The document outlines a method for scoring sales opportunities based on a model sales cycle to enhance CRM efficiency, triangulate forecasts, and provide targeted coaching. Key attributes for scoring include business size, industry, business goals, maturity, and decision-maker profiles, among others. Implementing this scoring system has led to improved win rates, reduced administrative burdens, and increased responsiveness within sales teams.

1. SALES OPPORTUNITY
SCORING
DataDrivenSalesManagement.com
Swayne Hill, 2012
Copyright Swayne Hill, 2012

2. Sales Opportunity Scoring
Marketing scores Leads, why doesn’t
Sales score Opportunities?
Copyright Swayne Hill, 2012

3. Sales Opportunity Scoring
By Scoring Sales Opportunities against
a Model Sales Cycle we…
1. Streamline CRM Systems
2. Triangulate Sales Forecasts
3. Provide Deal-Level Coaching
4. Monitor Risk/Exceptions
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4. How to Create a Scoring System
Consider This: Do This:
• What are your ideal 1. List the most impactful
sales circumstances? sales-cycle attributes
• Is this ‘Ideal’ different 2. Profile attributes
for each line of according to impact on
business? winning to create a
• Has this ‘Ideal’ Model?
changed over time? 3. Press this new Scoring
System into action
4. Plan to revisit
assumptions regularly
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5. MOST IMPACTFUL
ATTRIBUTES
Top 10 Most Impactful Sales-Cycle Attributes
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6. 1. Size
By knowing the size/scale of the business we’re
selling into, we anticipate the complexity and
potential deal value
• Size might be defined by Annual Revenue,
Employee Count, etc.
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7. 2. Industry
In our case, success probability is more tied to
Business Model but Industry is a good proxy and
more readily available
Examples
• Financial Services
• Tech
• Media
• Manufacturing
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8. 3. Business Goals
By understanding the
top-level business
goals, we can infer the
investment climate
Examples:
• Growth
• Profitability
• Market Share
• Acquisition Roll-Up
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9. 4. Maturity/Readiness
How clear is the prospect on the ‘problem’ and
its impact on the business?
Example:
• Is the pain intolerable to
the right people?
• How long have they
had systems in place?
• How’s the relationship
between IT & the
Business?
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10. 5. Compelling Event
Is there a forcing-function, some event or deadline
imposed on the buyer (not you) that drives
urgency?
If it’s well-corroborated
and the prospect is close
to the ‘sweet spot’, this is
often the most important
attribute
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11. 6. Primary Buying Agenda
We encounter three different buying agendas,
some turn out to be more likely to succeed than
others due to…
• Perceived competition
• Scope of buying group
• Strategic v. tactical
problems
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12. 7. Pro-Services Attached
In our business, actively managing a transformation
project is critical to success
• Is the value of professional services understood
and embraced?
• Do they have people who WANT control and have
the skills to TAKE control over the project?
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13. 8. Decision-Maker Profile
By understanding the profile of
our decision-maker, we know
how to position the value of
solutions
• Are we actively engaged with
the real decision-maker?
• Is the decision-maker a
‘cowboy’, ‘student of the
game’ or a ‘data jockey’?
Copyright Swayne Hill, 2012

14. 9. Buying Experience
If our decision-maker is new or has little
experience running a buying process, they often
underestimate the effort to get a deal over the line
On the other hand, if
they have too many
battle-scars, they may
be ultra-conservative
and not push their own
organization hard
enough
Copyright Swayne Hill, 2012

15. 10. Corroboration
By double-checking the facts, we gain confidence
in our view of the buying process
It does matter at what
level of the org, we do
the fact-checking…
• Higher up
• Same level
• Lower down
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16. ATTRIBUTE VALUE/SCORE
PROFILE
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17. Ideal Sales Circumstance
Decision-maker is engaged,
a ‘student of the game’ and
a practiced buyer High state of readiness
with solution deadlines
driven from above
Blended App/Tools buying
agenda with 30% services
attach
Medium-large sized high-
technology company
Key situational details focused on growth
corroborated from above
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18. Assign Scores to Attribute Values
Attribute Attribute Value : Score
1. Size S:2, M:10, L:7, XL:2
2. Industry FS:4, Tech:10, Media:8, Other:2
3. Business Goals Growth:10, Margin:2, Blend:7
4. Readiness Low:1, High:10
5. Compelling Event Y:10, N:0
6. Primary Buying Agenda App:8, Tool:4, Service:6, Blend:10
7. Pro-Services Attach 0%:0, 20%:8, 30%:10, >30%:4
8. Decision-Maker Profile SOTG:10, Cowboy:5, Other:2
9. Decision-Maker Buying Experience None:0, Practiced:10, Expert:5
10. Corroboration Higher:10, Lower:3, Same:8, None:0
Copyright Swayne Hill, 2012

19. Weight the Attributes
Weight sales-cycle
attributes according
to relative impact
on the probability of
winning – don’t
worry about getting
it perfect, adjust
later
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20. Weight the Attributes
Attribute Weight Attribute Value : Score
1. Size .05 S:2, M:10, L:7, XL:2
2. Industry .05 FS:4, Tech:10, Media:8, Other:2
3. Business Goals .10 Growth:10, Margin:2, Blend:7
4. Readiness .10 Low:1, High:10
5. Compelling Event .20 Y:10, N:0
6. Primary Buying Agenda .10 App:8, Tool:4, Service:6, Blend:10
7. Pro-Services Attach .05 0%:0, 20%:8, 30%:10, >30%:4
8. Decision-Maker Profile .10 SOTG:10, Cowboy:5, Other:2
9. Decision-Maker Buying
.15 None:0, Practiced:10, Expert:5
Experience
10. Corroboration .10 Higher:10, Lower:3, Same:8, None:0
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21. PRESS SCORING SYSTEM
INTO ACTION
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22. Example
Possible Values Sample Weighted
Attribute Score
(Benchmark) Prospect Score
1. Size S:2, M:10, L:7, XL:2 XL 2 1.0
2. Vertical FS:4, Tech:10, Media:8, Other:2 Media 8 4.0
3. Business Conditions Growth:10, Margin:2, Blend:7 Blend 7 7.0
4. Maturity/Readiness Low:1, High:10 High 10 10.0
5. Compelling Event Y:10, N:0 None 0 0.0
App:8, Tool:4, Service:6, Blend:
6. Primary Buying Agenda App 8 8.0
10
7. Pro Services Attach 0:0, 20%:8, 30%:10, >30%:4 30% 10 5.0
8. Decision-Maker Profile SOTG:10, Cowboy:5, Other:2 Other 2 2.0
9. Decision-Maker Buying
None:0, Some:10, Expert:5 Some 5 7.5
Experience
Higher:10, Lower:3, Same:8,
10. Corroboration Same 8 8.0
None:0
60 52.5
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23. Streamline CRM System
• Recording deal details in the CRM system is a
pain in the ass for sales reps. By focusing on the
data that really matters, we minimized the admin
overhead for reps AND we got richer, more useful
data at the same time.
Copyright Swayne Hill, 2012

24. Triangulate Sales Forecast
• We always consider three data sources before forecasting
next period sales – what the Sales Reps say, what the
over-rides look like and what the data says.
• Creating a scoring system based on the sales cycle model
gives us that third leg of the stool – what the data says.
Copyright Swayne Hill, 2012

25. Provide Deal-Level Coaching
By exploring the gaps between
Win Probability on a particular
deal – the ‘Weighted Score’
and Forecast Probability, the
subjective probability
associated to the stage we’re
in, we focus a Sales Rep’s
attention on the high-impact
activities that would bring a
deal closer to the model
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26. Create Risk/Exception Reports
Not all of the information
we need is available at
the beginning of the
cycle. If the information
does not unfold as it
should OR we are not
converging on the Model
Sales Cycle, the system
triggers risk-alerts so
we’re not blind-sided at
quarter-end.
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27. REVISITING
ASSUMPTIONS
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28. Watch For New Patterns
Every quarter, we re-evaluate the assumptions in the Model
– top attributes and weightings and adjust accordingly.
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29. Sales Opportunity Scoring
By setting up a Sales Opportunity Scoring System
we’ve increased our win rate, reduced admin time
and given our team more reaction time
Copyright Swayne Hill, 2012

30. SALES OPPORTUNITY
SCORING
Swayne Hill, 2012
DataDrivenSalesManagement.com
Copyright Swayne Hill, 2012