The Complete Guide for How to Use Otterly in 2026

Otterly.AI is a GEO monitoring tool that tracks how your brand appears across AI search engines like ChatGPT, Perplexity, and Google AI Overviews. You set up prompts, run them against the platforms you care about, and get structured data on whether your brand shows up, how often, and what the AI says about you. This guide covers everything from initial setup to prompt strategy to reading your results.

What Is Otterly and What Does It Actually Track?

Otterly monitors brand visibility inside AI-generated answers. You give it a set of prompts, tell it which AI platforms to check, and it runs those prompts on a schedule, recording whether your brand appears in each response. The output is visibility data you can track over time.

That sounds simple, but the underlying challenge is real. AI search engines don't return a ranked list of URLs. They generate prose answers, and your brand either gets named or it doesn't. There's no position 1 to chase. This makes measurement harder than traditional SEO, and it's exactly why a tool like Otterly exists.

At the time of writing, Otterly tracks across ChatGPT, Perplexity, Google AI Overviews, and Gemini. The coverage matters because visibility on one platform doesn't guarantee visibility on another. A brand that appears consistently in Perplexity answers might be invisible on ChatGPT, because each engine pulls from different sources and weights different signals.

How Do You Set Up Otterly for the First Time?

Getting started in Otterly takes four steps: create a project, define your brand entity, add your prompts, and configure your tracking schedule. The project is basically a container for one brand or client. The brand entity tells Otterly what to look for in AI responses, which usually means your brand name plus any common variations.

Once you've set up the project, you need to add competitors. This is worth doing from the start, not later. Otterly can show you your share of voice relative to named competitors, which is far more useful than raw mention counts. A brand mentioned in 40% of responses sounds good until you find out the category leader appears in 80%.

The most important setup decision is which prompts to track. Otterly lets you add prompts manually or import them via CSV. Most teams start by typing in a handful of obvious queries, which works fine for initial exploration. For production tracking at any real scale, you'll want to bring in a properly structured prompt set rather than building one query at a time inside the tool.

Which Prompts Should You Track in Otterly?

Your prompt set determines the quality of your visibility data. If your prompts are too generic or too branded, you'll get a skewed picture of how you actually appear in AI search.

Good Otterly prompts mirror how real users ask questions, covering a range of intents across the buying journey. Here's how we think about structuring a prompt set for meaningful tracking:

• Category prompts: "What is the best [your category]?" These test whether the AI knows your brand exists at all in its training data.
• Use-case prompts: "What [category] should I use for [specific job]?" These test contextual relevance, not just brand awareness.
• Comparison prompts: "How does [your brand] compare to [competitor]?" These test competitive positioning.
• Recommendation prompts: "Can you recommend a [category] for [persona or need]?" These test whether the AI names you unprompted when helping someone with a decision.
• Problem-solution prompts: "How do I solve [problem your product addresses]?" These test whether you appear in solution contexts rather than just branded queries.
• Feature prompts: "Which [category] has the best [feature you're known for]?" These test feature-level association.

The common mistake is over-indexing on branded queries like "[Brand] review" or "[Brand] vs [Competitor]." Those queries tell you what the AI says once someone already knows you exist. The more important questions are the category and use-case prompts where brand discovery actually happens.

For serious tracking, you need enough prompts per topic and market to produce statistically reliable data. A handful of prompts gives you anecdotes. A properly sized, structured prompt set gives you a visibility score you can act on. If you're building a prompt set from scratch and want research-backed prompts generated from real search data rather than guesswork, BrandPrompts is built specifically for that job and exports CSV files formatted for Otterly import.

How Do You Read Your Otterly Dashboard?

The core metric in Otterly is brand mention rate: the percentage of your tracked prompts where your brand appears in the AI's response. This is your headline visibility score. Track it over time and across platforms.

Beyond the headline number, the useful analysis happens when you break it down. Here's what to look at:

Don't check the dashboard in real time and panic at individual data points. AI responses are non-deterministic, meaning the same prompt can produce different answers on different runs. Trends over weeks and months are meaningful. Day-to-day fluctuations usually aren't.

How Do You Improve Your Visibility After Setting Up Tracking?

Otterly tells you where you stand. Improving that position is a separate job, but Otterly's data tells you exactly where to focus.

If you're missing on category and use-case prompts, the issue is usually earned media. AI engines, particularly ChatGPT and Claude, weight third-party coverage heavily when deciding which brands to surface in category answers. Getting your brand named in industry roundups, comparison articles on authoritative sites, and product reviews on G2 or Capterra matters more than publishing more content on your own blog.

If you're missing on feature-specific prompts, you likely have a content gap. The AI doesn't associate you with a particular capability because there's not enough content making that association explicitly. Publishing detailed guides, case studies, or comparison content that ties your brand name to that feature directly helps here.

If you're visible on one platform but not others, think about the underlying sources. Claude pulls from Brave Search's index, so Brave crawlability affects your visibility there. ChatGPT retrieves via Bing, so Bing indexing matters. Google AI Overviews draw heavily from Google's organic index, so strong traditional SEO still carries significant weight. Platform-specific gaps usually point to platform-specific source gaps.

One thing we'd push back on: don't optimise your own pages for AI at the expense of making them useful for humans. The content formats that AI engines cite tend to be the same formats humans find genuinely useful: clear answers up front, structured headings, comparison tables, real data. Good content strategy and GEO content strategy are mostly the same thing.

What Reporting Can You Get Out of Otterly?

Otterly produces exportable reports that work for client reporting and internal stakeholder updates. For agencies managing GEO for multiple clients, the ability to pull structured visibility data per project is the core workflow value.

The most useful reports to run regularly are share of voice comparisons (your brand versus named competitors across the same prompt set) and platform breakdowns (visibility per AI engine). Both tell a cleaner story than raw mention counts.

For teams that want to go deeper on analysis, exporting raw data and working in a spreadsheet or BI tool gives you more flexibility. You can cross-reference visibility changes with publishing dates, PR activity, or algorithm updates to build a picture of what's actually moving your numbers.

Frequently Asked Questions About Using Otterly

How many prompts do I need in Otterly to get reliable data?

Reliability depends on how many topics and markets you're tracking. As a working guide, fewer than 30 prompts per topic-market combination tends to produce data that's too noisy to act on. AI responses vary run-to-run, so you need enough prompts that random variation averages out. If you're tracking one brand in one market across five topic pillars, you're looking at 150 or more prompts for meaningful signal.

Does Otterly track real-time AI responses or cached ones?

Otterly runs prompts against live AI platforms on a schedule, so the data reflects what the AI would actually say at the time of the run. This means your visibility scores can shift as AI models are updated, as new content gets indexed, and as the platforms change their retrieval behaviour. It's a live signal, not a static snapshot.

Can I import prompts into Otterly from a CSV file?

Yes. Otterly supports CSV import, which is the practical way to load a large, structured prompt set. If you're building prompts manually in a spreadsheet or using a prompt research tool like BrandPrompts, you can export to CSV and import directly into Otterly without re-entering each query by hand.

How is Otterly different from traditional SEO rank tracking?

Traditional rank trackers report a position number: you're ranking 4th for a keyword. Otterly reports a binary outcome: your brand appeared or it didn't in an AI-generated answer. There's no position to track because AI answers are prose, not ranked lists. Share of voice is the closest GEO equivalent to rank position, and it's a percentage of prompts where you appear rather than a spot on a list.

How long before I see my Otterly visibility scores change after doing GEO work?

Expect a lag. For AI engines that retrieve live content, like Perplexity and ChatGPT Search, changes in what's indexed can affect responses within weeks if the new content gets crawled and surfaces in retrieval. For changes driven by training data (the model's baseline knowledge), the lag is much longer because models are retrained on a schedule, not continuously. Earned media coverage that gets indexed quickly tends to move retrieval-based visibility faster than anything else.