4. What Reps care about
• Am I spending my limited focus on the highest-
value opportunities?
• What can I do right now to move my open
opportunities forward?
• Are my leads any good?
• How am I tracking towards quota?
5. What Managers care about
• How are my reps performing?
• How can I help my reps understand the product(s)
and their target market?
• Am I assigning leads in an efficient way?
• Am I spending my limited team resources (sales
engineers, etc.) on the highest-value
opportunities?
6. What Execs care about
• Forecasting
• Am I aggregating the right information from my sales force to
drive:
• VP, Sales: Sales strategy?
• VP, Marketing: Marketing plans?
• VP, Product: Product roadmap?
• What can I do to improve my payback period for investments in
sales?
• Which lead sources should I invest/disinvest in?
• What does my pipeline really look like?
7. 1. Deal insights (Rep)
Problem
If all I know about a particular deal is a numeric deal
score, it’s difficult to use that score to improve my
sales tactics.
Solution
Tell reps about the strongest influences on their
organization’s aggregated deal scores, so they can
change their approach to deals.
8. 1. Deal insights (Rep)
Example
• Your organization's deals are extremely likely to
close if a CSO or VP, Security is the point of
contact
• When selling Product A, the length of time
between demo and follow-up has very little effect
on your deal score
9. 2. Calendar view (Rep)
Problem
Some actions that are necessary to move a deal
forward take more effort and/or lead time than
sending a short email.
Solution
Display a calendar with the deadlines at which, if a
certain action hasn’t happened, the deal score of a
particular open opportunity will start to fall.
10. 3. Expected value --> Financial projections
(Manager/Exec)
Problem
It’s difficult for sales managers to create accurate
financial projections based solely on their reps'
estimates of deal size.
Solution
In addition to the likelihood that a deal will close (deal
score), predict the size of each deal, should it close.
Use this number with deal score to calculate an
expected deal value for each open deal.
11. 3. Expected value --> Financial projections
(Manager/Exec)
Bonus: Customer LTV
With several account cycles' of CRM data, the
expected value of a deal might include the
likelihood of future renewals and upgrades.
12. 4. Deal insights (Exec)
Problem (VP Marketing, VP Sales, VP Product)
We know we have several different customer types/
demand gen strategies/feature clusters we could
pursue. Which one should we target?
Solution
Expose human-readable information about the
influences on an organization’s aggregated deal
scores (weighted by deal value).
13. 4. Deal insights (Exec)
Example: Per-variable
• Your deals are extremely likely to close if a CSO
or VP, Security is the point of contact
• The length of time between demo and follow-up
has very little effect on your deal score
14. 4. “Mainly because…” (Exec)
Example: Clustering
You appear to have 3 kinds of deals:
Deals that close in 5 months with Directors of
Security/CSOs
for Product A
Deals that close in 7 months with Directors of
Security
for Products A and B
Deals that close in 3 months with Data Scientists for Product B
15. 5. Renewal score (Manager)
Problem
Closing the deal for a subscription product is less
than half the battle. Most customer value comes from
maintaining low churn.
Solution
Calculate a "renewal score" for customers with long-
term deals, allowing sales managers and account
reps to farm effectively.
16. 6. Optimized lead allocation (Manager)
Problem
It's difficult to determine which reps on my team will
be best at closing which leads.
Solution
Determine which reps would have the highest deal
scores on each particular lead. Suggest assignments
of leads to reps based on this information.