How to Create a Sales Opportunity Scoring System

SALES OPPORTUNITY SCORING DataDrivenSalesManagement.com Swayne Hill, 2012

Copyright Swayne Hill, 2012

Sales Opportunity Scoring Marketing scores Leads, why doesn’t Sales score Opportunities?


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


How to Create a Scoring System

Do This: 1.  List the most impactful

sales-cycle attributes 2.  Profile attributes

according to impact on winning to create a Model?

3.  Press this new Scoring System into action

4.  Plan to revisit assumptions regularly

Consider This: •  What are your ideal

sales circumstances? •  Is this ‘Ideal’ different

for each line of business?

•  Has this ‘Ideal’ changed over time?


MOST IMPACTFUL ATTRIBUTES Top 10 Most Impactful Sales-Cycle Attributes


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.


2. Industry

Examples • Financial Services • Tech • Media • Manufacturing

In our case, success probability is more tied to Business Model but Industry is a good proxy and more readily available


3. Business Goals By understanding the top-level business goals, we can infer the investment climate Examples: • Growth • Profitability • Market Share • Acquisition Roll-Up


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?


5. Compelling Event

If it’s well-corroborated and the prospect is close to the ‘sweet spot’, this is often the most important attribute

Is there a forcing-function, some event or deadline imposed on the buyer (not you) that drives urgency?


6. Primary Buying Agenda

• Perceived competition • Scope of buying group • Strategic v. tactical problems

We encounter three different buying agendas, some turn out to be more likely to succeed than others due to…


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?


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’?


9. Buying Experience

On the other hand, if they have too many battle-scars, they may be ultra-conservative and not push their own organization hard enough

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


10. Corroboration

It does matter at what level of the org, we do the fact-checking… • Higher up • Same level • Lower down

By double-checking the facts, we gain confidence in our view of the buying process


ATTRIBUTE VALUE/SCORE PROFILE


Ideal Sales Circumstance

Medium-large sized high-technology company focused on growth

High state of readiness with solution deadlines driven from above

Blended App/Tools buying agenda with 30% services attach

Decision-maker is engaged, a ‘student of the game’ and a practiced buyer

Key situational details corroborated from above


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


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


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 Experience .15 None:0, Practiced:10, Expert:5

10. Corroboration .10 Higher:10, Lower:3, Same:8, None:0


PRESS SCORING SYSTEM INTO ACTION


Example


Attribute Possible Values (Benchmark)

Sample Prospect Score Weighted

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

6. Primary Buying Agenda App:8, Tool:4, Service:6, Blend:10 App 8 8.0

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 Experience None:0, Some:10, Expert:5 Some 5 7.5

10. Corroboration Higher:10, Lower:3, Same:8, None:0 Same 8 8.0

60 52.5

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.


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.


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


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.

REVISITING ASSUMPTIONS


Watch For New Patterns Every quarter, we re-evaluate the assumptions in the Model – top attributes and weightings and adjust accordingly.


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


SALES OPPORTUNITY SCORING Swayne Hill, 2012 DataDrivenSalesManagement.com
