B2B Customer Segmentation Approaches: Census Composition Analysis
Last week, I shared 6 one-off B2B customer segmentation exercises that early development stage B2B companies can use to quickly identify potential segmentation characteristics and use as a tool to inform target segment decisions:
- Compare the composition of your customers industry or size against the US census composition statistics for your selected target geography.
- Compare the composition of your lost customers by employment size against the US census composition statistics for your selected target geography.
- Monthly Recurring Revenue (MRR) / Customer or Annual Revenue Per Deal by Selected Firmographic Characteristic
- Monthly Recurring Costs (MRC) / Customer or Cost of Service Per Month by Firmographic Characteristic
- A Closed Opportunity Win-Loss Analysis by Target Firmographic Characteristic(s)
- Tenure of Customer by Firmographic Characteristic
This week, I will explain how to use census data to set up and execute the two census composition comparison exercises.
Census Composition Analysis: Overview
The purpose of a census composition analysis is to identify positive and negative trends in the composition of customer, opportunity, lost deal, or lost customer groups relative to the census in a given geography. Most of the time a census composition analysis is used to identify firmographic (industry, industry groups, size, etc.) trends, but often seeing these trends will help highlight other potential segmentation characteristics.
You can run a census comparison analysis really quickly. The only time-intensive aspect of this analysis is categorizing a sample of your customers, opportunities, lost deals or lost customers by size, NAICS-industry, and geography. This only takes a minute or so per company and will often be the input to several other analyses that you will be doing, so it is a limited time investment.
However, you will first want to evaluate whether or not one of these one-off B2B customer segmentation analysis approaches make sense for you and your company. Below are a couple of factors to consider:
- The analysis will be most informative for companies who have used an industry agnostic go-to-market strategy or limited targeting.
- This approach will yield the most value to companies who sell products or provide services to a wide-range of customer types.
A Step-by-Step Guide to Set Up and Execute a Census Composition Analysis
- Identify the relevant geography. This is where your company has predominantly focused its sales and/or marketing efforts.
- Download the census data for the target geography (City, County, MSA, Group of MSAs, State, Region or US) and relevant NAICS industry groupings and/or size groupings. This data can be pulled from the following locations:
- 2010 Census U.S. Business Statistics by NAICS Industries, Size Ranges, and States
- 2009 Census U.S. Business Statistics by MSA, NAICS Industries and Size Ranges
- The key here is to identify the appropriate level of NAICS industry detail. The NAICS major industry groups (2-digit codes) are very broad and quick to identify. Each additional digit you add to the NACIS codes increases the level of specificity of the industry or sub-industry being tracked. The most specific NAICS codes have 6-digits and are almost always too detailed for this one-off type of analysis. I recommend using 3-digit codes as a starter as they are easy to identify and still offer a lot of information. Keep in mind that each additional layer of the NAICS code detail that you include will increase the time commitment to identify NAICS industries within your sample of data.
- Calculate the census industry and/or size composition statistics to make sure the subset you pulled is detailed enough for your needs. To do this, you will need to subset the census data to the relevant NAICS industry level (i.e. 2-digit, 3-digit, etc.) and/or company size range. Next, you will want to calculate the relevant proportion of US establishments that are made up by each industry and/or size range.
- Identify the relevant subset of customers, opportunities, lost deals, or lost customers that you will analyze in this analysis. This will be dependent upon your company’s previous go-to-market strategies. If your company has already led a targeted effort into selected segments that are correlated with size and/or industry, then you will want to look at a subset that was not part of a targeted campaign like inbound lead opportunities or inbound lead generated deals.
- Categorize the sample of customers, opportunities, lost deals, or lost customers by size, NAICS-industry, and/or geography. To categorize by NAICS industry codes, you can read the LinkedIn profile for each company and then search for the keywords in the NAICS industry identifier tool. Choose the selected code level that best fits. This will be more time consuming for more detailed NAICS industry code searches.
- Calculate your subset of customer, opportunity, lost deal, or lost customer industry and/or size composition statistics.
- Calculate the percentage differences in actual versus expected sector or company size compositions for your subset of customers, opportunities, lost deals, or lost customers. Percentage difference is calculated as actual sector composition percentage divided by census sector composition percentage.
- Now you will want to chart the composition statistics side by side and overlay a line chart of the percentage difference. You will want to bucket the irrelevant NAICS industries into an “Other” bucket so you can focus the chart on the most relevant NAICS industries.
- Look over the chart and try to identify patterns of industries and/or company size ranges where the subset of customers, opportunities, lost deals, or lost customers are different from the census composition statistics. These patterns will often tell a story about the types of prospects your company does well with and those that it does not. They can also help you identify common no-industry or size factors that link each of these groups.
- Further analyze the subsets of NAICS industries or company size ranges of interest.
Below is an example of what the output should look like using 2-digit NAICS major industry codes.
Prior to kicking-off a census composition analysis, I recommend thinking about the potential benefits of this analysis relative to the time commitment and evaluating alternative analysis approaches. Younger companies are always resource constrained, so it is important to wisely invest your time.
Next week, I will explain why and how to set-up and execute customer revenue and cost analyses for the purpose of B2B customer segmentation.
B2B brand and product positioning will only continue to become more important with the rise of the End User Era.