The Revenue Blog /
How Activity Data Can Transform Forecasting in a Downturn?
Sharad Verma
July 29, 2022
5 min read
Activity data exhaust from our sales tech investments is the new oil of revenue operations in the 2020s. Most sales organizations use between 10 to 30 sales and marketing tools but poorly analyze the usage & activity data from those tools to make business decisions.
Examples of primary activity data include:
- Buyer emails and content of those emails
- Seller emails and content of those emails
- Gong call recordings - sentiment, topics, talk time
- Buyer activity on your digital content, such as website data
- Intent data from Zoominfo, Demandbase, 6sense
- Slack interactions
- Meetings
- Number of Digital deal reviews in tools like BoostUp
- Who is using insights in revenue intelligence
- Deal updates by Reps
Two-way activity and its inverse Lack-of-activity are the best predictors of deal velocity and pipeline quality. Lack of activity from the buyer is the same as buyer disengagement and is the best predictor of deal stalling.
This activity data, when captured completely and matched accurately at the opportunity level, helps you de-risk your forecast in the following areas:
When combined with a great forecasting process, activity data can result in the goldilocks zone of forecasting, which is 98-99% accurate.
That’s when you are within 1-2% of your forecast. This allows you to make:
Goldilock's zone of forecasting doesn’t happen on its own. It takes rigor, process, tools, and data to get it right. You need:
Read our advanced forecasting guide and list to our recent "Art and Science of Sales Forecasting" masterclass to learn more about getting to the Goldilocks zone of forecasting.
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