Historical Data Required for Sales Forecasting

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A few examples of data you'll need to become effective and reliable at sales forecasting. More detail in the accompanying blog post on http://DataDrivenSalesManagement.com

Empresariales Tecnología

DATA REQUIRED FOR
EFFECTIVE SALES
FORECASTING
Swayne Hill
Twitter: @DataDrivenSales
Blog: DataDrivenSalesManagement.com

Copyright Swayne Hill, 2012

Period-to-Date Performance

Copyright Swayne Hill, 2012

Days to Closed/Won from Sales Stage
Averge Days to Closed/Won • Calculated using a 6-
From Stage
month historical view on
Stage 2 90
Closed/Won deals
Stage 3 63 captured from
Stage 4 40
Salesforce.com into our
Cloud9 data warehouse
Stage 5 23
• Average number of days
Stage 6 15
it takes to move from
Stage 7 0 any particular stage in
the sales cycle to
Closed/Won
Days to Closed/Won

Copyright Swayne Hill, 2012

Propensity to Close/Win from Sales Stage
% of Deals That Go To • Calculated using a 6-
Close/Won
month historical view on
Stage 1 35%
Closed/Won deals
Stage 2 42% captured from
Stage 3 50%
Salesforce.com into our
Cloud9 data warehouse
Stage 4 60%
• Percentage of sales
Stage 5 80%
opportunities that
Stage 6 95% ultimately move to
Stage 7 100%
Closed/Won from each
of our sales stages
% To Close/Won

Copyright Swayne Hill, 2012

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Historical Data Required for Sales Forecasting

1. DATA REQUIRED FOR EFFECTIVE SALES FORECASTING Swayne Hill Twitter: @DataDrivenSales Blog: DataDrivenSalesManagement.com Copyright Swayne Hill, 2012

2. Period-to-Date Performance Copyright Swayne Hill, 2012

3. Days to Closed/Won from Sales Stage Averge Days to Closed/Won • Calculated using a 6- From Stage month historical view on Stage 2 90 Closed/Won deals Stage 3 63 captured from Stage 4 40 Salesforce.com into our Cloud9 data warehouse Stage 5 23 • Average number of days Stage 6 15 it takes to move from Stage 7 0 any particular stage in the sales cycle to Closed/Won Days to Closed/Won Copyright Swayne Hill, 2012

4. Propensity to Close/Win from Sales Stage % of Deals That Go To • Calculated using a 6- Close/Won month historical view on Stage 1 35% Closed/Won deals Stage 2 42% captured from Stage 3 50% Salesforce.com into our Cloud9 data warehouse Stage 4 60% • Percentage of sales Stage 5 80% opportunities that Stage 6 95% ultimately move to Stage 7 100% Closed/Won from each of our sales stages % To Close/Won Copyright Swayne Hill, 2012

5. Sales Forecast Risk Profile Stalled Deal Risk filter, driven from Opportunity Scoring benchmark and historical Salesforce.com CRM data Copyright Swayne Hill, 2012

6. Sales Forecast Risk Profile Met with VP Sales Risk filter, driven from Opportunity Scoring System Copyright Swayne Hill, 2012

7. Sales Forecast Risk Profile Pushed Deal Risk filter, driven from historical Salesforece.com CRM data Copyright Swayne Hill, 2012

8. DATA REQUIRED FOR EFFECTIVE SALES FORECASTING Swayne Hill Twitter: @DataDrivenSales Blog: DataDrivenSalesManagement.com Copyright Swayne Hill, 2012

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