We’ve built a solution called DataviCloud LEO, designed to support lean GTM motion, especially. It eliminates the need for multiple tools and makes enrichment-to-outreach completely seamless. Happy to DM you more details.
Hi Ray R., welcome to the community!
Your focus on GTM and revenue ops in the AI space is right up our alley. We’ve been building AI-driven solutions to make discovery sharper and conversions smoother. Happy to share how we’ve helped teams simplify evaluation and pilot cycles. Happy to DM you the details.
Hi Ishika K.. We have come to realize that “well-funded” doesn’t always mean “ready to buy.” So we started layering in a few important metrics to define a sharper ICP and built an end-to-end solution especially for AI SAAS companies. Happy to share more details on DM
Hi Kurk A. This is an existing concern among GTM teams. We faced the same roadblock in finding the right prospects beyond referrals. We ended up building LEO, which addresses this with clarity.
I can DM more details if this interests you
WonSuk Y., We leverage a few key metrics to deliver a detailed company analysis, assign an ICP fit score, and provide the reasoning behind the score, along with potential use cases. I’d be happy to connect and share more details on DM.
We faced this gap between enforcement and ICP fit, so we looked out for a solution and later solved it for ourselves. It enriches based on live ICP signals rather than static filters, and it’s been a game-changer in keeping our outreach relevant.
Hey all,
I’ve noticed our ICP has evolved faster than our enrichment filters. The data we get looks accurate, but not relevant. Anyone else feel their enrichment criteria are still stuck in last year’s buyer profile?