than Surprise and Delight
In 2025, more customers may use smart speakers and voice assistants like Alexa and Google Assistant to shop hands-free. AI will improve voice recognition and contextual understanding, so it’s easier for customers to find products they want.
Instead of fumbling with a keyboard, customers will be able to say, “Order more coffee pods,” and AI will not only recognize the request but also pull up the preferred brand and size based on past orders. Less friction will make the buying process more intuitive, especially for repeat purchases.
Voice commerce expands shopping accessibility and creates a more convenient experience for busy customers. It also opens the door for brands to surface product recommendations and upsell during the conversation.
Pro Tip: Optimize product descriptions and catalog structure for voice search. Clear, simple language and detailed product tags will help AI understand and surface the right products.
A recent McKinsey report suggests that investing in real-time customer analytics will continue to be key to adjusting pricing and more effectively targeting customers.
In 2025, machine learning will allow ecommerce brands to adjust product prices instantly based on demand, competitor pricing, and customer behavior. If a competitor drops their price on a popular item, AI can respond immediately, so you stay competitive without sacrificing margins.
Machine learning will also refine pricing models over time, finding the sweet spot between profitability and customer conversion.
For example, AI might detect that customers are more likely to buy a product when it’s priced at $29.99 rather than $30, and adjust accordingly. More competitive pricing means higher revenue and better margins, but it also increases customer trust when prices are consistent with market trends.
Pro Tip: Test different pricing strategies and monitor how they affect sales and customer behavior.
According to McKinsey, AI-driven personalization and customer insights can improve marketing efficiency by 10-30% and cut costs significantly.
In 2025, AI will analyze customer data like purchase history, browsing patterns, and feedback to generate smarter, more actionable next steps. Instead of guessing what customers want, brands will have the data to predict it.
For example, Gorgias’s AI Agent for Sales can identify a shopper’s interest level and purchase intent and then use it to adjust its conversational strategy. It analyzes shopper data like browsing behavior, cart activity, and purchase history.
Here’s how it would behave for different customers:
AI-driven personalization leads to a 5-10% higher customer satisfaction and engagement. Yet, only 15% have fully implemented it across all channels — leaving a huge gap to fill.
In 2025, AI-driven personalization will go beyond product recommendations. Brands will be able to adjust website layouts based on customer preferences, highlight products that align with their style, and even customize customer service interactions.
A higher level of personalization will boost conversion rates and customer satisfaction. When customers feel like a brand “gets” them, they’re more likely to make a purchase and come back for more.
For example, AI Agent for Sales can adjust discounts and provide smart incentives to drive sales. When adjusting for discounts, AI Agent analyzes shopper behavior, including browsing activity, cart status, and conversation context, to offer a discount based on how engaged and ready the shopper is to buy.
Pro Tip: Use AI to test different personalization strategies and refine them based on performance data. Small adjustments, like changing product order or highlighting specific categories, can have a big impact on sales.
Keeping the right products in stock at the right time is about to get a whole lot easier. In 2025, AI will predict demand patterns and automate restocking decisions based on sales trends, seasonality, and customer behavior. Instead of manually tracking inventory, AI will handle it in real time to avoid stock issues.
For example, AI could notice a spike in orders for a specific product right before the holidays. It could then automatically increase stock levels to meet demand or scale back on items that aren’t moving as fast. Real-time tracking means fewer missed sales and less wasted inventory.
Efficient inventory management not only cuts costs but also improves the customer experience. When products are consistently available, customers are more likely to trust and stick with your brand.
Pro Tip: Implement AI-powered inventory management to sync data across all sales channels. This ensures accurate stock levels and seamless fulfillment, whether customers are shopping online or in-store.
AI makes it easier for brands to deliver a personalized and efficient shopping experience. From helping customers find products faster with visual search to automating support with conversational AI, there are plenty of opportunities for personalization.
The brands that adopt and refine these strategies now will be better positioned to meet customer expectations and stay ahead of the competition. Start by implementing conversational AI and later test some other AI trends like personalized suggestions.
Ready to see how AI can upgrade your brand? Book a demo to see AI Agent in action.
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TL;DR:
Chargebacks are more than a thorn in a merchant’s side — they’re a growing financial and operational threat. According to Ethoca, chargebacks are projected to more than double, from $7.2 billion in 2019 to $15.3 billion by 2026 in the U.S. alone. And while fraud plays a role, the primary reason customers file chargebacks is simpler: they feel ignored.
At Chargeflow, we recently published a comprehensive report analyzing why customers dispute chargebacks. The findings were eye-opening. While it’s true that fraud is a real concern, most chargebacks happen for a different reason: a lack of communication between merchants and customers.
Top stats from Chargeflow’s report:
When customers feel ignored or frustrated, they often turn to their bank for a solution instead of reaching out to the merchant first. Understanding these behaviors is key to preventing disputes before they escalate and cause chaos.
So, what actually drives customers to dispute charges? Here’s what the data says.
While chargebacks are often the cost of doing business, the truth is that many disputes are preventable — but only if merchants understand the root causes. We identified five key drivers behind chargebacks.
According to our research, most customers file a dispute right away after encountering an issue, leaving no opportunity to resolve the problem. Another 38% file within one to three days if they don’t receive a timely response.
Why? Customers assume the fastest way to get their money back is by filing a chargeback, especially if they receive no response from the merchant.
We found that 80% of customers never receive a follow-up after filing a chargeback. Additionally, 64% of customers state immediate communication is crucial, yet many businesses fail to reach out.
Why? Customers expect businesses to be proactive. When they don’t hear back quickly, they assume the merchant won’t help, making a chargeback seem like the best option.
98% of customers report a neutral to highly satisfactory experience when filing chargebacks, and only 12% are denied.
Why? Many customers believe chargebacks are faster and easier than dealing with merchants directly, especially if return policies are unclear.
The most common reason for filing a chargeback is “product not received” (35% of the cases). Other common reasons included:
Why? When customers don’t receive clear shipping updates or experience delivery delays, they assume their order won’t arrive and file a chargeback rather than waiting.
Friendly fraud occurs when a cardholder makes a legitimate purchase but later disputes the charge as fraudulent or unauthorized, leading their card issuer to reverse the payment.
Our research found that:
According to our State of Chargebacks report, 79% of chargebacks are actually friendly fraud, meaning they were filed for invalid reasons.
Why? Many customers mistakenly believe that a chargeback is just another way to request a refund, rather than a process intended for fraud or merchant failure.
📌 The takeaway: Most chargebacks aren’t actual fraud, but rather a result of customer confusion, impatience, or poor communication from merchants.
Merchants who want to stop chargebacks before they happen need a two-part strategy:
Chargebacks result from slow response times, poor communication, and unresolved issues, not fraud. Adopting AI-driven customer support and chargeback automation allows businesses to significantly reduce disputes and retain more revenue.
Many chargebacks happen because customers don’t receive a fast enough response. In fact, 52% say they will dispute a charge if the response time is too slow. AI-powered chatbots provide real-time support, resolving issues before they escalate.
Customers expect updates regarding orders and refunds, but often don’t receive them. 80% of customers report never hearing from a merchant after filing a chargeback.
Automated order updates, refund confirmations, and proactive notifications keep customers informed, reducing unnecessary disputes.
Customers expect round-the-clock support, but most businesses can’t provide live assistance. AI-powered ticketing and automation ensure every customer receives help, regardless of the time zone or urgency.
The result? Fewer chargebacks, faster resolutions, and increased customer satisfaction.
It’s impossible to please every customer. On average, chargebacks take 50 days to resolve successfully. Focus your energy on retaining high-value, long-term customers.
Lost inquiries take on average 15 days to resolve, and lost chargebacks take 38 days. Prioritize cases based on impact.
Advanced automated ticketing systems can route inquiries and prioritize urgent cases.
Ensure customer service teams have quick-response templates to speed their resolutions.
“Product not received” was the most cited reason for delivery-related chargebacks. Work closely with carriers and third-party suppliers to improve fulfillment and reduce disputes.
Use automated tools for real-time analytics, enhanced communication, and proactive alerts, which will reduce response times.
Successfully tackling chargebacks requires both proactive customer support and automated dispute management. That’s why Gorgias and Chargeflow work so well together to give merchants a comprehensive defense against disputes.
Post-purchase automation isn’t just about reducing customer support workload or quick replies. It's about finding the most effective ways to increase customer loyalty and prevent disputes.
Learn more about how AI-driven automation enhances post-purchase experiences here.
As you know, chargebacks are costly, frustrating, but most importantly, preventable. Our research shows that most chargebacks don’t stem from fraud, but from poor communication, slow response times, and customer uncertainty.
By prioritizing fast, AI-driven customer support and automated chargeback management, merchants can resolve issues before they escalate, improve customer experience, and protect their revenue.
With Gorgias handling proactive customer support and Chargeflow managing chargeback disputes, merchants get a powerful, end-to-end prevention system that ensures fewer chargebacks, higher dispute win rates, and, at the end of the day, happier customers.
Don’t let chargebacks drain your revenue. Take control today with faster, smarter automation.
Download Chargeflow’s full Psychology of Chargebacks Report to dive deeper into the data and start preventing disputes before they happen.
TL;DR:
Shoppers aren’t just open to AI — they’re starting to expect it.
According to IBM, 3 in 5 consumers want to use AI as they shop. And a McKinsey study found that 71% expect personalized experiences from the brands they buy from. When they don’t get that? Two-thirds say they’re frustrated.
But while most brands associate AI with support automation, its real power lies in something bigger: scaling personalization across the entire customer journey.
We’ll show you how to do that in this article.
Before AI can personalize emails, recommend products, or answer support tickets, it needs one thing: good data.
That’s why one of the best places to start using AI isn’t in sales or support — but in enriching your customer data. With a deeper understanding of who your customers are, what they want, and how they behave, AI becomes a personalization engine across your entire business.
Post-purchase surveys are gold mines for understanding customers — but digging through the data manually? Not so fun.
AI can help by analyzing survey responses at scale, identifying trends, and categorizing open-ended customer feedback into clear, actionable insights. Instead of skimming thousands of answers to spot what customers are saying about your shipping times, AI can surface those insights instantly — along with sentiment and behavior signals you might’ve missed.
Try this prompt when doing this: "Analyze 500 open-ended post-purchase survey responses. Identify the top 5 recurring themes, categorize customer sentiment (positive, neutral, negative), and surface any trends related to product quality, delivery experience, or customer support."
One of AI’s biggest strengths? Spotting intent.
By analyzing things like page views, cart activity, scroll behavior, and previous purchases, AI can identify which shoppers are ready to buy, which ones are likely to churn, and which just need a little nudge to move forward.
This doesn’t just apply to email and retargeting. It also works on live chat, in real time.
Take TUSHY, for example.
To eliminate friction in the buying journey, TUSHY introduced AI Agent for Sales — a virtual assistant designed to guide shoppers toward the right product before they drop off.
Instead of letting potential customers bounce with unanswered questions, the AI Agent steps in to offer:
With a growing product catalog, TUSHY realized first-time buyers were overwhelmed with options — and needed help choosing what would work best for their home and hygiene preferences.
“What amazed us most is that the AI Agent doesn’t just help customers choose the perfect bidet for their booty — it also provides measurement and fit guidance, high-level installation support, and even recommends all the necessary spare parts for skirted toilet installations. It’s ushering in a new era of customer service — one that’s immediate, informative, and confidence-boosting as people rethink their bathroom habits.”
—Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY
AI also helps you see the road ahead.
Instead of looking at retention and loyalty metrics in isolation, AI can help you forecast what’s likely to happen next and where to focus your attention.
By segmenting customers based on behaviors like average order value, order frequency, and churn risk, AI can identify revenue opportunities and weak spots before they impact your bottom line.
All you need is the right prompt. Here’s an example you can run using your own data in any AI tool:
Prompt: “Analyze my customer data to forecast revenue by segment. Break customers into at least three groups based on behavior patterns like average order value, purchase frequency, and churn risk.
For each segment, provide:
Here’s what a result might look like:
Instead of flying blind, you’re making decisions with clarity — and backing them with data that scales.
When used strategically, AI becomes a proactive sales agent that can identify opportunities in real-time: recommending the right product to the right shopper at the right moment.
Here’s how ecommerce brands are using AI to drive revenue across every part of the funnel.
Your prices shouldn’t be static — especially when your competitors, inventory, and customer behavior are anything but.
AI-powered pricing tools like AI Agent for Sales help brands automatically adjust pricing based on shopper behavior. The goal is to make the right offer to the right customer.
For example:
With dynamic pricing, you can protect your margins and boost conversions — without relying on blanket sales.
AI-powered chat is no longer just a glorified FAQ. Today, it can act as a real-time shopping assistant — guiding customers, boosting conversions, and helping your team reclaim time.
That’s exactly what Pepper did with “Penelope,” their AI Agent built on Gorgias.
With a rapidly growing product catalog (22 new SKUs in 2024 alone), Pepper knew shoppers needed help discovering the right products. Customers often had questions about styles, materials, or sizing, and if they didn’t get answers right away, they’d abandon carts and move on.
Instead of hiring more agents to keep up, Pepper deployed Penelope to live chat and email.
Her job?
“With AI Agent, we’re not just putting information in our customer’s hands; we’re putting bras in their hands... We’re turning customer support from a cost center to a revenue generator.”
—Gabrielle McWhirter, CX Operations Lead at Pepper
Let’s look at how Penelope performs on the floor:
A shopper asked about the difference between two wire-free bras. Penelope broke down the styles, support level, and fabric in plain language — then followed up with personalized suggestions based on the shopper’s preferences.
Using Gorgias Convert chat campaigns, Pepper triggers targeted messages to shoppers based on behavior. If someone is browsing white bras? Penelope jumps in and offers assistance, often leading to faster decisions and fewer abandoned carts.
If a customer adds a swimsuit top to their cart, Penelope suggests matching bottoms. No full-screen popups, no awkward sales scripts — just thoughtful, helpful guidance.
Penelope also handles WISMO tickets and return inquiries. If a shopper is dealing with a sizing issue, Penelope walks them through the return process and links to Pepper’s Fit Guide to make sure the next purchase is spot on.
By implementing AI into chat, Pepper saw a 19% conversion rate from AI-assisted chats, an 18% uplift in AOV, and a 92.1% decrease in resolution time.
With Penelope handling repetitive and revenue-driving tasks, Pepper’s team now has more time to offer truly personalized touches — like virtual fit sessions that have turned refunds into exchanges and even upsells.
Bundling is a proven tactic for increasing AOV — but most brands still rely on subjective judgment calls or static reports to decide which products to group.
AI can take this a step further.
Instead of just looking at what’s bought together in the same cart, AI can analyze purchase sequences. For example, what people tend to buy as a follow-up 30 days after their first order. This gives you powerful clues into natural buying behavior and bundling opportunities you might’ve missed.
If you’re looking to explore this at scale, you can use anonymized sales data and feed it into AI tools to surface patterns in:
Try this prompt:
"Analyze this spreadsheet of order data and identify product bundle opportunities. Look for: (1) products frequently purchased together in the same order, (2) items commonly bought as a second purchase within 30 days of the first, and (3) patterns in high-value or high-frequency product pairings. Provide insights on the most promising bundles and why they might work well together."
Just make sure you’re keeping customer data anonymous — and always double-check the insights with your team.
Related: Ecommerce product categorization: How to organize your products
AI isn’t just here to deflect tickets. From quality assurance to proactive outreach, AI can elevate the entire support experience — on both sides of the conversation.
Manual QA is slow, selective, and often feels like it’s chasing the wrong tickets.
That’s where Auto QA comes in. Instead of reviewing just a handful of conversations each week, Auto QA evaluates 100% of private messages, whether they’re handled by a human or an AI agent.
Every message is scored on key metrics like:
It gives support leaders a full picture of how their team is performing, so they can coach with clarity, not just gut feeling.
Here’s what brands can do with automated QA:
Let’s walk through a real example.
Customer: “Hi, my device broke, and I bought it less than a month ago.”
Agent: “Hi Kelly, please send us a photo or a video so we can determine the issue with your device.”
Auto QA flags this interaction with:
Reactive support is table stakes. AI takes it a step further by anticipating issues before they happen — and proactively helping customers.
Let’s say login errors spike after a product update. AI detects the surge and automatically triggers an email to affected customers with a simple fix. No need for them to dig through help docs or wait on chat — support meets them right where they are.
Proactive AI can also be used for:
This saves the time of your agents because the AI will spot problems before they turn into tickets.
Your customers are telling you what they think. AI just helps you hear it more clearly.
By analyzing reviews, support tickets, post-purchase surveys, and social comments, AI can spot sentiment trends that might otherwise fly under the radar.
For example:
Related: 12 ways to upgrade your data and trend analysis with Ticket Fields
Whether you’re enriching customer data, making smarter product recommendations, triggering dynamic pricing, or proactively resolving support issues, AI gives your team the power to scale personalization without sacrificing quality.
With Gorgias, you can bring many of these use cases to life — from AI-powered chat that drives conversions to automated support that still feels human.
And with our app store, you can tap into additional AI tools for data enrichment, direct mail, bundling insights, and more.
Personalized ecommerce doesn’t have to mean more work. With the right AI tools in your corner, it means smarter work — and better results.
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TL;DR:
AI is everywhere in customer service—powering live chats, drafting responses, and handling inquiries faster than ever.
But as AI takes on more of the customer experience, one question keeps coming up: Should brands tell customers when they’re talking to AI?
Legally, the answer depends on where you operate. Ethically? That’s where things get interesting. Some argue that transparency builds trust. Others worry it might undermine confidence in support interactions.
So, what’s the right move?
This guide breaks down the debate and gives CX leaders a framework to decide when (and how) to disclose AI—so you can strike the right balance between innovation and trust.
Depending on where your business operates, disclosure laws may be strict, vague, or nonexistent. Some laws, such as the California Bolstering Online Transparency Act, prohibit misleading consumers about the use of automated artificial identities.
For maximum legal protection, it’s best to proactively disclose AI use—even when not explicitly required.
A simple disclaimer can go a long way in avoiding legal headaches down the line. Here’s how to disclose AI use in customer interactions:
Truthfully, AI laws are evolving fast. That’s why we recommend consulting legal counsel to ensure your disclosure practices align with the latest requirements in your region.
But beyond avoiding legal trouble, transparency around AI usage can reinforce customer trust. If customers feel deceived, they may question the reliability of your brand, even if the AI delivers great service.
Related reading: How AI Agent works & gathers data
Research shows that 85% of consumers want companies to share AI assurance practices before bringing AI-driven products and experiences to market.
But what does “transparency” actually mean in this context? An article in Forbes broke it down, explaining that customers expect three key things:
How you disclose AI matters just as much as whether you disclose it. At the end of the day, AI isn’t inherently good or bad—it’s all about how it’s implemented and trained.
The way a brand approaches AI disclosure can impact trust, satisfaction, and even conversion rates—making it a decision that goes beyond simple legal requirements.
While some customers appreciate honesty, others may hesitate if they prefer human support. Brands must weigh the pros and cons to determine the best approach for their audience.
Let’s be honest: AI in customer service still carries baggage. While some consumers embrace AI-driven support, others hear "AI" and immediately picture frustrating, robotic chatbots that can’t understand their questions.
This is one of the biggest risks of transparency: customers who’ve had bad AI experiences in the past may assume the worst and disengage the moment they realize they’re not speaking to a human.
For brands that thrive on personal connection and high-touch service, openly stating that AI is involved could create skepticism or drop-off rates before customers even give it a chance.
Another challenge? The perception gap.
Even if AI is handling inquiries smoothly, some customers may assume it lacks the empathy, nuance, or problem-solving skills of a live agent. Certain industries may find that transparency about AI use leads to more escalations, not fewer, simply because customers expect a human touch.
Despite the risks, transparency about AI can actually be a trust-building strategy when handled correctly.
Customers who value openness and ethical business practices tend to appreciate brands that don’t try to disguise AI as a human.
Being upfront also manages expectations. If a customer knows they’re speaking to AI, they’re less likely to feel misled or frustrated if they encounter a limitation. Instead of feeling like they were "tricked" into thinking they were talking to a human, they enter the conversation with the right mindset—often leading to higher satisfaction rates.
And then there’s the long-term brand impact.
If customers eventually realize (through phrasing, tone, or inconsistencies) that they weren’t speaking with a human when they thought they were, it can erode trust.
Deception—whether intentional or not—can backfire. Proactively disclosing AI use prevents backlash and reinforces credibility, especially as AI becomes a bigger part of the customer experience.
Arcade Belts, known for its high-quality belts, wanted to improve efficiency without compromising customer experience. By implementing Gorgias Automate, they reduced their reliance on manual support, creating self-service flows to handle common inquiries.
Initially, automation helped manage routine questions, such as product recommendations and shipping policies. But when they integrated AI Agent, they cut their ticket volume in half.
The transition was so seamless that customers often couldn’t tell they were interacting with AI. “Getting tickets down to just a handful a day has been awesome,” shares Grant, Ecommerce Coordinator at Arcade Belts. ”A lot of times, I'll receive the response, ‘Wow, I didn't know that was AI.”
You can read more about how they’re using AI Agent here.
We mentioned it earlier, but deciding whether or not to disclose your use of AI in customer support depends on compliance, customer expectations, and business goals. That said, this four-part framework helps CX leaders evaluate the right approach for their brand:
Before making any decisions, ensure your brand is compliant with AI transparency regulations.
AI transparency should align with your brand’s values and customer experience strategy.
Rather than making assumptions, run controlled tests to see how AI disclosure affects customer satisfaction.
AI strategies shouldn’t be static. As customer preferences and AI capabilities evolve, brands should refine their approach accordingly.
If you decide to be transparent about AI in customer interactions, how you communicate it is just as important as the disclosure itself. Let’s talk about how to get it right and make AI work with your customer experience, not against it.
AI doesn’t have to sound like a corporate FAQ page. Giving it a personality that aligns with your brand makes interactions feel natural and engaging. Whether it’s playful, professional, or ultra-efficient, the way AI speaks should feel like a natural extension of your team, not an out-of-place add-on.
Instead of:
"I am an automated assistant. How may I assist you?"
Try something on-brand:
"Hey there! I’m your AI assistant, here to help—ask me anything!"
A small tweak in tone can make AI feel more human while still keeping transparency front and center.
Read more: AI tone of voice: Tips for on-brand customer communication
One of the biggest mistakes brands make? Leaving customers guessing whether they’re speaking to AI or a human. That uncertainty leads to frustration and distrust.
Instead, be clear about what AI can and can’t do. If it’s handling routine questions, product recommendations, or order tracking, say so. If complex issues will be escalated to a human agent, let customers know upfront.
Framing matters. Instead of making AI sound like a replacement, position it as a helpful extension of your support team—one that speeds up resolutions, but hands off conversations when needed.
Even the best AI has limits—and customers know it. Nothing is more frustrating than a bot endlessly looping through scripted responses when a customer just needs a real person to step in.
AI should be the first line of defense, but human agents should always be an option, especially for high-stakes or emotionally charged interactions.
A smooth handoff can sound like:
"Looks like this one needs a human touch! Connecting you with a support expert now."
AI disclosure doesn’t have to feel like an apology. Instead of focusing on limitations, highlight the benefits AI brings to the experience:
It’s the difference between:
"This is an AI agent. A human will follow up later."
vs.
"I’m your AI assistant! I can answer most questions instantly—but if you need extra help, I’ll connect you with a team member ASAP."
The right framing makes AI feel like an advantage, not a compromise.
AI perception isn’t static. Regularly analyzing sentiment data and customer feedback can help refine AI messaging over time—whether that means adjusting tone, improving explanations, or updating how AI is introduced.
When you follow these best practices, AI can be a real gamechanger for your customer support. Just take it from Jonas Paul…
Jonas Paul Eyewear, a direct-to-consumer brand specializing in kids' eyewear, needed a way to manage high volumes of tickets during the back-to-school season without overwhelming their customer care team.
To streamline these conversations, Jonas Paul implemented AI Agent to provide instant responses to FAQs. This allowed human agents to focus on more complex cases that required personalized attention.
“Being able to automate responses for things like prescription details and return policies has allowed us to focus more on the nuanced questions that require more time and care. It’s been a game changer for our team,” said Lynsay Schrader, Lab and Customer Service Senior Manager and Jonas Paul.
Jonas Paul saw a 96% decrease in First Response Time and a 2x ROI on Gorgias’s AI Agent with influenced revenue. You can dive in more here.
Whether or not your brand chooses to disclose AI in customer interactions, the key is to ensure AI enhances the customer experience without compromising transparency, accuracy, or brand identity.
So how can you get started? Gorgias AI Agent was built with both effectiveness and transparency in mind.
For every interaction, AI Agent provides an internal note detailing:
Excited to see how AI Agent can transform your brand? Book a demo.
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By Ross Beyeler, Founder and CEO of Growth Spark
Often, a support team answers the same questions over and over…
Or issues returns repeatedly for reasons that could be addressed internally…
Maybe the sizing isn’t well represented, the fulfillment house has mixed up SKUs, or your product images aren’t clear or detailed enough.
If you can lighten the load for your customer support team, you can save significant time and costs, while at the same time improving the buying experience for your customers.
The goals here are to:
The key is to address your customers questions and issues before they ask your support team. Here's how you do that:
91% of shoppers would gladly try to answer their own questions first using an online knowledge base or FAQ page before reaching out to a customer service team, according to a survey by Coleman Parkes for Amdocs.
This means that your FAQ page is a huge opportunity to answer your customers’ most common questions and issues so they don’t need to reach out to customer support.
FAQ information typically falls into one of two distinct buckets: product-specific and buying process.
Product Specific: Common questions about individual products may be better off addressed on the product pages rather than in a broad FAQ page. You may need to provide clearer or more comprehensive product descriptions, or consider more or better photography to clear up common product questions.
Buying Process: Questions about shipping, returns, policies, and other operational topics are best addressed in a single easy-to-find page like an FAQ.
When is the last time you cross-checked the content of your FAQ page with the data from your customer support team?
There are many customer support tools like Gorgias that will make it easy for you to track the reasons behind why users submit a ticket.
Once you begin tracking the topic, or tag, of your questions, you can easily identify the questions that top the list, and permanently add the responses to the FAQ.
Bonus points: Prioritize the FAQ page based on the frequency of each customer service inquiry so that the most relevant answers are closer to the top.
Your next step is to set up a monthly meeting with your head of customer service to review the feedback coming in from your customers and ask yourself:
Remember, an FAQ page is:
For more on FAQ pages, check out this Shopify article.
Now that you have your FAQ page squared away, be sure to track visitors to the page and note any changes in volume, and look for changes in your support ticket volume around those related questions.
Remember: You should never answer a support ticket only by referencing your FAQ page. Always include the information they are asking for directly within your response. After that, let the customer know that there is an FAQ page for more information, to avoid future tickets.
Have you watched actual customers explore your online store to see where they stumble?
Customer behavior tools like Hotjar make it easy to review how customers navigate your website. One way that customer behavior analysis tools can help you understand exactly how your customers are using your site is with heat maps.
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A heat map is a visual representation of the most popular (hot) and unpopular (cold) elements of a website page. They can give you an at-a-glance understanding of how people interact with individual website pages. Elements that get the most views and interaction are shown in red, so you can immediately spot what your users are clicking on. Those that most people tend to ignore appear in blue.
Once you know which parts of your website are most (and least) useful to shoppers, you can tweak those elements to make the on-site experience easier to use.
Customer behavior data can inform on-site improvements, such as:
It may require some A/B testing to ensure your changes deliver results.
According to a recent Shopify post, during the holiday season, Ecommerce returns surge to 30 percent (or as high as 50 percent for “expensive” products).
Return deliveries are estimated to exceed $550 billion by 2020 in the U.S. alone.
Many of those returns are probably associated with a customer support ticket - whether customers are asking questions about the product they received, or need help processing their return.
Anything you can do to reduce the number of returns - and the number of customer support requests associated with them - can mean a huge boost for your bottom line.
So, what causes returns?
Returns can often be traced back to a disconnect between customer expectations and the reality of the product once they receive it. It may be that:
All of these problems (and more) can be prevented in advance with improvements to your website content.
While fit can be a difficult factor to get right online, including detailed dimensions is a big step in the right direction. Some apparel merchants are taking sizing one step further with interactive fit guides, like the one above Nudie Jeans, which uses an app integration called Virtusize:.
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Poor quality or not enough product images can make it difficult for customers to accurately understand what your product will look like when it arrives at their home.
You can easily reduce your return rate by making sure your product photography is clear and high-quality, and illustrates all of the primary parts of each product. More complicated or detailed products can also benefit from a video or 360-view.
Detailed product descriptions can also help address confusion about product appearance and feel. Sol de Janeiro does this with a multi-tab product content area that defaults to a brief product highlight, with additional tabs to provide more details.
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Are orders not being fulfilled to the right customers?
Are deliveries taking longer than they should?
Analyzing your fulfillment data and using that information to make adjustments to your website content - such as average delivery times - can help eliminate a source of customer support calls.
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For example, maybe you want to be able to deliver every order within two days, but your current fulfillment resources simply can’t make that happen consistently. Being up-front and clear about realistic delivery times (like The Black Dog does in their Shipping FAQ page, above) will help set customers’ expectations appropriately.
Bonus: To get setup on two day shipping, consider our partners at ShipBob.
Continue to study your on-site data using Google Analytics or Shopify’s native analytics and look for high exit % pages. These may be pages where prospects or customers are running into a dead end and being forced to turn to support.
You can also create a goal in Google Analytics that corresponds to contacting support, then reverse the user path to determine which pages lead to them submitting a ticket / hitting that “contact” or “support” button.
Chances are, there are a few areas of “low hanging fruit” that can make significant improvements to your customer support load once you find them and address the root concerns. And with those small fixes, you could see a big impact on your bottom line, and a better on-site experience for your customers.
Read more about customer support on our trusted partner’s site, Growth Spark:
Ecommerce has become awash with digital bells and whistles. Technology has no doubt enhanced the shopper experience but the rapid rate of digital innovation has had a profound effect on customer expectations. By 2020, customers expect brands to automatically personalize experiences to address (not just predict) their current – and future – needs.
But, although customers expect more in terms of tech, they still crave the person-to-person connection. In fact, 75% of consumers want to see more human interaction, not less.
At LoyaltyLion we know that bringing back this human-touch depends on providing a good customer experience. Clearly, a worthwhile cause, as studies show that 86% of shoppers who received great customer care are more likely to repeat purchase. By going the extra mile to treat your shoppers as people – rather than numbers – you can secure a faithful, constant customer base.
Here are three insights that will help you bring the human touch back to your online store.
Each customer is unique. They interact with your brand in different ways, all while having their own personal needs and desires. When a customer feels that you have taken the time to understand their unique requirements, they will trust and value your brand more.
Data and personalization go hand in hand. By using member information to learn how customers engage with your loyalty program, you can understand their feelings towards your brand and react accordingly. Being data-driven is the key to true e-commerce success.
One golden opportunity to personalize your communications this is through targeted emails. Use your Gorgias dashboard to identify past interactions and purchases, as well as a customer’s loyalty points balance. You can then use that member data to create bespoke rewards that you can send right to your customer’s inbox.
Maybe you’ve noticed that they keep eyeing a specific product range? If so, give them discounts on new products in that collection to tempt them to back to buy again. Or perhaps you’re aware that they’re just a couple of points away from their next reward. Give them a little nudge to return and receive their reward sooner. For example, LoyaltyLion user Dr. Axe alerts customers when they have rewards waiting to be claimed, and suggests a particular product to redeem that reward on.
Shoppers love to feel that they’re your only priority and that you care about them on a personal level. They want to feel valued as individuals, not just another number in an extensive database.
Loyalty strategies should incorporate ways to surprise and delight customers. For example, making it easy to offer customers points on their birthday or taking a moment to personally congratulate them when they’ve made a certain number of purchases with you. Beauty Bakerie, for example, offers their customers 500 points on their birthday.
With Connectors for Shopify Flow, it’s easy to use LoyaltyLion and Gorgias to set up triggers that automatically create tickets on a customer’s birthday, reminding a representative to get in touch. It’s the thought that counts and going the extra mile will ensure your customers trust and remember you. Plus, you’ll feel good about it too!
Customers get frustrated when they feel their complaints aren’t taken seriously. Dissatisfied customers will tell between nine and 15 people if they have a bad brand experience. Using Gorgias’ helpdesk and macros, you can help resolve complaints whilst maintaining a personal touch. For example, ethical online yarn store, Darn Good Yarn uses the helpdesk to analyse and automate how they solve common customer issues, using a whole database of the shopper’s history to address specific queries in a more informed way.
If you are reacting to customers have had a negative experience, your loyalty program can help you demonstrate you care. You might consider offering bonus points or benefits such as free delivery, or moving them up a loyalty tier so that they can unlock more exclusive rewards in the future. These tokens of appreciation can turn a bitter experience into a sweet deal.
Research shows that 94% of customers who have their issues solved painlessly said they would purchase from that company again. This shows that helping customers to solve their problems is key to securing their long-term loyalty. Treat your most valuable customers well by making their shopping experiences as easy as possible. In return, they’ll give you their loyalty.
In a world where technology and data can give ecommerce stores a competitive edge, there’s a risk that we could lose touch with the human side of retailing. Human exchanges are still, and always will be, the primary driver of loyalty. So, use digital personalization to your advantage and treat your customers as individuals.
It's been over 3 years since we've started working on the Gorgias helpdesk. The engineering team started with just me (Alex) and then gradually grew to a team of 5 people. We're a small team, but we've accomplished a lot during this period. Here are some stats from 0 code/customers/revenue in Oct 2015 to this:
Modest numbers to be sure, but we're very proud that people use our product in a big part of their workday and hopefully are becoming more productive while doing so. The whole idea behind our product is to scale customer support with as little resources as possible. Given this, perhaps it's only natural to build our product with a small team as well?
We've been suffering chronically from "not having enough people" - we still do. That forced us to adopt a certain engineering culture that I want to talk about in this post.
When we first started building Gorgias, having just a few people on the team allowed us to progress at a pace where we could collect real feedback from our customers with things that really mattered to them rather than building every feature they ask for. A lot of their asks seemed legitimate, but because we didn't have a lot of people it forced us to prioritize the critical, high impact things first.
Having a small team can act like a barrier that blocks you from building a bloated product.
I want to make more of a case for the above statement, but first I'd like to get a bit more into what we did during the 3 year period.
Once we've build an initial version of the app and got our first customers we quickly realized that building a "second Gmail" is super-hard:
It takes a lot of effort to get to a point where you can compete with the likes of Gmail or Zendesk - both amazing products btw. This was definitely the case for us, for close to 2 years we had only a couple of customers and our product wasn't that good if we're being honest.
So what changed a year ago? To put it simply: our product didn't suck anymore. Or sucked less. It had that minimum set of features and stability that made it attractive enough to our main customer base (Shopify merchants) that were passionate about productivity in the customer support space. That, and the tenacity of our CEO Romain who was convincing everyone that they should use us.
So we started having our second wave of early adopters and all our hard work was finally starting to pay-off!
Now that we had more and bigger customers we were starting to have performance issues, our app was slow, suddenly we were starting to get bombarded by viral facebook posts events or promotional events via an email campaigns, we didn't have enough monitoring in place, our app was pretty inefficient, the main database was a frequent source of congestion. So we started fixing those issues while still receiving numerous feature requests.
Thankfully we didn't actually optimize our code that much before (no customers!) and there were a lot of low hanging fruits at first, but it still put a lot of stress on the team which was becoming tired and overworked and requested to hire more people to build those features and help with the performance issues.
We all agreed that it would be for the best to have more people on the team, but hiring is hard. Competent coders are not just randomly looking for the next gig. SF is also a very expensive city and for a startup that raised $1.5M and a 2 years of money burned we couldn't really compete with other players in town. We've started working with some great devs in Europe, we worked with a few talented interns as well and we tried to get by until we could have more customers and hopefully raise some more money to hire more people.
I could speak more about hiring in the Bay Area and there are a lot of things we did wrong and still have a lot of things to learn, but that's probably an even longer post than this one. But yeah, it's hard to find someone good, it's expensive, etc...
So what is the situation right now? Well, it's not much better. We've raise d a seed extension round from SaaStr with Jason Lemkin and hired a few people in the Growth team, but we still have a hard time hiring in SF or remote. In the meantime we have a small team and want to talk about that.
I think it's important to realize the advantages of having a smaller team and the single most important super-powers that you're forced to acquire is saying NO more often that you would with a bigger team. If you have a bigger team and say no to a feature, new platform, integration, etc.. it's harder to justify the decision. There are arguments like:
... we have enough devs! They are paid to make features, so what's the problem!?
... the data shows that 50% of our customers are saying that they want this or that feature, we must build it!
But do we absolutely need to build that feature? Are the customers going to be a lot less effective with your product otherwise? Is it going to be a big boost for them or just a nice improvement? Once a feature is there you have to maintain it, fix bugs, improve it, etc.. The thing with data driven decisions is that sometimes it can be biased towards some historical practice that might not have a place in your current world.
Now, I'm not saying that you shouldn't listen to your customers, you absolutely have to, but be sure you understand well what they want before taking action and understanding takes time. Having an artificial brake on your enthusiasm might be a good thing.
Engineers build things, the natural tendency is to accept any technical challenge because of ego, curiosity, fun, etc... It takes discipline to say no and stick by it. A small team is making it easier to do it.
When you have a small team you're forced to automate a lot more often some of your workflows. You don't have the luxury to do repetitive stuff so:
People that work at Gorgias come from different backgrounds and sometimes it can be challenging to be on the same page. In some cases our work processes are similar to many other companies:
But there is so much more than just the above processes to engineering:
These things need time to happen to be embedded in your engineering consciousness and if you're the first-time founder (like myself) you also need the time to understand how to operate in this environment.
Never managed a big team so I can't really speak about it's dynamics, but I would expect that because there are more people there is a lot more bandwidth you have to manage, a lot more people have to agree, a lot more politics have to be settled. I don't look forward to that to be honest, the more time I can get away with hiring as little as possible without a big sacrifice of our growth as a company the more I'll try to delay it.
I conclusion I would say that it's totally fine to have a small team, in fact, I'm considering it a competitive advantage that you should try to keep as long as you can.
I made a point in this post that having a small team is a competitive advantage, but I also think that we are ready to grow our team a bit. Yep, we're hiring!
Facebook Messenger is becoming a new marketing channels for brands. They use it as a way to build personal relationships with customers and to drive higher conversion than traditional email marketing.
Today, we're excited to announce our newest integration: Octane AI.
When a brand launches a marketing campaigns on Messenger, it typically leads to insane conversion rates. That's why the trend is on the rise.
Another consequence is that a lot of customers respond to promotional Messenger communication. This generates a spike of support requests, that your support team has to deal with.
Our integration with Octane AI lets you handle this support spike directly in Gorgias. Your agents have context about the customer: they see the conversation history before the Messenger conversation (did the customer email you last night?), and allow you to take action, like editing or refunding an order
Customers are already using Octane AI and Gorgias. Here's what Live Love Polish has to say about the Octane AI and Gorgias integration:
“We’re really thrilled that Gorgias and Octane AI came together to make the customer service experience over Messenger even better for our customers. Accessible customer service is central to what we do at Live Love Polish. Answering customer questions via Messenger has made our customers happier.”
Do you want to give this a shot? If you use both tools, just connect your Facebook page to your Gorgias account and see the magic happen. If not, create a Gorgias account, or sign up for Octane AI.
Do you have questions? Just hit the chat bubble, our team would love to tell you more about the integration!
Loyalty programs are widely used amongst e-commerce merchants to grow and maintain market share by improving the number of repeat customers and attracting new ones. These programs come in different formats - from loyalty points to surprise gifts depending on the level of loyalty of each customer - and have proven efficient to help brands build a community of consumers based on the emotional attachment to their identity and values.
As a customer support helpdesk, Gorgias is focused on providing the best experience for both end-consumers and support agents. Consequently, giving access to the most accurate information about your customers’ loyalty status enables your support team to adapt their answers to customer requests.
Thus, it seemed only natural that we partner with Smile.io, a rewards platform that has helped over 20,000 merchants reward their most loyal customers for performing profitable actions.
With Smile, you can create and manage reward programs such as loyalty points, referrals and VIP programs, to build a fruitful relationship with your customers.
Because Gorgias is appreciated for its ease of use and automation tools, we have decided to build a strong integration with Smile: not only can your support team have easy access to all the necessary data about your customers, but they can also use Smile variables in canned responses (or “macros”) and automation rules.
By integrating your Smile account to Gorgias, you’ll be able to improve yet again not only your customer support but also your customers’ engagement to your brand. Our early adopters of the integration are already thrilled by it!
"We're loving the Smile integration so far! Having access to the variables in the automation features of Gorgias (macros and rules) is a game-changer, especially now that we're focusing on improving our loyalty program. It would be great if the integration went a little further in the future to enable editing loyalty points!"
Chris Storey, Founder and CEO at Dinkydoo
If you're already a Gorgias customer, you can connect Smile directly from your Gorgias account, in the Integrations section. If not, you can create an account here and get started in a few minutes.
Here at Gorgias, our aim is to provide the best customer support tools to our clients, whatever their specific needs. The more you grow, the more we work to develop our offer so that you can benefit from a tailor-made spectrum of integrations. As your business becomes more successful, you need to adapt your website to a fast-growing community of consumers, especially regarding the quality of your reviews and how they appear.
This is why today we are proud to announce our new partnership with Okendo, a customer-marketing platform perfectly suited for high-performance Shopify businesses.
Okendo helps Shopify’s fastest growing companies like oVertone, Paul Evans and Dormify build vibrant customer communities through product ratings & reviews, customer photos/videos and Q&A.
Along with this, Okendo gives you the tools to leverage customer generated content across other marketing channels such as Google Search, Google Shopping, Facebook and Instagram.
Since one of the key advantages of using Gorgias is to manage all your customer support in one dashboard, we decided to design a straight-to-the-point integration:
If a customer leaves low rating review such as < 3 stars and/or with negative sentiment, Okendo can automatically create a ticket in Gorgias. This way, your staff can quickly engage in a conversation with them to understand what went wrong, and address the issue immediately.
We believe this integration will take your customer support teams to the next level, as Okendo has already convinced some of our key clients.
"One of our biggest assets is our unique customer community, so being able to maintain it as active and engaged as possible is key for our business. And making sure that we address any negative experience efficiently and in no time is just as important: this is exactly what the Okendo integration within Gorgias has enabled us to do, by automatically creating a ticket for these cases with the review displayed right next to it."
Dan Appelstein, Founder & CEO at BeGummy
"Aside from being excellent at building shopper trust, reviews enable us to identify customers who, for whatever reason, have had a less than stellar experience. The Okendo + Gorgias integration enables us to flag these instances and automatically assign a Gorgias ticket to a member of our Client Services Team, so that we can follow up and do our best to assist them with whatever issues they're encountering. This integration, along with Okendo’s consistent availability and unwavering support, have made the integration between these two platforms seamless and successful!"
Jae Sutherland, Director of Client Service at oVertone
If you're already a Gorgias customer, we can introduce you to Okendo to implement the integration directly from your Okendo account. If not, you can create an account here and get started in a few minutes.
The supplement industry is not often the first thing that comes to mind when looking to start a new business. It’s crowded, the barriers to entry are low, the margins are thin, and there are some established and well-known brands with large budgets to outspend competitors.
And yet, Campus Protein, a provider of supplement to college students that started in a dorm room in 2010, has managed to carve itself a highly profitable niche and power its way to millions of dollars in revenue.
No, there’s no magic sauce or secret weapon that helped them do it. They have the same access to resources as everyone else. In fact, they have a smaller team than older brands in the space.
The only difference is they focused on one thing that others in the industry weren’t, the customer experience. This is the story of how they did that and dominated behemoths like GNC in colleges across the US.
Before coming up with the idea, founder Russell Saks was just another sophomore at Indiana University. After joining a fraternity, his new friends convinced him to start hitting the gym.
As Russell started getting into fitness, he noticed that every month his friends would head to the local supplements store to purchase $200 to $300 worth of protein and workout drinks. These were the same people who always complained that they didn’t have beer money on the weekends. Yet here they were, spending hundreds of dollars on supplements without batting an eyelid.
In any industry as crowded as the supplement industry, there are always cheaper options. You can go online and buy your supplements at a much lower price than at the local store. However, the drawback is that you have to wait for it. And, as Russell found out, college students never planned ahead and always needed their next tub of protein powder instantly.
Ever the entrepreneur, Russell figured there was an opportunity here. If he could combine the affordability of online prices with the same-day delivery of the local store, he had a business. All he had to do was bulk order product from a low-cost site in advance, store it locally, and then redistribute it to students when they needed it.
As with any business, those initial days were rough. Yes, there was demand and Russell would often sell out each batch soon after they came in, but the margins were razor thin. To maintain cost-effectiveness, Russell sometimes had to take a loss on certain products.
On top of that, Russell found that his life was getting consumed by the fledgling business. To scale it up, he needed help. His friend and first business partner (now Chief Sales Officer), Mike Yewdell, was a fellow student at Indiana University with lots of connections. With his network, they quickly became the go-to source for supplements on campus.
Russell’s next stop was his high school friend (now business partner and CMO), Tarun Singh, who was studying in Boston University at the time. Tarun noticed the same problems at his school and quickly expanded Campus Protein to his school and then the entire Boston area.
The final piece fell into place when they entered into a business competition and won $100,000 to scale up. With the up-front money, they could negotiate deals with supplement makers to improve their margins, and expand to more college to increase sales.
Today, Campus Protein is in over 300 colleges across the US and shows no signs of slowing down. But none of that would have happened if Russell hadn’t been hyper-focused on a certain type of customer and their needs.
One thing Russell learned early on was that college students had very specific needs. Thus, they craved a personalized experience. They needed help with what supplements to buy based on their goals and budget.
At the local supplement stores, Russell noticed that they couldn’t get any of that. Firstly, they sold to everyone so they didn’t have any expertise specific to the college student market. Secondly, they were trained to sell as much product as possible, so they’d often push supplements that weren’t right for the students.
Russell realized that Campus Protein needed to really understand the needs of a college student to own the market. That meant the company needed to hire students who were into fitness. And so the Campus Rep program was born.
A Campus Rep's main job is sales and marketing. They grow awareness for the brand and encourage help other students achieve their fitness goals.
By recruiting Reps in each college, Campus Protein could keep their core team lean while maintaining a large salesforce on the ground.
This has been the real key to their growth. These Reps are their ideal customers, and they hang out with other prospective customers. Thus, they provide a customer experience that’s far better than anything other brands can offer.
Imagine you’re a college student. Before Campus Protein came along, you had to figure out which products to buy, got pressured into buying unnecessary stuff, and ended up with very little money left over.
Today, you probably have a Campus Protein rep in your gym, wearing a branded tank. He’s giving out free tasters, providing you with workout tips and nutrition advice, listens to your goals, and hands you a card with a link where you can buy exactly what you need for much less. How’s that for customer experience?
Campus Protein may be marketing offline with their campus reps but all their sales come from their Shopify website. That’s the best way for them to scale.
Here’s how it works - they have warehouses across the country where they stock product. Because of their deep customer understanding, they know exactly what to stock and what not to stock. The campus reps then go around building awareness, and students head to the website to make their purchase. Because of the warehouse network, they get their products pretty quickly.
Because the actual sale is made online, the website becomes a crucial part of their strategy. If they don’t provide the same level of customer support and care their reps do, they’ll drop the ball and lose the sale. More importantly, they’ll lose trust. One bad experience could hurt their reputation across an entire college.
To replicate the one-on-one support of their reps, they used website chat. In the early days, they started with Zopim Chat. But as they grew, they found that it was too basic for their needs. They couldn’t tell if someone they were chatting with was an existing customer or a new one. They couldn’t tell if it was a new conversation or a continuation of one that happened in a different channel. It was a poor experience for the customer and the company.
Remember, they have a small core team, so they needed a customer support tool that could do the heavy lifting for them. That’s when they came across Gorgias and it allowed them to create an online experience that increased conversions and revenues.
For starters, Gorgias combines all their customer support channels (chat, email, phone, social media) into one unified view, and builds a profile of each customer. When a student chats with them, Campus Protein know if they are a previous customer, can see all past conversations and sales in their dashboard, and can provide relevant support.
Compare that to the typical support you get when you’re forced to repeat your previous conversations each time you chat with someone.
To speed things up, Gorgias also has macros and templated responses based on the question. For example, if a customer wants to know where their order is, Gorgias presents the support agent with a templated response that pulls in the customer’s order details from Shopify. With just a click, the support agent can answer the question in near real-time.
Automations like this also frees up time for support agents to provide more detailed answers to complicated questions, like when a student asks for nutrition advice. Again, they can provide the same level of caring support that reps do and this helps increase sales.
Another way they increase sales is by detecting if customers are spending a lot of time on a certain page and initiating a chat with them. For example, if someone is on the checkout for too long, Gorgias automatically pops a chat and ask them if they need help. This directly increases conversions.
Perhaps the most important way Campus Protein uses customer support to increase revenues is by converting feedback into website and product changes. For every question that comes in, they try to understand why it wasn’t obvious on the website, and make the appropriate change. This leads to fewer tickets of the same type and higher conversions.
At the end of the day, Campus Protein is just another retailer. In an industry like supplements, anyone can replicate their model, or existing brands like GNC can enter the market. So why hasn’t that happened yet?
Like Warren Buffett says, every business needs to have a moat, something that defends them against competition. In Campus Protein’s case, it’s their deep customer knowledge and the personal level of support they provide.
A college student is introduced to Campus Protein via the local rep. They’re nice, helpful, and remember the student’s name each time. When the student goes online, they have the same experience. Their previous conversations are remembered and even their most complicated questions are answered with care.
Now, you may not be able to create a rep army like Campus Protein for your eCommerce business, but you sure can create an online customer experience that sets you apart from others in your industry.
With Gorgias, whenever a customer creates a ticket on any channel, you have all their information like previous conversations and sales, right there. Instead of asking the customer if they’ve written in before or what their order numbers are, you can get straight to the important stuff. And with all the templates, macros, and automations available, you can do it in minutes.
When a customer has to decide between purchasing at a store where they forget about you after the sale, versus one where they treat you like a friend and remember you a year later, which do you think they’ll choose?
Give your customers a great experience and, like Campus Protein, you’ll have a business that keeps going up.
Aircall is a cloud-based call center software made for support teams. With Aircall, support agents can track everything from A-Z, on any device, with zero hardware to manage. The right tool to increase agent efficiency and customer satisfaction!
After listening to early customer feedback, we quickly realized we needed to find a phone integration that empowered users to manage voice calls as easily as emails or chats.
Traditional helpdesk integrations simply log calls as tickets. We wanted to go one step further and associate the phone call with the right customer. This way, agents can see the full conversation history between the brand and the customer.
By building Aircall’s cloud-based phone into the Gorgias platform, agents can also quickly edit orders while on the phone based on the case history they see. After a call has ended, all notes will be added to the correct customer’s profile along with a link to the full call recording.
Looking back, the partnership has been mutually beneficial and seamlessly implemented.
Aircall has a well-documented API that our dev team could easily use. We were able to build a working and robust phone integration with Aircall in just a few hours. Four days later, after QA testing, the new solutions were fully functional and ready to use.
Since Gorgias and Aircall both seek to provide the best customer experience possible, cross-company visibility has become a valuable source of new leads and sales. Furthermore, we conduct regular catch-up meetings and share a Slack channel to make sure both teams work hand-in-hand to create the best integration and the best results. The partnership with Aircall is super valuable for both our customers and our respective companies and we strongly recommend each others.
If you're already a Gorgias customer, head to your account and go to Integrations to connect Aircall. If not, you can create an account here and get started in a few minutes.