Data Analysis Helper Use Case Library

Forecast Projected Sales Based on Past Sales Performance

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Problem: Creating accurate forecasts and tracking actual progress

For Sales Leaders, creating annual forecasts is part art and part science. New products, strategies, investments, tools, and staff--these unknowns and variables are the “art” part. Historical sales data and metrics are the science. There’s a track record at work here. Existing customers, retention, and traditional growth rates—across certain reps, accounts and territories/segments—provide a glimpse of the future.

Gathering and analyzing this data from Salesforce, and then trending it into projections, can be challenging. Then Sales Leaders have the separate challenge of monitoring progress toward those projections as well as gathering insights in time to make any needed adjustments. That's why we built Sales Performance Intelligence, Account Performance Intelligence, and Territory & Segmentation Intelligence analytic packs for the Data Analysis Helper app.

Solution: Leveraging historical and real-time projecting tools

Data Analysis Helper’s premium add-on packs deliver insights and performance suggestions directly to Sales Leaders. No need to spend time figuring it out; you can go straight to acting on this actionable information--whether you are creating forecasts or working toward quota achievement.

See projected sales amounts for a rep not meeting (or overachieving) established goals? Check out which key metrics are lagging (or exceeding) benchmarks, and then act accordingly to get back on track (or recognize success and share the methods with others). 

Projected Sales Dashboard by Rep

This same methodology can be used on accounts, territories and business segments as well.

Projected Sales Dashboard by Account

Sales projections are the first indicator of an emerging problem or opportunity. Then, using Data Analysis Helper’s analytical packs, you can diagnose the root cause and address the issues.

As sales activities are optimized through data analysis, there are fewer chances for surprises—both for the current sales cycle and when predicting the next one. This leads to better forecasts and quota achievement, at least for the science part of sales management.


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