“A little knowledge is a dangerous thing” — Alexander Pope
79% of the companies still miss their forecast by more than 10%, signaling accurate forecasting is hard. Given the shrinking tenure of VP Sales (averaging 18 months), it is a problem that most sales leaders are still challenged with today.
There are many reasons for forecast misses, ranging from rolling hairball deals, overly optimistic reps, aggressive forecasting, and hockey sticks. There are also widely accepted forecasting methods i.e. Historical weighted averages as a good approximation, but what do you do when you have a new sales motion, a new playbook, a new product to sell, new competitors, or new sellers?
Should forecasting then be influenced by sales activity?
Does knowing the activity — the emails, calls, and other communication between sellers and prospects – lead to higher accuracy in forecasts?
The answer is yes — but this applies in extreme cases & only if you have really dodgy sellers. Consider this –
- If there is no or little activity — and the seller is still optimistic about the deal — there is a real problem with the seller, not just your forecast.
- If there is some activity — well the question is – what is the content and quality of that activity? What is actually discussed in those emails?
- If there is a lot of activity — sure that’s a sign of momentum but is it the right kind? Are there buying signals? Are we talking at the right levels? Discussing the right topics and actions?
As Outlook started opening their APIs after 2010, few companies came to the scene to create predictability by mining activity metadata from emails — things like, is the prospect responding over email (a.k.a the deal has momentum) or if the next meeting is even scheduled.
These are useful indicators, but we also know that activity-based prediction is quite easy to dodge and intentionally misrepresent. OOO email from the prospect, or an email that says “I am no longer interested” while actually a negative momentum could be misconstrued as an added activity touchpoint.
Reducing false positives derived from sales activities.
While activity-based prediction is definitely a step forward from relying on unclean CRM data, it still cannot accurately judge the efficacy of most deals as it misses a key component — The deal content — the actual words exchanged verbally and/or in writing with the prospect.
Thus the semantics and not just the volume of the activities become the consideration.
With the ability to now capture predictive red flags that are buried deep— within the seller’s email, calendar, web recordings, and call transcripts — deal derailments can be arrested with actionable insights thus boosting forecast accuracy.
And the way to get an actionable picture of risk in such forecasted deals is to account for —
- Sentiment risk: Objections from key stakeholders in the late stages.
- Relationship risk: Single-threaded, weak relationships, over-reliance on a champion, weak relationship with the current buyer role.
- Disengagement risk: Senior titles or relevant buyer personas not engaging substantively over email and meetings.
- Out of sales process risk: Key topics not discussed, key actions not completed on time.
That is precisely what we do at BoostUp.ai. We help measure the totality of risk from every angle and make it actionable. Get better at not just calling your number, but post bigger & bigger numbers in successive quarters.
Schedule a demo here.