I Tracked 39 Brands on Momentum. Google Won.

I built a brand tracker. 39 brands. 8 categories. Each one scored on momentum. Google came out on top. As I studied the data, I stumbled upon a few interesting stories about which brands are gaining attention — and which ones aren't.

Here's how it happened.

I've always been a data nerd. Fifteen years in market research will do that to you. But AI changed what's actually possible for one person to do.

I started experimenting with data analysis using AI. I pulled public data sources: Google Trends data, stock performance, Wikipedia pageviews. Even my own personal data (1.67 million rows of it!).

I didn't have a clear direction in mind when I started — I just wanted to explore different data sources and find interesting stories. And one story that emerged was a story around brand momentum. This led me to creating my own mini brand tracker and building out a Brand Check-In page to highlight the stories I stumbled upon.

Why momentum?

Momentum is the signal that matters now. By the time headlines catch up, the shift already happened. This isn't about who's "winning" — it's about catching signals before they become stories.

I wanted to see what happens when you blend multiple sources: Google Trends (what people search), stock performance (where money flows), Wikipedia pageviews (cultural curiosity), and news coverage (media attention). Each source tells part of the story. Together, patterns emerge.

The methodology

This tracker mixes brands, parent companies, and flagship products. That's intentional — it reflects how attention actually shows up in culture, even when ownership structures differ.

I picked 39 brands across 8 categories. These are brands I follow, admire, and find interesting — that's why they're here. Each brand gets a momentum score based on these signals, not a definitive ranking of brand value. Each signal was normalized and blended into a composite momentum index, emphasizing recent change over absolute scale.

A few notes on how I approached this and what I noticed:

• Bigger brands naturally got downweighted. Apple and Microsoft don't spike in search because they're always there. Stability looks different than momentum.
• Viral moments matter. A TikTok video or controversy can spike Wikipedia views 50x overnight. That's real signal, but it's noisy.
• Some brands don't have their own stock. Chipotle does. But P&G owns dozens of brands under one ticker. We note where this applies.
• We split OpenAI and ChatGPT. Brand vs company. Wanted to see how attention differs. (It does.)
• No sentiment data yet. We're tracking attention, not feelings. Adding sentiment is on the list for v2 — it would help ground the chatter.
• Attention ≠ trust or usage. High attention doesn't always mean positive adoption — controversy and curiosity can inflate visibility without long-term value.

The top 5 momentum scores

🎉 Drumroll please...

Out of 39 brands, these 5 rose to the top. Here's who's seeing the most momentum right now.

This tracker prioritizes momentum and cultural signals over financial scale. Use directionally, not definitively. Based on public data sources. Full table available on the Brand Check-In page.

• Brand Score: Overall position combining all signals — the cumulative picture
• Momentum: Recent direction — is it rising (🔥), steady (✅), or navigating change (🔄)?
• Stock (5yr): % change in stock price from Dec 2020 to Nov 2025 (or from IPO for newer companies)

A few takeaways:

Google — Dominant across multiple industries. They weren't seeing a lot of AI buzz at first, but that shifted toward the end of the year as they released newer versions of Gemini. They keep expanding their capabilities.

Apple — Ecosystem loyalty is unmatched. Boring is profitable for a reason.

Meta — Remarkable comeback from 2022 lows. Reels and AI bets seem to be paying off. The whiplash from "everything about metaverse" to "everything about AI" is real.

Claude AI — My favorite AI partner (yes, I'm biased). Taking a different approach with privacy and safety. Not the biggest, but has momentum. Bias aside, Claude's placement is driven by growth in search, Wikipedia views, and media mentions — not personal preference.

Costco — Cult status. Good deals, high quality, trusted. They've made private label cool and stuck by values that resonate with their customer base.

Interesting that tech rose to the top. That tells its own story about where attention is flowing right now.

Stories that emerged

The fun part: findings lined up with things I'd already been noticing and writing about. And some new insights emerged!

Millennial brands navigating change. Lululemon, Target, Nike — cultural darlings facing new headwinds. The data showed it before the headlines did.

Recession-proof brands holding steady. Costco, Walmart, Kroger quietly gaining ground. Value holds steady when things get uncertain. Everyday needs beat discretionary spending.

AI is hitting peak cultural relevance. It's everywhere — in headlines, in tools, in conversations. ChatGPT has 127M Wikipedia pageviews (as of Nov 2025) — the most looked-up brand in the dataset. Claude has the fastest momentum growth.

Streaming fatigue — or maturity? Every major streamer is down 30-50% in search interest over 5 years. But that might mean they've hit mainstream. When something becomes ubiquitous, people stop searching for it. Except Spotify, which is up 62%. Audio is seeing the most momentum in the category.

Why this matters to me

For someone who loves data and AI, this is the dream. I'm finally able to dig into questions I've always been curious about — without needing a team or a budget.

AI made it possible to process more data, spot patterns across sources, and actually build something to explore it. A year ago this would've taken months. Now it takes curiosity and stubbornness.

Go explore

See the full tracker. 39 brands. 8 categories. 5 years of data.

→ See the Brand Check-In

A note: This tracker reflects changes in public visibility and attention — not brand equity, sentiment, sales, or financial performance. Scores are directional, not definitive. Financial data is included as context, not performance analysis. The goal isn't perfect precision — it's catching patterns early.

What patterns are you noticing that nobody's talking about? I'm always curious.