Friday, February 20

🌟 Today’s Highlights:

• Google added a new Scenario Planner to its Meridian toolbox

• Reddit is testing a new AI search feature for shopping

• If AI has been on your radar, here’s how to start learning about it

• 📊 Stat of the Day: Text ad clicks surged year-over-year as classic organic clicks fell across key verticals from January 2025-2026. (Source: Similarweb)

• 💡 Today’s Insight: The new SEO KPI: LLM consistency and recommendation share

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⚡️ Today’s Headlines ⚡️

✏️ Google added a new planner element to its Meridian toolbox. The new Scenario Planner element gives external developers and marketers access to various estimation tools that can help them develop better approaches to campaign measurement.

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🖼️ Microsoft Advertising added multi-image creative to Shopping ads. The new multi-image Shopping ads in Bing search results gives ecommerce brands a richer way to showcase products and capture shopper attention before the click.

🛍️ Reddit is testing a new AI search feature for shopping. The new tool takes community recommendations and matches them with products from some of the company’s shopping and advertising partners.

💡 Today’s Insight 💡

The new SEO KPI: LLM consistency and recommendation share

🗞 TL;DR - As search increasingly shifts from classic blue links to AI-driven answers and recommendations, traditional SEO metrics like rankings, impressions, and CTR no longer fully capture visibility. To address this gap, Search Engine Land suggests LLM Consistency and Recommendation Share (LCRS) as a new KPI for the AI era.

💡 Insight - In many AI and LLM-mediated experiences (e.g., Google AI Overviews, ChatGPT), a site can rank well in search but not appear or be recommended in the answer itself, meaning influence can happen without clicks — and traditional measurement misses it entirely.

LCRS measures how reliably and competitively a brand’s content is surfaced and recommended by LLMs across varying prompts, platforms, and over time — emphasizing repeatability and competitive presence rather than isolated mentions.

LLM Consistency: Tracks whether a brand or page consistently appears across semantically similar prompts, different LLM interfaces, and over time (not just one hit that may be noise).

Recommendation Share: Measures how often the brand is recommended relative to competitors, including first or prominent placements in generated answers rather than buried mentions.

Here’s how you can start measuring this new KPI:

1. Track LCRS over time: Run a set of varied but representative prompts across key LLM platforms regularly to assess consistency trends rather than snapshots.

2. Benchmark against competitors: Measure not just whether you appear, but how often and in what prominence compared with other brands in your category.

3. Automate collection: Manual tracking isn’t scalable — use scripts or tools to execute prompts and parse results, then analyze patterns over days/weeks.

4. Complement traditional SEO: Continue optimizing rankings and traffic; LCRS is additive, showing influence in AI discovery layers traditional metrics miss.

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