If lead scoring feels like duct tape and your AI visibility dashboard keeps flattering you, this issue rewires how your stack earns pipeline.

This week's edition covers:

  • Kevin's Take: lead scoring was a workaround from day one, and agents just made the whole scaffolding obsolete
  • The Signal: Your AI visibility score might be flattering you, plus why ChatGPT Ads is quietly pulling in advertisers faster than anything else
  • Tools & Tactics: simulating a campaign on every customer before you spend a dollar, and one marketer's live test of replacing his CMS with Claude Code
  • Quick Links: 2026 marketing salary benchmarks from 1,100 job posts, how AI is rewriting the way buyers see your pricing, a new protocol that lets AI agents through your bot defenses

Kevin's Take

Lead scoring was always a workaround. Agents make it obsolete.

I've been thinking about lead scoring as a workaround for the limits of the old martech stack, and Phil Gamache's piece on why lead scoring might be martech's longest-running bad idea finally names something I think most of us have quietly known for years. We built scoring models because we couldn't actually have a conversation with every lead at the top of the funnel, so we invented a proxy, points for a whitepaper download, points for a job title that matches an ICP template, points for opening three emails in a quarter, and we told ourselves that if we weighted it right the math would spit out the people worth talking to.

The thing is, that whole system was a compromise born out of scale constraints, not out of any real belief that visiting a pricing page twice means someone is ready to buy. Phil points at Drift's old promise around conversational marketing and that 8X homepage experiment where declared intent beat behavioral scoring, and I think he's right that we're finally at the point where the compromise isn't needed anymore.

What I keep coming back to is that an agent at the top of the funnel can just ask. It can ask what someone is trying to solve, who else is involved on their side, what their timeline looks like, what they've already tried, and it can do that at scale in a way that an SDR team of forty people never could. That's not a scoring model, that's a qualification conversation, and the output isn't a number between 0 and 100, it's a transcript and a decision we can act on. The MQL as a handoff artifact starts to look pretty thin when the alternative is a dialog that already knows the budget range and the two competitors on the shortlist.

One thing I've found helpful when we're thinking about where to spend demand gen energy is to just run the test. If I were running demand gen right now I'd put a small experiment up this quarter where one segment goes through the normal scored path and another segment hits an agent that just asks. We can compare the pipeline conversion, the cycle time, and the quality of the sales conversation on the other side. My bet is the scored path doesn't win that comparison, and once you've got data your own team collected it becomes pretty hard to go back to defending points for an ebook download.

That's it for this week. Talk soon.

— Kevin Kerner, CEO, Mighty & True

The Signal

Why AI visibility scores hide whether brands get chosen (1 min read)

Foundation Marketing ran 21 prompts twice across ChatGPT, Claude, Gemini, Perplexity, Google AI Overview, and AI Mode to test ClickUp's visibility, finding that showing up in results and actually getting recommended are very different outcomes. The study highlights significant variance in how the same brand appears across AI surfaces.

Why it matters: Your AI visibility dashboard might be lying to you about whether you're actually winning the recommendation, not just the mention.

ChatGPT ads are outpacing every other platform in new advertiser growth (1 min read)

Original analysis of 2 million company websites finds ChatGPT Ads adoption accelerating faster than Meta, LinkedIn, Reddit, Snapchat and X combined in new daily pixel installs, with over 15,000 advertisers detected in the platform's first six months.

Why it matters: If you haven't tested ChatGPT Ads yet, this data suggests your competitors are already there and the channel is scaling faster than any other platform you're tracking.

Tools & Tactics

Uniphore builds a personal AI model for every customer (1 min read)

Uniphore launched Marketing AI, which builds a per-customer digital twin using a small language model fine-tuned on that individual's data to predict behavior and simulate campaign outcomes before budget is committed.

Why it matters: If you're tired of guessing which segment will respond to a campaign, this points at a future where you can simulate the outcome on each customer before you spend a dollar.

A marketer rebuilt his Webflow site with Claude Code and cancelled it (1 min read)

A B2B marketer shares his first-person account of rebuilding his $20K Webflow site from scratch using Claude Code, then cancelling his Webflow subscription entirely.

Why it matters: If you're paying thousands for a CMS, this is a live case study on whether AI coding tools can now replace that line item in your stack.

Work with us — Growth Marketing

Need pipeline this quarter, not next year? Mighty and True Growth Marketing builds full-funnel campaigns for B2B tech companies. Demand gen that actually compounds, not decks that look good.

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