A performance team that understands both auctions and a regulated, slow-converting product.
Insurance has a long path from first click to bound policy, so we map every step a buyer takes: ad view, quote start, quote complete, application, and issued policy. We set the campaign to optimise toward the deepest event your tracking can confirm, usually a completed quote or a verified lead, not a raw form fill. This keeps the demand-side platform learning from outcomes that actually correlate with revenue.
We assemble audiences from first-party signals like quote abandoners and existing customers, plus contextual targeting against finance and life-event content. For sensitive lines we avoid health and other restricted inference categories and follow the ad platform's insurance and consent rules. A server-side or consent-aware tag setup keeps measurement working as third-party cookies and tracking get tighter.
We start with controlled manual or target-CPA bidding while the platform gathers data, then move to automated bidding once conversion volume is stable. Frequency caps stop the same prospect from seeing the ad dozens of times, which matters in a considered category where over-exposure feels intrusive. Budgets are split across prospecting and retargeting so you are not paying premium rates to re-reach people who already know you.
Insurance buyers hesitate over price, trust, and claim reliability, so creative speaks to those objections directly rather than chasing clicks. We run variations across formats, native, display, video, and connected TV where it fits, and match each ad to a focused quote or comparison page. Then we read the funnel weekly, cut what does not move quotes, and shift spend toward the audiences and placements that produce issued policies.
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Dcrayons is a digital marketing agency founded in 2016, with our head office in Delhi and a US entity, working across SEO, PPC, social, content, e-commerce, and web. For insurance startups we treat programmatic as one part of a full funnel: prospecting to build awareness, retargeting to recover abandoned quotes, and analytics to prove which spend actually produces policies. We are direct about what programmatic can and cannot do for a new insurer, and we build for compliance and measurement from the first campaign rather than bolting it on later.
We optimise to quotes and issued policies, not vanity impressions, so spend ties back to underwriting outcomes you care about
We set up consent-aware, server-side tracking so measurement holds up as cookie and privacy rules tighten
Real questions people ask Dcrayons about programmatic ads for insurance startups. Honest answers, no jargon.
It is the automated buying of digital ad inventory, such as display, video, native, and connected TV, through real-time auctions on a demand-side platform. Instead of negotiating fixed placements, you target audiences by intent and life stage and let the system bid for each impression. For an insurance startup it is a way to reach in-market shoppers at scale while controlling cost per quote.
Search and social ads run inside one walled platform, while programmatic buys across many publishers, exchanges, and formats through a single demand-side platform. Programmatic gives you broader reach and formats like connected TV and native that search does not offer. Most insurance startups run both: search and social to capture active demand, programmatic to build awareness and retarget across the open web.
No. Major ad platforms restrict targeting based on health conditions, medical history, and other sensitive categories, and insurance is treated as a regulated vertical. We rely on contextual targeting, life-event signals, and first-party audiences such as quote abandoners instead. Staying inside these rules protects your ad accounts from suspension and keeps the program running.
Budget depends on your lines of cover, geography, and competition, so there is no single right number. We usually recommend starting with a test budget large enough to gather real conversion data on a few priority audiences, then scaling the placements that produce quotes and policies. The goal early on is to learn your cost per quote and per issued policy before committing larger spend.
Expect a learning phase of several weeks while the platform gathers conversion data and the bidding stabilises. Insurance has a longer consideration cycle than impulse purchases, so the gap between first ad view and a bound policy is often weeks, not hours. We track upper-funnel signals like quote starts early so we can adjust before the full policy data comes in.
We measure against funnel events you can verify: quote starts, completed quotes, qualified leads, and issued policies, then work back to cost per outcome. Impressions and clicks are early indicators only and never the goal. We use consent-aware, server-side tracking so attribution stays reliable as privacy and cookie restrictions increase.
A free, no-obligation readout and a 90-day plan to improve.