Reputation

Ask five different AI engines about the same business and you may get five different answers. Not because the business changed, but because each engine relies on different sources and weighs them differently. One of the biggest misconceptions is that AI is just looking for the highest-rated business. In reality, it's piecing together context from reviews, business listings, and other trusted sources to decide which brands to recommend. Giving AI better signals is the key. We explore what those signals are in the latest article from our Mastering GEO series 👉 https://lnkd.in/gWEWg66F

A star rating tells you what a customer thinks. It doesn't tell you why. Westfield receives over 24,000 reviews, with nearly half including a comment. That's a lot of feedback, but ratings alone weren't giving their team the full picture. They wanted to understand the story behind the score, the specific reasons driving customer satisfaction and dissatisfaction, not just the numbers. So they turned to a simple, gamified feature in our survey module called the Comment Strength Meter, which encourages customers to write longer, more detailed comments. The result was a 40% increase in average comment length, the equivalent of gaining 12,000 additional surveys worth of commentary. As Michael Scarfe, Head of Research & Measurement, Analytics, Insights & Research at Westfield, put it: "The extra commentary has sharpened our ability to understand key drivers of both satisfaction and dissatisfaction." This small product tweak led to a meaningful shift in what their data could tell them. Scroll for the full story and visit our website for more customer success stories.

A few weeks ago, we launched the GEO Readiness Audit. It's built on a simple but uncomfortable truth that today, a brand can rank well on Google and still be almost invisible to AI engines. Ranking and being recommended are not the same thing anymore. Find out where your brand stands 👉 https://lnkd.in/gYViEA3q

Outdated location data is quietly costing multi-location brands their customers. Imagine a prospective patient asking Google's AI Overview for the nearest urgent care. It returns an address that closed eight months ago, but the patient doesn't know it's closed. So they drive there, find nothing, and end up booking with a competitor. Stories like this are happening to multi-location brands every day, and most don't realize it until the damage is done. Why does this happen? AI pulls from dozens of sources at once, including listings, your website, and old press mentions. One outdated source and it can confidently get the answer wrong. What's the real cost? For an 80-location chain, just 10% with one bad data point means 8 daily chances for a customer to hit a dead end. What can you do to fix it? Here's what we recommend: 💡 Audit listings quarterly 💡 Add structured data to your site 💡 Monitor what AI says about your locations 💡 Centralize data to one source of truth Our latest Mastering GEO episode breaks this down in full 👉 https://lnkd.in/g9KyhasA

We sat down with the team at St Austell Brewery to talk about how they're using Rep Score to bring more consistency to every pub, hotel, and restaurant they operate. In the interview, the team shares why they stopped looking at reviews location by location and started using a single benchmark to help managers understand performance, prioritize improvements, and keep teams aligned around a common standard. It's a practical example of what reputation management looks like when it's embedded into day-to-day operations.

For twenty years, marketers built their strategies around ten blue links. Today, 50% of consumers are starting their path to purchase inside an AI tool, getting answers before they ever click a search result. The mechanics of discovery have changed. AI isn't just looking at your website. It's piecing together information from reviews, business listings, location pages, and trusted third-party sources to decide which brands to recommend. For multi-location brands, showing up in AI-generated answers requires a different playbook. That's why we created Mastering GEO, a 10-part series exploring what Generative Engine Optimization actually looks like in practice. We cover everything from measuring your visibility across major LLMs to strengthening the signals that influence AI recommendations. The first four episodes are live now 👉 https://lnkd.in/gZsK35A7

60% of online searches now end without a click to a website. The way people discover brands is changing, and it's happening faster than most marketing strategies can keep up with. As our CTO Anuradha Choudhury writes in a new piece for The AI Journal, SEO is no longer the ceiling of your digital strategy, it's the floor. As AI-powered search becomes part of how people research and choose brands, organizations need to think beyond rankings and start understanding what drives visibility in AI-generated answers. If you're trying to make sense of what Generative Engine Optimization (GEO) means in practice, Anu breaks it down clearly here 👉 https://lnkd.in/gJK7uPeD 

Getting reviews isn't the hard part. Knowing what to do with them is. When you manage dozens of locations, feedback from individual sites can quickly become disjointed. That was the challenge St Austell Brewery was facing. They weren't struggling to collect reviews, but they needed a way to unify that feedback into a single, shared standard every team could work toward. Rep Score provided a common benchmark that lets their teams see how each location is performing, compare against local competitors, and focus on the service improvements that move the needle. Read the St Austell story and lean more about Rep Score 👉 https://lnkd.in/gdJfGG2m

More customers are getting answers before they ever click a search result. For years, marketers built their strategies around keyword rankings, the local map pack, and the top three blue links. Today, the path to discovery is changing. In the recent Reputation Without Boundaries webinar, our experts explain how AI engines evaluate brands, why traditional search performance doesn't always translate to AI visibility, and what multi-location organizations can do to improve how they show up in AI-generated answers. Watch the preview below, then catch the full session on demand here 👉 https://lnkd.in/gaJ49mpe

Yesterday, we introduced the GEO Readiness Audit. Here's what it measures. It evaluates whether AI engines can accurately understand your brand and whether they can consistently find, access, and trust information about your locations. For multi-location organizations, knowing there's a visibility gap is only half the picture. Knowing which locations are driving it, and where to focus first, is what makes that information actionable. That's what the GEO Readiness Audit is built to do. Read the full announcement 👉 https://lnkd.in/gZF3Hd-T