Leveraging Customer Reviews In Ecommerce

Founder: "I can't find the right leads." Me: "What about the unhappy customers from your competitors?" Here's the exact system we built 👇 (We've seen 15-25% reply rates when messaging hits documented competitor weaknesses) G2. Capterra. Trustpilot. They're full of pain points, written by people actively looking for a better option. We've turned that into a repeatable outbound system. 1️⃣ Review Scraping Start by scraping negative reviews from 2-3 core competitors. a. n8n (starts at $20/mo): Build custom scraping workflows for G2, Capterra, and Trustpilot. We use this to power the majority of our review mining workflows. b. Apify (starts at $49/mo): Pre-built scrapers for most review platforms. 2️⃣ Pain Point Analysis Start by clustering hundreds of complaints into themes like feature gaps, support response time, UX issues, security concerns, and pricing. ↳ ChatGPT-4 ($20/mo) / Claude ($20/mo) / Perplexity ($20/mo) You now have a live database of what your prospects hate about their current tool. 3️⃣ Positioning Alignment Map those complaints to your actual value props. If their reviews mention "hidden fees" and your pricing is transparent, lean into that. ↳ Google Sheets (free) / Airtable ($20/mo) for mapping pain points to your positioning. Now you're not just pitching features. You're presenting a clear solution to a known frustration. 4️⃣ Data Enrichment & Targeting Once you know who's unhappy and why, you need to find the decision makers at companies using those competitors: ↳ Clay ($149/mo) / FullEnrich ($29/mo) The messaging angle is already validated, and the frustration warms the list. You're simply showing up with a better option. 5️⃣ Outbound Execution Once the data part is covered, the next step is to engage your leads and ensure your message delivers: a. Instantly.ai(starts at $37/mo) for unlimited email outreach b. lemlist (starts at $69/mo) for multi-channel outreach c. Expandi.io or HeyReach.io for LinkedIn-focused campaigns 6️⃣ System Automation Nothing replaces good strategy when it comes to outbound... but automation makes it scalable. We've built versions of this using n8n (for scraping) + ChatGPT (for clustering complaints) + Google Sheets (for inputs) + Clay + Instantly (for execution). The system runs on autopilot. Every week, we analyze what's working, tweak our messaging, and pull in fresh prospects. Once it's live, it becomes one of your highest-converting outbound motions. Why? Because you're focusing on real pain points and providing a better solution. Want to see this level of systematic outbound in action? Like and comment “competitors” and I will send you a training on how to send 1,000 personalized cold emails with AI ♻️

Here’s a science-backed way to increase sales by 24% - without more leads or a new sales strategy. It all has to do with how you handle online reviews. I’ll give you the research, then the formula to get more sales. - A 2021 study in the Journal of Marketing Science by Proserpio and Zervas found that a single negative first review can tank your average rating by 0.29 stars, and cost you nearly 40 reviews over the next year. The research found that responding to reviews boosts star ratings and can increase the total reviews by 12%, and bump you up half a star within six months - Research from Bocconi University and INSEAD in 2023 showed that a SINGLE negative review on the first page of your webpage can decrease purchases by 42%. Each additional negative review drops that by another 27% (the effect is strongest for reviews about product or service functionality). - Research from Tuck and the London Business Schools highlights the primacy effect: A bad first review is incredibly damaging, but a relevant positive first review is a massive plus. There’s a lot more detail to these studies BUT I’ll shortcut it for you. Armed with science, are the steps to make more sales: 1. RESPOND: Respond to *every single review*, good or bad: it shows that you care, you’re listening, and this builds brand value over time. 2. NEGATIVE REVIEWS: Negative reviews aren't all bad. They give you a chance to publicly demonstrate how you handle problems and can turn dissatisfied customers into brand advocates by responding to them. 3. REVIEW ORDER: Check how your website or product listing sorts reviews, because if the first review shown is negative you’re hurting sales.  4. FEATURED REVIEWS: Use “featured reviews” - a detailed positive review as the first one that people see. This can increase your sales by up to 20% (!). I worked with a services company to lift revenues by over 20% without spending a dime on new advertising by tackling how reviews work. Using science-backed research - and the scientific method - is a cheat code for scaling (I’ve made a mini-course on how to do it, check it out).

New Ecommerce SEO article: How to use gen-AI + reviews to write product descriptions at scale. In 10 minutes, you can create 250+ descriptions: This is an article that I just wrote for the Search Engine Land site. Reviews are a goldmine of data for ecommerce sites. However, this is a data source that's often underutilized on my sites. Many commerce sites have reviews that contain a ton of information about real customers. Fans of your company, people who have used the product, users will real-life experience. This is the type of content that's perfect for using as a source for product descriptions as users are likely highlighting the product's most important features. By using Screaming Frog's OpenAI integration, you can have the tool extract your reviews, run them through ChatGPT and have it create product descriptions. Here's the process. 1. First you'll need to have Screaming Frog extract the reviews from your site. Navigate to Configuration > Custom > Custom Extraction > Add. Add a new extraction called "Reviews" 2. Then select the "Globe" icon to pull up the visual editor. This will help you create the regex/CSS to extract your reviews. 3. Run a sample product page through the editor. Click your reviews section and look at the "Suggestions" feature. Toggle through these until you find a code snippet that will pull just your reviews. Save this configuration. 4. Next, you'll need to push this extraction to OpenAI. Navigate to onfiguration > API Access > AI > OpenAI. Ensure your OpenAI key is added in "Account Information". 5. Next go to the Prompt Configuration tab and click Add. Name your prompt “Product Descriptions.” In the Page Text dropdown, select Custom Extraction > Reviews. 6. In the "Enter Prompt" field add your prompt. You'll want to tell OpenAI to create reviews from the submitted product reviews. You can click the "Play" button to test the output. 7. Finally, start your crawl by using Screaming Frog on "Spider" mode. When the crawl is complete, go to AI > Product Description in the right-side bar to find your new product descriptions. What I've found is that the product descriptions outputted are generally pretty strong. They take into account a product's most prominent features from reviews and integration them into the actual description. It's worth noting that this content only serves as a STARTING POINT for product descriptions. You 100% need to have a copywriter review the output and makes adjustments. However for commerce sites with thinner resources, this is a good way to quickly generate product descriptions using real-world customer data.

93% of consumers say online reviews influence their purchase decisions. But the way most use social proof actually hurts conversion instead of helping. It's one of digital marketing's greatest ironies. I've analyzed thousands of websites over the past decade and found a consistent pattern: companies add testimonials and reviews to their sites, yet they often sabotage their effectiveness through poor implementation. The psychology is clear: humans are social creatures who look to others when making decisions. But simply sprinkling testimonials throughout your site isn't enough. Here are the common social proof mistakes that kill conversion: ↳ Placing social proof at the wrong stage of the journey Don't show testimonials before establishing what your product actually solves. ↳ Using reviews that sound suspiciously perfect Real reviews have nuance... 4.7 stars is more believable than 5.0. ↳ Showcasing anonymous quotes instead of identifiable people Our brains dismiss "J.S. from California" as potentially fake 🤷🏻♂️ Social proof is most effective when strategically deployed based on where customers are in their decision-making process: ↳ Discovery Use expert endorsements and certification badges to establish credibility ↳ Information Gathering Customer reviews highlighting specific benefits address practical concerns ↳ Decision-making Testimonials addressing potential objections remove final barriers One enterprise client at The Good increased conversions 42% (!!) by simply moving testimonials from their homepage to their decision stage pages. Is your social proof convincing potential customers, or just convincing *you* that you've checked a marketing box?

I started Yotpo because I bought the wrong camera. Not because it was bad. Because it wasn’t right for me. If I’d had the right information from someone with similar needs, I probably wouldn’t have bought it. That moment stuck with me. We built Yotpo on that insight: When people don’t know what to buy, they ask others. That behavior hasn’t changed in 2025, but how we ask has. Our new report, To Buy or Not to Buy, based on +50K data points across 3 global markets, shows exactly how reviews and AI now work together to drive shoppers’ decisions. TLDR: 82% of shoppers say reviews are a critical part of how they decide what to buy 66% hesitate to buy products with fewer than 5 reviews More and more shoppers now turn to AI to summarize thousands of reviews, surface what matters, and help them feel confident hitting “Buy.” For eCommerce leaders, this isn’t just interesting, it’s actually strategic. In the 50s, the 70s, and now in 2025, people still want to know: “Is this right for me?” The brands that win are the ones that help them answer that question clearly, quickly, and with trust. Get the insights here >> https://lnkd.in/emE7i2ex

Trust signals improved conversions by 30% in 2 weeks. Here’s how we turned skepticism into sales in just 14 days. Our partner, a company selling innovative hunting gear designed to cloak the wearer’s bioelectric signature from prey, was facing a major hurdle. Their visitors didn't trust their product. Their product (while effective) was met with a ton of skepticism, especially on first contact. This was affecting their conversion rate, largely because their website wasn’t prominently showcasing reviews, security badges, or other trust signals that could reduce hesitation from potential buyers. To tackle this, we focused on one key element: building trust with their website visitors. We took the following steps: 1. Added customer reviews and testimonials directly on product pages to establish credibility. 2. Displayed security and payment assurance badges throughout the site to reassure users of safe transactions. 3. Conducted an A/B test to measure how these changes impacted the conversion rate. What we implemented was simple, yet incredibly effective. We made reviews and trust signals easily visible and strategically placed across key areas on the website. The results were almost immediate. In just two weeks, we saw a 30% increase in conversion rate. This led to a 34.5% increase in revenue per visitor, amounting to an additional $30,000 in revenue per month. A large number of their skeptical visitors became confident, paying customers. This case is a perfect example of how crucial trust signals are in e-commerce. By addressing hesitation head-on and showcasing credibility, we saw tangible results. A simple reminder: Keep reviews and security badges visible, and eliminate skepticism wherever possible. Have you implemented similar strategies to build trust and improve conversions?

To improve ecommerce product performance: don’t ignore customer reviews. Most brands do next-to-nothing with this valuable feedback. Yet, they are a goldmine because: 1. Customer reviews are generally more honest than surveys. 2. Which means the information in these reviews can effectively inform improvements for headlines, testimonials, content, or even sales pitches. At Enavi we utilize this information through our Human-Obsessed approach, based on the following set of questions: Identifying Pain Points 1 - What issues were customers trying to solve with the product? 2 - Is there a common thread that led users to shop for the products? Recognizing Recurring Features: 3 - Which aspects of the product are repeatedly mentioned, positively or negatively? 4 - How does that compare to what we “thought” was important for users? Noticing Benefits: 5 - Are there any benefits in the customer reviews that we didn’t consider previously? Identifying Outcomes: 6 - Which specific outcomes have customers highlighted? Acknowledging Concerns: 7 - Were there any hesitations before the purchase? Use Cases: 8 - What frequent uses or applications of the product are mentioned? 9 - Do the use cases align with what is mentioned in the product description and key messages? 10 - Could these reviews be harnessed for testimonials? By following this 10-step process, we've effectively enhanced product-specific conversion rates and overall performance. Why does it work so well? Because review mining with a Human-Obsessed focus isn’t just about making adjustments. It’s about building better products and growing your business. Where data ends, human insight begins.

Amazon sellers: every legitimate 1-star review is a test. Option A: Get upset and try to ignore it Option B: Publicly respond (not to argue... but to make the situation right) Each critical review is an opportunity to demonstrate exceptional customer service: - Potential customers see you're attentive and responsive - The algorithm notices your engagement with customers - You gain valuable insights for product improvements - You might even change the reviewer's perspective I've watched sellers turn detractors into advocates simply by acknowledging concerns and offering solutions. Remember that Amazon's review algorithm prioritizes helpful, detailed reviews (including negative ones that provide specific feedback). You can't remove legitimate criticism, but you can CONTEXTUALIZE it with a thoughtful response. The key is to remain professional. Thank the reviewer for their feedback, acknowledge their concern, explain any misunderstandings, and offer a reasonable solution. This approach signals to both Amazon's algorithm and potential customers that you stand behind your products and value customer satisfaction. What's your approach to handling negative reviews? Do you engage or ignore?

𝗬𝗼𝘂’𝗿𝗲 𝗻𝗼𝘁 𝗮𝘀 𝗽𝗲𝗿𝘀𝘂𝗮𝘀𝗶𝘃𝗲 𝗮𝘀 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸. Your reviews are. A survey of 1,000+ shoppers showed: ✅ 99% read reviews before buying. ✅ 97% are influenced by them. ✅ They spend 18 minutes reading 6–10 reviews. ✅ They won’t buy unless you’re rocking at least a 3.9-star rating. And here’s the kicker: 96% think reviews can be fake. But they’re still reading them. Because in 2025, buyers aren’t just buying your product. They’re buying the stories strangers tell about you. And if your review game sucks, your sales will too. So if you’re spending all your time writing clever hooks, but not spending any time getting your customers to write real stories about you? You’re leaving money on the table. Want to sell more without spending more? ✅ Get specific reviews with pros + cons. ✅ Make them from verified buyers. ✅ Showcase them everywhere. In a world where people trust strangers on the internet more than your landing page… Reviews aren’t a vanity metric. They’re your conversion engine.

I've been in ecommerce for 18 years, and have made hundreds of millions of dollars of incremental profit for clients. One of the key factors I see stopping brands from scaling is putting too much emphasis on a tactic. For example: On Amazon, it is widely understood that your page needs to have robust reviews to perform well. This is true. However, brands will often compress this into reviews = money Which is not true. This is where you lose money.  Brands who get fixated here will “do what it takes” to get a review, fast. If reviews=money, then you aren’t going to wait for them to show up organically and Vine takes a little while. Now you're tempted to incentivize your sister in laws friends to write you reviews. This costs you revenue in two ways: 1. Your account is going to get suspended. The largest data company on earth can see what you’re doing 2. Your conversion will go down and returns will go up Good reviews can print money. They help customers validate their search and answer questions before they buy. This increases conversion and reduces returns. How? The best, highest converting, lowest churn goods have star ratings between 3.7- 4.2 1. No one believes a 5 star review- they always look like your mom wrote them 2. There is nothing useful in “This is great”- and your customers probably don’t all agree on what great is 3. 3 and 4 star reviews usually have justification- “I liked this but not that”- This is the money maker. This helps people decide if they care more about this than that. Example: You sell a moisturizing shampoo It is 3.7 stars All reviews mention that it is not moisturizing. But it's also a best seller. How? The clues are in your 3 star reviews “It isn’t moisturizing at all, but it smells great and works fine on my normal hair. Don’t buy it if your hair is dry, but I love it” This works in three ways -Increases conversion by validating purchase decisions from people with normal hair -Reduces returns from those with dry hair because they are aware it won’t work -Tells you how to update your copy and search to maximize sell through Honorable mention- people who don’t like your product will rarely tell you. They will return it and talk about how much it sucks to their friends, not you. Feedback is a gift that you want desperately. This process is what makes reviews valuable on a page. Good reviews can make you money, but bad ones will cost you and this is not based on star rating. Do not hyper focus on a tactic at the expense of your strategy. Shortcuts are often incredibly expensive. #strategy #retail #topretailexperts #ecommerce #amazon