Our clients range from fast-moving startups to global companies, all with one goal: design that makes them stand out.
Overview
NovaTech had a 6-person sales team but only 2 were consistently hitting quota. The problem was not closing ability � it was pipeline. Reps were spending most of their day manually researching prospects on LinkedIn, building lists in spreadsheets, and guessing who to call next. We built an AI system that scrapes ideal customer profiles from their best existing clients, identifies lookalike companies, enriches contact data from multiple sources, and scores each lead based on buying signals � delivering a ranked list of ready-to-contact prospects every morning.
Challenges
Lead quality was the critical factor. Flooding reps with thousands of names would have been worse than useless. We spent the first two weeks analysing their closed-won deals to build an accurate ICP model. The intent scoring layer � tracking job postings, tech stack changes, and funding announcements � required integrating 4 different data providers. Getting the scoring threshold right took multiple iterations with the sales team.
Conclusion
Within 90 days, the average rep went from 15 qualified conversations per month to 47. Two underperforming reps hit quota for the first time. Total pipeline value increased 2.8x without adding headcount. The VP of Sales called it the single biggest productivity unlock in the company history.
