When we speak to our clients about how people find and engage with their website, access to data is sometimes their first challenge. With the current systems they have, they might not know which AI platforms are sending visitors to their site, or where their organization is being cited and recommended in those AI-generated answers.
But having access to more data only solves part of the problem. The harder part is connecting those different data points to build a broader narrative around what’s happening, why it matters, and what it means for your overall digital strategy.
In a recent CMS Critic article, Matt Garrepy described the approach to this challenge as the shift from an AI visibility “scoreboard” to a “playbook.” There are a few key components to that shift that we’ve incorporated into our AI Visibility Suite:
1. The first is that, yes, you do need the scoreboard. Those scores and charts are how you establish your baseline, and going forward, that view serves as your summary of progress.
Our GEO Suite Dashboard brings that information together in one place. You can see your overall GEO score, citation performance, keyword visibility, answer readiness, and more. It gives you a quick way to see where you stand across your AI visibility strategy without having to dig into each individual report.
We’ve also explored lightweight options that help that dashboard tell a more complete story at a glance. The ai12z Beacon, for example, is a small piece of code that sits on your website and captures when someone arrives from an AI answer engine. This adds real referral and engagement data to the analysis, including which AI platforms are sending visitors to your site, which pages they reach, whether they interact with your search or digital assistant and, if so, what they ask, and how that traffic is trending over time.
- As we mentioned before, the quantity of data is only part of the picture. The second component in this shift is turning those insights into action by interpreting the findings and lessons behind those scores together. Each report can identify its own set of issues and recommendations, but that can quickly leave you with a lot of separate things to work through.
The ai12z Action Plan pulls those findings into one list, removes duplicates, and prioritizes what to work on first. When you run the analysis again, it can also show what’s been resolved since the last time and what still needs attention.
- Next is bringing in data and context beyond the numbers. AI search is driven by questions, and those questions don’t necessarily stop when someone reaches your website. If a visitor arrives from ChatGPT and then engages with your search bar or digital assistant on your website, we can connect where they came from and where they landed with what they asked once they got there.
That direct phrase or question from the user adds another layer of context to your strategy. Over time, those questions can reveal patterns in what your audience wants to know and give you another source of information to feed back into your AI visibility strategy.
This creates a broader feedback loop, that’s much more dynamic and informative than a static scoreboard that measures the same set of signals over and over again. If you’re trying to build a data-centric digital strategy, you need more than a snapshot of where you stand. You also need the tools to turn those insights into action.
Read more on Matt Garrepy’s perspective of this shift in his article: “ai12z Takes AI Visibility from Scoreboard to Playbook, Turning AI Search Insights into Action" and a closer look at ai12z’s AI Visibility Suite.