Enterprise Customer Market Segmentation: A Guide for Limited Customer Data

June 7, 2012 by

Enterprise Customer Market Segmentation

Image provided by: www.mindofmarketing.net

Going after enterprise customers is often a tempting strategy for startup and expansion stage companies because the contract sizes offer huge returns to efforts and enable companies to generate high revenue levels with only a limited number of customers. However, these customers also tend to be some of the most competitive and expensive deals to compete for, so they also carry considerable risk.

Often when startup and expansion stage companies first decide to shift part or all of their focus towards the enterprise segments, they only have a handful of enterprise customers who are not well distributed across the industries of interest, and lack the data to conduct a customer segmentation analysis to identify the best enterprise customer segment for them to target. This often leads to companies taking a carpet bombing approach to enterprise sales, resulting in a very low likelihood of success.

By refining its focus to a specific set of target segments, a startup or expansion stage company can improve its return on its sales efforts. Providing a focus to build a meaningful marketing and product strategy around should increase sales conversion rates and drive up their revenue derived from enterprise sales. One inexpensive, quick, and non-resource intensive way to identify a specific set of target segments when there is limited customer data to work with is by doing an enterprise customer market segmentation analysis with the Fortune 500 companies.

Step-by-Step Enterprise Customer Market Segmentation Approach

In the next section of this blog, I will walk you through a step-by-step process for conducting an enterprise customer market segmentation analysis when limited customer data is available.

  • To start, you will first want to get agreement from all stakeholders in the project as to what the definition of “best customer” is.  In most instances, this will be a function of the following factors:
    • Economic value: measured by potential deal volume or other quantified economic benefits derived from the customer
    • Reasonable time horizon for an actual purchase
    • Whether or not there is a business case for product/service
  • Next, you will want to gather these same stakeholders to identify the most important characteristics that determine whether or not a customer fits the best customer definition. It can also be worthwhile to do a quick customer segmentation of the current customers to identify trends in current customers that could help the team identify a better list of “best customer characteristics”. These factors will need to be identifiable through secondary research or proxied via other information. You will want to limit this to no more than 4 or 5 factors.

   Some examples of these factors would be:

    • Minimum Customer Size (i.e. 1,000 customers or more)
    • Whether or not a company’s end customers are primarily B2B or B2C companies
    • Whether or not a company is public
    • Economic Model (i.e. SaaS, Perpetual License, Hybrid)
    • Considered Purchase (i.e. insurance) vs Impulse purchase (i.e. can of CocaCola)
    • Geography
    • Nature or Focal Point of Products or Services
    • Level of Outbound Marketing
  • At this same time, you will want to have the stakeholders rank these factors relative to one another and use this information to assign weights to each of these “best customer characteristics”.  For example, if all things were equal and there were 4 characteristics, you would assign each a 25% weight.  However, if one factor was twice as important as the others and the rest were equal amongst the 4 characteristics then you would assign the more important value a 40% weight and the other 3 criteria 20% weights.  This information will factor into the analysis later.
  • Next, you will want to download the Fortune 500 company list and confirm that the Fortune 500 provides a representative list of the industries and types of companies that your company is interested in considering.  If not, you may want to consider using an alternative list like the Forbes Global 2000.  This list will define the universe of potential enterprise customers that you will be considering in this analysis.
  • You may want to sub-set this list of potential enterprise customers to just the industries/types of companies that your company has previously had experience with or remove those groups of companies that logically would have no need for your company’s products or services.  This will help limit the resource commitment and time to complete this analysis.  Similarly, you can also limit the analysis to only the top 250 customers or a stratified sample of the customers that accounts for all of the relevant customer types/industries.  Doing so, will slightly decrease the accuracy of the results, but also speeds up the analysis.  So you need to decide what is more important for your company.
  • Now you will want to identify how you can measure each of the “best customer characteristics” and identify the best proxy measurement for this factor if it is not observable via secondary research.
  • Next, you will want to collect this information on each one of the companies in the universe of potential enterprise customers.  You will also want to collect some additional demographic information (size, geography, industry, etc.) on the companies if you are not already collecting that information as part of your “best customer characteristics”, as this will provide you with a couple very easily accessible factors to look at in your market segmentation analysis.
  • Now you will want to develop your potential customer score formula using the “best customer characteristic” weights and apply it to each of the potential customers to calculate a potential customer score.
  • Now you have an idea of which customers are the most attractive based on the potential customer score.  You will now want to try and identify patterns in these potential customers and see if you can start grouping them together.  These groupings should also relate to a company’s product/service use case and value propositions, so that the segments will be useful for developing your go-to-market and product strategy.  You can use a decision tree with potential customer score as the dependent variable to help identify the most effective segmentation scheme.
  • Next you will want to make sure that the top segments are large enough to build your company’s go-to-market and product strategies around.  To do so, you will want to estimate the ASP for each segment and estimate the maximum percentage of the budget that an enterprise would allocate towards that product or service.  Then, you need to find an estimate of the average percentage of revenue that companies in each segment will spend on a given category of spending.  Usually these types of statistics can be found in industry publications. For example, Adage provides these types of statistics for marketing.
  • Minimum  Revenue Size = ASP/ (Average Ad Expenditure as Percentage of Revenue * Max Percentage of Budget to Spend on Your Company’s Products)
  • This will provide you a minimum revenue amount for a company to be a relevant target customer.  Since revenue data is not always publicly availble, you will want to use a revenue to employee multiplier to translate this figure into employees. The US Census and CNN Money both maintain online resources that list this information.    This will give you a minimum company size in each segment that you can use to calculate the number of relevant companies that belong to each customer segment.  Depending on what the segment criteria are generally you can use LinkedIn to get a guestimate of the segment size.
  • The last step is ranking the segments based on expected ASP, number of potential opportunities and average lead score in each segment.
  • Once you have identified a segmentation scheme you will want to test its effectiveness at identifying your top customers.  To do so, you will want to estimate the likelihood that the segmentation scheme accurately predicts the potential customer score quintile that the customer belongs to.

Now you have a quick and non-resource intensive methodology for identifying the top enterprise customer segments to target and build a meaningful marketing and product strategy around.

If you are interested in reading more about market segmentation, I highly recommend reading my colleague Tien Anh’s blog post on how to incorporate market segmentation into your company’s go-to-market and product strategies.

 

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