Lead Discovery

Reduced drop-off rates by 20% by improving Bitscale’s core lead discovery experience (Find People & Find Companies) to make complex filtering more intuitive and scalable.

Simplified lead filtering, enhanced natural search behavior, and improved preview functionality. Enabling users to confidently search, preview, and refine leads without needing to understand the underlying data structure.

Approx 25% of active users were unable to find desired leads, increasing the user drop-off rate.

Users expressed a strong need for discovery leads in bulk and preview capabilities to reduce the time spent finding and generating leads.

How might we reduce user drop-off while increasing trust and confidence during lead generation?

Based on user research conducted through customer support calls, support tickets, PostHog analytics, and other internal metrics, I identified several key areas that needed improvement: 1. Lead discovery was not intuitive for large number of filters 2. Filters were missing real-world search behavior (synonyms, shorthand, etc.) 3. Cognitive load increased overtime with addition of filters 4. Filter complication related to (include / exclude) logic controls 5. User demands to preview, download lead list, adjust, save, and reuse filter sets

The experience focused on helping users move from intent to action with minimal friction. Filters were designed to reflect how users naturally think about lead discovery, while previews and grid interactions helped users validate results before committing to large imports.

By supporting reuse through saved filters and flexible imports, the system scaled from quick one-off searches to repeatable GTM workflows — without forcing users to rebuild logic each time.

Reduced drop-off rate by 20% by reduced hesitation at the moment of search, helping users move faster from intent to confident action.

1. Faster lead discovery despite increased filter depth 2. Improved trust through preview-first workflows 3. 10% higher reuse of saved filters across GTM workflows 4. Reduced confusion around inclusion and exclusion filter logic 5. Consistent experience across Find People and Find Company

Based on my learnings and the design constraints during this project, there are several areas I would improve in future iterations:

1. Introduce a full-page filtering modal to replace the current filtering experience. 2. Replace search-specific credits with a unified global credit system. 3. Increase the lead import limit from 100, enabling teams to work with larger prospect lists more efficiently.