Hey PH Community !
We've been heads down building. Four new things in the works. I want to know which one matters most to you.

RASE v1.0 App Store Intelligence

Tracks how your mobile app appears in AI answers (ChatGPT, Perplexity) and in store search. If you build apps, this tells you where you're visible and where you're invisible.

We were drowning in data. Page views. Session duration. Bounce rate. Time on site. New users. Returning users. Feature adoption. Support tickets. NPS scores.

None of it told us who was about to leave.

We had retention data. We had churn data. But it was backwards. You only knew someone churned after they cancelled. By then, it was too late.

So we looked for a leading indicator. One metric that predicted churn before it happened.

I will go first.

We developed RAISA. A co-pilot for SEO and GEO.

Here is what it does.

It connects to your Google Search Console and Google Analytics 4. It reads your data every day. It watches your rankings, your traffic, your content decay, your competitors. Then it sends you a weekly briefing.

You're building a product.
Your focus is code, features, user experience.
Not meta descriptions.
Not FAQ schema.
Not internal linking.

But content still needs to get done. Docs, landing pages, blog posts, metadata. And if you ignore it, nobody finds your product.

So you have a choice. Spend hours on content yourself. Hire someone who doesn't understand your product. Or let an OS handle it.

We're building ROSE ( Rankfender Fullstack Optimization Engine ) as a Git based library. An SDK you install directly into your repo. It runs on every commit. Checks your metadata. Validates your heading structure. Suggests internal links. Even auto fixes the small stuff.

You have a dashboard. It shows numbers. They look official. You trust them.

Then you open another dashboard. The numbers are different. Now you have a problem. Which one is right? Neither. Both. It depends.

Here is the enigma marketers face every day.

The enigma

Most content never gets cited by AI. I know because we tracked 14,000+ pages across 200+ domains.

But here's what's interesting: a small subset of pages consistently win 80% of all citations. And they follow a pattern.

We reverse-engineered that pattern. Then we applied it to our own content.

The result? Our citations tripled in 90 days.

On May 19, 2026, at Google I/O, the company announced the most sweeping set of changes to Google Search in over 25 years. The core shift? Moving from a box where you type keywords to a control panel where you deploy AI agents to do things for you.

Here is what changed and why it matters for brands.

1. The Era of "Information Agents" has arrived

You no longer have to keep searching for the same thing repeatedly.

For two years, we have been tracking AI citations through third-party tools. We built dashboards. We monitored ChatGPT, Perplexity, and Gemini. We helped publishers understand their citation patterns.

But there has been a gap. No search engine was providing first-party data on how their own AI systems cite content.

On February 10, 2026, Microsoft changed that .

They launched the AI Performance dashboard in Bing Webmaster Tools. The first time any major search platform has given publishers direct, first-party data on how AI systems cite their content .

Here's the problem nobody talks about.

Your data doesn't match. GA4 says one thing. Search Console says another. Your CRM says something else. They're all tracking the same campaign, same time period, and they give you different numbers .

This isn't a bug. It's how the systems are built. GA4 measures sessions and modeled behavior. Google Ads measures ad interactions. Search Console provides aggregated impression data. Your CRM tracks identified leads . They were never designed to agree.

The result? You spend hours trying to "fix" the numbers instead of acting on them.
Imagine this : having an operating system for SEO & GEO, that actually reads your Google Analytics, your GSC, Bing webmaster, treat your data, explain it to you, and ACT!