Brooke Hattie · Mar 26, 2025 · Case Studies
About this engagement
Our client's CEO and founder had no real-time view of how the business was performing. Reporting was fragmented and pieced together by hand, so trends were hard to read, revenue swings hard to diagnose and decisions slow.
They brought us in to rebuild their analytics and reporting so leadership could see what drives revenue and act on it.
The Challenge
The company's analytics and reporting didn't give a clear, accurate picture of what drove revenue. Leadership couldn't tell why certain metrics were moving, whether pipeline gaps came from sales execution or demand generation, or which opportunities to prioritize.
Forecasts lacked precision, which made planning hard, and without real-time reporting the team was reacting to problems instead of adjusting its go-to-market strategy ahead of them.
The Solution
We rebuilt the client's analytics and reporting framework so leadership has the insight it needs to grow revenue.
At a high level, here is what changed:
| Before | After | |
|---|---|---|
| Fragmented reports, pieced together by hand | → | Automated, central dashboards in their BI tool |
| Metrics defined differently by each team | → | Standard revenue metrics across sales and marketing |
| Imprecise forecasts | → | Historical and cohort trend analysis behind the forecast |
| No way to rank opportunities | → | Segmentation models that pick out high-value accounts |
And now, here is how we got there.
An audit of the reporting
We reviewed the whole analytics setup, its reports and dashboards, and found the inconsistencies, the gaps and the manual processes slowing insight down.
One set of revenue metrics
We defined clear revenue metrics, agreed across sales and marketing, so every team works from the same data.
Dashboards in the BI tool
Automated dashboards in their BI tool bring several data sources together into a single source of truth on pipeline health, conversion rates and revenue trends, in real time.
Trend analysis for the forecast
Historical and cohort-based models track deal progression, sales cycle length and customer retention over time, which makes the forecast more accurate and revenue more predictable.
Segmentation and prioritization
Segmentation models built on past deal patterns and engagement categorize the high-value accounts and show where revenue can expand.
The Results
More accurate forecasts give leadership the confidence to make hiring, investment and go-to-market decisions, and with slow manual reporting gone, they can adjust strategy before problems arrive. They can now pinpoint the causes behind changes in pipeline, conversion rates and retention.
Real-time visibility into sales cycles keeps the teams on the highest-impact opportunities, and standard reporting across sales, marketing and finance has cut redundant data work and improved how they work together.
Request a free consultation to see how we can help you better understand where to spend your marketing budget based on data.