What's your pipeline managing secret?

  • 13 July 2022
  • 5 replies
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What is one thing that you do that no one else does to manage pipeline?

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I don’t have a pipeline managing secret. But I do mid-month check Ins with my reps to make sure we stay on track and asses each deal or opp that needs to be worked on to ensure higher win rates and better the accuracy of our forecast.

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I don’t manage a direct pipeline, but I do train a lot on how to have Forecasting Best Practices. I set parameters for how to forecast “Commit” “Best Guess” “Low.” This is documented in SF and reviewed weekly by the managers. 

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When managing pipeline I love to rely on data and it’s not really a secret but I use Gong dealboards in 1:1s with my team. We look at the open pipe for the quarter, go through deal warnings and the deals with low activity. Then we look at the best case and commit tabs of the board to see if the deals are in the correct stages and where we should focus on this week. So much better than looking at Salesforce! 

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Using warnings to identify opportunities stalled per stage will be a game change. We could use some help with optimizing the right number for “no change for X days or more” in each stage to flash an accurate warning. I also like to use the “next call” data pulled from the calendar to ensure it matches the “next step” pulled from the crm. 

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While admittedly still new to Deal boards, I am starting to do some of the same things as noted above.  Looking at warnings, the visual side of activity etc.   I like to look for commonalities like the number of contacts in each deal and how that impacts close rates.   I am also finding some interesting commonalities in the company account status page.   The ratio of incoming to outgoing emails is interesting but most of all I can now see the top topics discussed in deals that are closing.   For me it’s pretty consistent so this allows me to see deals where some are forecasting to close but when I don’t see the top topics I expect to see I can really dig in and find out why.    It’s another layer or sniff test that goes past the data that I find is working well.

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