Leverage data to invest in the right customers

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Time, people and materials are all important resources for the sustained growth of a company.

This encompasses who sales representatives or account managers spend their time with and how they’re spending that time as well as where they’re spending it. It also includes who, how, and how often marketing targets prospects and customers.

However, which customers or prospects get special attention (demonstrations or samples for example) is often left to the discretion of the individual sales representatives, but is this the best way to allocate resources for growth?

Data-driven decisions

With the maturity of using big data and the associated analytic tools, more and more companies are using segmentation as a way to answer this question. Why should a customer who is price-sensitive, orders infrequently and is not aligned to the company’s strategic product direction get the same treatment, care and support as a customer who is consistently choosing the company’s products over a competitor, is giving the company “first and last look” and is less price-sensitive? So how do you adequately define the segments so that they are accurate and actionable?

Four levels of segmentation

There are four levels of segmentation that should be considered as you think about a model that will help you successfully allocate resources to the best market opportunities.

Demographic data

Most organizations have some level of demographic segmentation. However, you must move beyond demographic segmentation. Demographic segmentation has minimal effectiveness, as at best it can only align resources to healthy industries and territories. That is too much of a macro allocation of resources and most likely will not result in growth. There are other segmentation attributes that must be considered beyond typical demographics.

Transactional behavior data

It can also be helpful to look at a customer’s transactional behavior or how he or she purchases your products or services. You need to include at least three to five years of transactional behavior. Transactional behavior includes:

Frequency of purchases
Discounting of the purchases
Total volume
Average purchase size
Returns
Gross margin
Any other associated transaction data that is available

This data is useful in helping to predict the future behavior of the segments as well as begin to paint a picture of an ideal customer. However, this data remains rear-view facing, and doesn’t include any growth potential or share of wallet or other indicators of future opportunity.

Behavioral data

More subjective in nature than other data we’ve discussed, it requires the input from those closest to the customer. Historically, the behavioral data is comprised of a handful of attributes that have strict “scoring” guidelines that sales reps or sales managers can use to append the demographic and transactional data.

Data attributes can include price sensitivity, “first look/last look” and supplier preference. This provides an offset to the backward looking transactional data and the static demographic data in the first two levels.

Psychographic data

Psychographic data is the highest level of understanding and looks at the motivations, culture and goals of the customer. This data is the most difficult to capture but also the most useful in directing offers and other experiences to win, sustain and grow an account.

Creating a useful segmentation model

Combining these four levels of maturity helps create a model that can be extremely useful for defining actionable segments. The usefulness of a segment should be scrutinized by these questions:

Is it practical? Can the model be sustained and replicated year over year? Is the data being used easily captured year over year to replicate the model?
Is it understandable? Do the descriptions of the segments make sense to the organization and do the descriptions convey the value of the segments?
Is it actionable? Are the segments relevant enough so that specific actions and strategies can be defined and executed against the segment? Are the segments delineated enough where the allocation of resources can be made to optimize the growth potential (or lack thereof) of each segment?
Is it measurable? Once the actions and strategies are executed against the segment, can the results be measured and reported on?

If an organization adopts these four criteria in defining their market segments, the allocation of resources to areas with the most growth potential is easily achieved. Organizations should refrain from allocating the same resources and treatment strategy across all customers. Focus resources to the customers that are going to provide the most value to the organization. Growth can be more easily forecasted and achieved through meaningful segmentation.