Hyper-target your market and automatically qualify the leads you generate, so you know who’s the best fit before you reach out.
Generate accurate personas to hyper-target your market.
Create on-demand personas from your new or existing data to understand who your target market is, how it shifts over time, and proactively adjust your outreach content accordingly.
Know who’s a fit before you reach out.
Rapidly qualify and disqualify leads, then prioritize your outreach, both inside and outside your funnels to build a consistent and predictable pipeline that converts.
Filter your inbound to find the "needles in the haystack".
Manage a case of “inbound overload” by creating High-Value Target (HVT) groups to easily focus on leads most likely to become your next customers.
Enhance your ABM (Account-Based Marketing) by knowing which decision-makers and influencers are most likely to know, like, and trust you, instead of spamming the entire account to see what sticks.
Generate hyper-targeted lead lists to maximize the number of qualified leads you generate and reduce the amount you spend on contact data providers like ZoomInfo or LeadIQ. A quality-over-quantity strategy.
Realize the true potential of LinkedIn Sales Navigator by doing hyper-targeted filtered searches and crafting relevant messaging unique to each niche, then using best-fit scores to know who’s worth focusing on. No more spray-and-pray.
Claim the 40% (Mkt Avg.) of unearned revenue in your existing client base by analyzing them to identify cross-sell and upsell opportunities, then delivering personalized offers and matching each client to campaigns that best fit them.
The marketing team becomes the hero when they only pass leads that convert to the sales team. Use the AI to accurately predict whether an MQL is qualified to hand off to the sales team as an SQL.
When experiencing high-volume inbound (a.k.a. “inbound overload”), filter out all the “junk leads” and know exactly who is worth your focus. Save your resources by avoiding false positives and eliminating bad fits.