FAQs for deal likelihood scores
Who's this for: Anyone forecasting with Gong
Where: Deals
Plan: Working with Gong Forecast requires a Forecast seat.
To see scores, you must have a Gong Forecast seat.
In addition, to qualify to see scores, your company must have:
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At least 50 deals that were closed-won in the last 2 years, with a minimum lifespan of 3 days
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At least 150 deals that were closed-lost in the last 2 years, with a minimum lifespan of 3 days
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The previous (latest) quarter’s full set of historical data. For example, all deals closed in Q2.
Deal likelihood scores are available for companies holding Gong Forecast seats only.
For companies using Gong Forecast, everyone can enjoy scores in deal boards, regardless of whether or not the individual has a Gong Forecast seat. However, in Deals > Forecast, only people with a Gong Forecast seat can see scores for forecasted deals.
Deal likelihood scores are not available in Gong Pro. Gong Pro license holders do not see likelihood scores.
The score may be less accurate in the following cases:
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You don't have any activity on the deal yet.
If you're at the beginning of the deal cycle and haven't exchanged any emails or had any calls yet, we'll only have CRM data to base the score on.
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You're not connected to one of the data sources.
Whether on a company or individual level, we will have less information if your CRM, email, calendar, web conferencing or telephony provider aren't connected.
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Your deal is managed by a 3rd party vendor.
While we have visibility into your interactions with the 3rd party vendor, we don't see interactions between that 3rd party and your buyer.
Note
Different deal board views or board filters do not affect the score.
For 3rd party deals, our model factors in that a 3rd party manages the deal and gives the deal a score accordingly. Bear in mind, however, that because most 3rd party deals include activity between the vendor and buyer that we don’t have eyes on, the score may be less accurate than for deals you manage.
The score indicator (low, fair, or high) and the score itself are directly related. Scores are grouped by how high they are, and then given the label indicator accordingly. Learn more
No, the model learns independently based on actual data. Our algorithms tune the weighting based on objective deal outcome data to achieve improved accuracy without bias.
Soon, we'll add the capability to segment your deals to refine the model with business context. The additional context provided by this segmentation e.g., deals with different motions such as varying sales cycles, regions, products, etc., will allow for a more nuanced understanding of your deals. This, in turn, will yield more accurate predictive outcomes for each segment.