How to Utilize Online Reviews

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?

Poor customer feedback systems = poor customer experience 😩 → Plus, research from Product Marketing Alliance found companies with structured feedback programs see 8-12% higher win rates. Who doesn’t want that... But sending random surveys won't cut it. You need a systematic approach that connects insights to action (and ultimately revenue). — I partnered with the Survicate team for this post (and a series on how I'm using Survicate in my own product) because they’ve built the most complete toolkit for capturing, analyzing, and actioning customer feedback in HubSpot of the integrations I’ve seen. The AI powered research assistant is 🔥 You can also get double the survey responses (for the same price) by emailing 'STUART' to the Survicate team when you signup by the end of April. — Here's a playbook to get started building an automated customer feedback engine in HubSpot (that will increase reviews and escalate problems): 1. Create a condition-based feedback survey in Survicate Question 1: "How happy are you with [product name]?" → Type: Rating Scale (1-5) IF High Scores (4-5): Question 2: "What do you love most about [Product]?" Type: Open text Question 3: "Would you be willing to help others like you by leaving a public review?" Type: Single answer selection IF yes to providing a public review - show thank you screen with link to 3rd party review website. IF no to providing a public review - thank respondent for their time. IF Low Scores (1-3): Question 4: “What is the main reason you aren't satisfied with it?” Type: Open text 2. Set up your automation workflow: ⚡️ Trigger: When the synced property value for your satisfaction rating is updated. → Has completed: Property value changed → Property name is Latest Satisfaction Rating → New value: Latest Satisfaction Rating is known 🛎️ Action 1: Send Slack notification → To channel: #customer-feedback → Message: 💡 New satisfaction score of {{ latest_satisfaction_rating }} submitted 🌴 Branch: check the branches in order → High Scores when “Latest Satisfaction Rating” is: IF High Scores (4-5) 📧 Action 1: Send review request email → To: Enrolled contact → Template: Review request → Email Content: Reference recent score and interest in providing a public review with links to preferred 3rd party review platforms. ✨ Action 2: Add to static list → List name: “Evangelists” → Optional Update lifecycle stage to Evangelist if used* ✅  Action 3: Create task → Title: Case study outreach → Type: Todo → Assign To: Contact Owner → Notes: Reach out to discuss a case study IF Low Scores (1-3) ✅  Action 1: Create task → Title: Engage dissatisfied customer → Type: Email → Assign To: Contact Owner → Notes: Reach out to address customer feedback One Survicate customer using this playbook improved their Trustpilot rating from 4.2 to 4.8 and generated 1,000+ responses in a single day 🔥

And...we're back! New year, new #PMMHacks 🚀 This week, let’s talk about using customer reviews to craft web copy or content that 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 resonates. Knowing what your customers say about your product—and why they like or dislike it—is gold. But sifting through hundreds of reviews on sites like G2 can take hours (or days). Here's something to try. This one comes from Steven Peters 🔥: ✅ Rows.com (specifically the RowsX Chrome Extension) ✅ ChatGPT (linked to Rows) Let's say I want to optimize my company's homepage, but I want to understand what our customers say they value about the platform before writing. I start by pulling reviews from G2 into Rows using the Chrome Extension. Instead of manually going through each review, I can use enrichment tasks to extract insights like (more on this below): • Sentiment: Positive reviews highlight “team collaboration.” • Primary Use Case: Customers love it for “deadline tracking.” • Value Proposition: “Simplifies complex workflows.” (🚨 NOTE: Keep in mind that AI-generated results may need some validation/corrections). Here’s the Step-by-Step (huge shout out to Steven Peters for this guide!): 1️⃣ Go to G2 Search for the product you’re writing about—or even your competitors. 2️⃣ Extract Reviews with RowsX Click the RowsX extension and hit “Open in Rows.” Rows will auto-generate a spreadsheet with all available reviews. Repeat this for multiple pages—aim for at least 100 reviews. 3️⃣ Link ChatGPT to Rows This integration unlocks enrichment tasks to analyze and categorize your data in the spreadsheet. 4️⃣ Extract Key Insights (using enrichment tasks) • Sentiment – Make a new column called "Sentiment" and use the prompt SENTIMENT_ANALYSIS_OPENAI(column) to have ChatGPT tell you if the review is mostly Positive, Negative, or Neutral. • Primary use case – Make a new column called "Primary use case" and use the prompt CLASSIFY_OPENAI(column, "Deadlines, Communication, Scope Management, Goal Setting, Team Collaboration", false). *Note that Steven did some legwork upfront to arrive at five potential use cases. He could add to, remove from, or amend the list as needed. By adding "false," you are telling the AI to choose the most applicable list item for each review. • Value proposition – Make a new column called "Value prop" and use the command EXTRACT_OPENAI("value proposition", column) to have AI extract a potential value prop from the "what do you like" (C) or "what problem did you solve" (F) columns. And BOOM 🔥, you can save hours of effort on customer research and created a strong foundation to kickstart upcoming messaging work. Video explainer from Steven Peters here: https://lnkd.in/ex8SWPVp Give it a try, and let me know how it works for you!

Reviews are more than social proof. They’re your best copywriters. Let me explain 👇 Most brands just throw reviews on a PDP and forget about them. Here’s a better idea: turn your best reviews into full email flows. Here’s how: • Take your top 10 5-star reviews. • Label what problem each one is solving. • Build an email around each. Examples: • Review: “Finally something that fits my wide feet!” → Subject: “Got wide feet? We made this for you.” • Review: “I was nervous buying shoes online…” → Subject: “She doubted it too — until she tried this.” • Review: “Works even with my 3 toddlers running around.” → Subject: “Kid proof. Mom tested.” You’re not showing off. You’re letting real people tell your story. Let your customers do the talking. It comes across more real than anything you could write yourself.