I ran Audience Loop on two scrappy lists last week—a Shopify customer file + newsletter subs, and a mixed batch of event leads split between HubSpot and Google Sheets. It felt like handing the boring parts to a capable assistant and getting back something I could actually launch.
I pulled the sources in, let the AI agents clean/normalize/dedupe/validate emails, and used the column-level prompts to enforce “company-domain only” emails and add a quick “role seniority” field. Identity resolution mattered: after a second pass and tiny prompt tweaks, my custom audience match rates jumped (Meta 43% → 67%, Google 39% → 58% in my case). From there I synced to LinkedIn/Meta/Google for paid and exported a clean CSV for our email tool.
The “always-on loop” is where it clicked. I checked their in-app analytics for list quality and match rate, nudged a few inputs, re-enriched, and re-synced the same afternoon—no rebuilding. Downstream, our warmed lists behaved better: CPA dipped ~14% over two weeks and CTR ticked up ~9%. Bonus: it surfaced ~11% role/invalid emails I’d been dragging around, so suppressions got cleaner before they hurt deliverability.
It’s early, but it didn’t get in my way. I’d personally love simple alerts (e.g., “match rate dipped below X%”) and more destinations as they ship (TikTok/Reddit when ready). The free plan with credits was enough to trial it on a real segment without ceremony.
If you’re stuck between duct-taped spreadsheets and an overbuilt CDP, this is a practical middle path. My first “show me” audience: high-LTV repeat purchasers + recent webinar attendees, enriched for seniority, filtered to company domains, suppressed for role emails—then loop, tweak, and re-sync.
iCustomer
Hi Product Hunt, Abhi here, founder of iCustomer.
I've worked on growth with data for more than a decade, for brands like Google, AmEx, Nike, and Target, and then as a founder. I started an enterprise CDP in 2015 and sold it. That taught me something uncomfortable: collecting the customer data was never the hard part. Every company I worked at had a CRM, a data warehouse, and a stack of dashboards.
Nobody had anything that decided what to do each day, by audience, by cohort, or 1:1. And after all the ad budget was spent, there was no learning and no memory. Same mistakes next quarter.
Growth Brain is that layer. It learns who your best audiences are, decides who to reach, when, and in which channel, runs the plays in the tools you already use, and proves what worked, causally, not by last-touch. It proposes every move and you approve it in Slack. Every action is traced, so you can always see why it did what it did.
Under the hood it's an agentic harness built around growth team roles, so the agents work alongside your people rather than around them. A self-learning context layer keeps your brand, systems, and audience knowledge in sync, with trust and governance built in.
Give it a goal, or a specific target. It keeps working while you're away and comes back smarter.
It's free to start. I'll be here all day. Tell me what's broken in your growth stack and I'll tell you honestly whether we fix it.
Really proud of what the team is building here.