Influencer Map - How does it work?
In the example below, Eric Stark has been identified as a key influencer for our target contact Paula.

To calculate the influencer score, we look at all opportunity and activities that Eric has been involved in with Paula, and calculated a weighted
score.

In this case, we see that Eric has been involved with 3 deals where we won, 2 deals where we lost, and 1 deal which is still in process and 10
activities that they have been together in (Activities are emails, phone calls, appointments, visits).
We then calculate the weighted score which is 29. This score is higher than all the other potential influencers of Paula, so we will ask Eric for help with this particular opportunity.
We also take end user feedback, so if Erick is moved from first position to last position then we store the user preference which will bring down the score as well.
Weighted score
Influencer Score = Σi=1..n (Si x Wi)
- No. of transactions
| Score (S) |
0 to 2 | 1 |
3 to 5 | 3 |
6 to 8 | 5 |
Transaction | Weight (W) (Example) |
User Preference | 5 |
Won Opportunity | 4 |
In Process Opportunity | 3 |
Lost Opportunity | 2 |
Activities (Email, Phone, Appointment, Visit) | 1 |
Thanks for this detailed explanation. This is perfect.
Have you got a similar description for the Deal finder by any chance?
This document was generated from the following discussion: How does the Influencer Map in SAP Cloud for Customer work?