Customer Intelligence Hub | Sales Automation

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Unified Customer Intelligence Hub for Sales Teams

Unified view of customer activity combining CRM, billing, support, and product usage for sales teams.

Sales automation case study featuring integration and reporting.

-18%

Churn Reduction

+22%

Upsell Conversions

Within 7%

Pipeline Forecast Accuracy

Overview

A SaaS company needed a unified view of customer activity combining CRM, billing, support, and product usage. Churn was reduced by 18% and upsell conversions increased by 22%.

Business Context

The SaaS company had grown rapidly, but their customer data was fragmented across multiple systems that didn't communicate with each other effectively. Sales reps were forced to toggle between five to seven different tools — CRM, billing platform, support ticketing system, product analytics, and various spreadsheets — just to understand a single customer's situation before a call, wasting valuable selling time on administrative research. This fragmentation meant that churn warning signs visible in support tickets or product usage patterns went unnoticed by account managers until it was too late to save the customer relationship. Upsell opportunities signaled by increased feature adoption or team growth were similarly invisible to account teams, leaving significant expansion revenue on the table. The executive team recognized that customer intelligence was their most valuable asset, but it was locked in silos that prevented actionable insights from reaching the people who could act on them.

How We Built It

We architected a comprehensive Sales Intelligence Hub that serves as the single source of truth for all customer-facing teams. The foundation is a consolidated data warehouse that ingests and normalizes data from HubSpot CRM, Stripe billing records, Intercom support conversations, Mixpanel product analytics, and internal databases containing contract and subscription details. ETL pipelines run on scheduled intervals to ensure data freshness, with real-time webhooks capturing critical events like support ticket escalations or significant usage changes. The feature usage heatmap visualization shows exactly which product capabilities each customer uses, how frequently, and how that usage trends over time — immediately revealing both power users ripe for expansion and struggling accounts that need intervention. We developed a sophisticated health scoring model that weights multiple factors including product engagement depth, support ticket sentiment, billing payment patterns, and contract renewal timeline to produce an actionable account health score updated daily. The forecast engine analyzes historical patterns in account behavior to predict renewal likelihood and expansion potential with remarkable accuracy. A custom Retool interface presents this intelligence in an intuitive dashboard where reps can see account health, renewal status, upsell opportunities, and the complete customer journey timeline in a single view. Automated alerts notify account managers when health scores drop below thresholds or when upsell indicators trigger.

Challenges

No single view of account health

Missed upsell opportunities

Churn warnings going unseen

Reps jumping across 5-7 tools

Poor qualification

What We Delivered

Unified sales intelligence warehouse

Feature usage heatmaps

Health scoring model

Forecast engine based on historical activity

Account health and renewal status dashboard

Customer journey timeline with upsell opportunities

Tech Stack

Consolidated data warehouse, CRM, product analytics, billing, support, Feature usage heatmaps, Health scoring, Next.js app

Results

-18%

Churn Reduction

+22%

Upsell Conversions

Within 7%

Pipeline Forecast Accuracy

Strategic Impact

The 18% reduction in churn represents substantial protected revenue — customers who would have churned are now being saved through proactive intervention enabled by early warning signals. The 22% increase in upsell conversions comes from systematically identifying and acting on expansion opportunities that were previously invisible across fragmented data sources. Pipeline forecast accuracy within 7% gives leadership confidence in revenue projections, enabling better resource planning and more accurate guidance to stakeholders. Account managers report dramatically reduced preparation time before customer calls because all relevant context is immediately accessible in one place. The health scoring model has shifted the organization from reactive firefighting to proactive customer success — problems are addressed before they become cancellation requests. Customer success managers can now prioritize their time effectively, focusing energy on accounts that most need attention rather than treating all customers equally. The visibility into product usage has informed product roadmap decisions, as patterns across the customer base reveal which features drive retention and expansion. New account managers ramp faster because institutional knowledge about each account is captured in the system rather than residing only in predecessor's heads. The intelligence hub has become central to quarterly business reviews and board reporting, providing data-driven narratives about customer health and revenue trajectory.