TAPS-Tech provides B2B SaaS companies with machine‑learning solutions that both optimize lead qualification and prevent customer churn. Their Lead Optimization system analyzes historical sales data to rank high‑probability leads, delivering sales increases of 20% or more, while the Churn Prevention model predicts subscription cancellations up to 11 months in advance, helping clients achieve retention rates above 95%.
Funding
Funding not disclosed
Founders
Product
Problem
Many B2B SaaS companies waste sales and customer‑success resources on low‑probability leads and experience unexpected subscriber churn, which inflates customer‑acquisition costs and reduces recurring revenue.
Solution
TAPS-Tech applies proprietary machine‑learning algorithms to historical sales data and SaaS usage patterns to rank leads by conversion likelihood and forecast churn up to 11 months ahead. The lead‑optimization model surfaces high‑conversion prospects, allowing SDR teams to focus on the most promising opportunities without increasing headcount. The churn‑prevention model generates early warnings for at‑risk accounts, enabling customer‑success teams to intervene with targeted actions before subscription termination. By integrating predictions into existing CRM and support workflows, TAPS‑Tech helps companies increase revenue, improve retention, and accelerate recovery of acquisition costs.
Target Audience
Primary customers are B2B SaaS companies with annual recurring revenue between $10 million and $100 million that rely on SDR and customer‑success teams to drive growth and retention.
Features
- Lead scoring engine that analyzes past sales outcomes to rank inbound leads by predicted conversion probability
- Churn prediction model that detects usage‑pattern declines and alerts teams up to 11 months before potential cancellation
- Seamless integration with Salesforce and other CRM platforms for automated lead assignment and churn alerts
- Dashboard visualizations showing lead rankings, conversion forecasts, and churn risk scores for strategic decision‑making
- No additional full‑time employees required; the solution works with existing sales and customer‑success staff