Promises top national carriers, names two

AI SEO playbook

Two different fights. Local-intent insurance queries return a Local Pack 92–96% of the time. Commercial queries return an AI Overview about 63% of the time. One is a profile problem, the other is a citation problem.

• Separated the two battles, because they need opposite tactics: personal and local lines are won in the Local Pack, commercial lines are won in AI citations.
• Built line-level and city-level pages for the local book, and rebuilt the Google Business Profile against category, proximity, title and address-in-city.
• For the commercial book, went after earned mentions through LinkersPro — 84% of AI citations trace to earned media and branded web mentions out-correlate backlinks 0.664 to 0.218.
• Ran the Scriblr baseline across ChatGPT, Gemini, Perplexity and AI Overviews against a 22% category median and 44% top quartile mention rate.
• Built out carrier appointments, licensing footprint and named specialisms as structured, citable facts — an assistant recommending an agency names carriers and coverage areas, and cannot cite what is not stated.
• Wrote answer content for the categories buyers actually ask about — bonds, workers comp, coverage limits, claims process — where 29% of customers now bring AI into the journey and 42% of those go on to purchase.

PPC playbook

Insurance search has the highest click-through rate of any vertical at 9.83% and nearly the lowest conversion at 2.64%. The money leaks after the click. So the work goes into the quote path, not the ad.

• Diagnosed the structural problem first: insurance earns clicks better than any other vertical and converts them worse than almost all of them, which means bidding harder makes it worse, not better.
• Rebuilt the quote path, where 84% of insurance forms are abandoned — cut the form to what actually binds, added progressive disclosure, and put a call fallback on every step.
• Split campaigns by line of business, because a commercial general liability search and an SR22 search share nothing except the word insurance and have entirely different economics.
• Built speed-to-first-contact into the routing: shoppers now pull 3.5 quotes each, an all-time high, and 48% of new policies are bought online — whoever responds first is usually the one who binds.
• Moved reporting to cost per bound policy against a ~$900 independent-agent acquisition benchmark, and set the payback window against 92% median retention rather than first-year commission alone.

AI SEO timeline

1. Days 0–30

   Citation baseline across four assistants, GBP rebuild, page architecture and entity cleanup.

2. Days 31–90

   Line × city page grid shipped, carrier and licensing facts structured, first earned-mention wave.

3. Days 91–180

   Mention velocity sustained, citation rate compounds, freshness cycle running on line and city pages.

PPC timeline

1. Days 0–14

   Audit, conversion tracking rebuilt, negative keyword purge, campaign restructure by line of business.

2. Days 15–45

   Quote path rebuilt, progressive disclosure live, speed-to-lead routing in place.

3. Days 46–90

   Budget reallocated on bound-policy data rather than quote-request data.

Targets this programme was set and measured against

These are not reported results. RL Insurance Agency's own reporting has not yet been reconciled against these rows — see how we define a target versus a result.

Where these targets come from