This step is grounded in the belief that past behavior is the best predictor of future actions. Therefore, existing customer spend is analyzed to look for predictors of future spend potential. Before getting deep into the analysis, it is necessary to brainstorm a list of firmographic attributes that could drive spend levels within your customers. A partial list of characteristics World Class companies contemplate using include:
- Market Cap
- # Employees
- # Locations/Facilities/Stores
- # Customers
- Size of Fleet
- SG&A Spend
- R&D Spend
- Operating Income
- Net Income / Earnings
- Revenue Growth
- Earnings Growth
- Debt/Equity Ratio
- Offering – Product/Service
- Decision Making – Central/Decentral
- Ownership – Public/Private/Non-Profit/Government
- Market Share
- Credit Score
- Willingness to Outsource
- Industry/Government Regulations
With the list of characteristics identified, it is now time to enrich the existing customer database to add the attributes you want to analyze. Often this requires additional data buys and the concatenation of lists. Once the full customer database is populated, correlation analyses are run looking for the attributes with the greatest determination on past spend levels (including associated confidence levels). An example of the analysis is displayed in the figure below which maps customer revenue to customer spend:
If the correlation proves strong, then a spend frontier is applied. It is not advised to use average or median spend for the frontier as that often understates the opportunity within accounts. It’s also not advised to use the maxim spend as this often overstates the opportunity within accounts. World Class companies typically use the 80th percentile spend for their frontier assignment – if you have 10 customers, sorted highest to lowest you would roughly take the spend level of the 3rd highest customer.
With the attributes and the frontier determined, customers can now be clustered in “segments”. Within each segment a spend potential is assigned. The example below shows how assigning accounts to industry and revenue “segments” then applying an 80th percentile spend frontier to project expected revenue from each account within each segment.
In this case a “small” Consumer Products company should spend $132K while a “medium” Professional & Business Services company should spend $918K while a “large” Technology & Software company should spend $1.98M.
These are a couple examples of the rich information that can be mined from existing customers. This step forms the baseline that will allow us to determine market potential and complete our territory design.