orange segments to illustrate data segmentation

How Openprise uses segmentation to find ideal prospects

Who are your ideal prospects? Every company has a rough sketch of the type of buyer most likely to purchase their product. In RevOps, developing an ideal customer profile (ICP) is a data-based process that ensures identifying your ideal customer is as precise as possible. At Openprise, we rely on our RevOps Automation Platform to handle data segmentation, which helps us pinpoint our prospects. In fact, if you’re reading this, the chances are good that our segmentation has done its job.

How exactly does data segmentation software play a role in defining ideal prospects? It all starts with basic organization—breaking down the data you have into consistently named buckets. You must define what each segment means for your company. For example, when we break down leads by company size, we need to know what size we consider small, medium, or large. How do we define that? By annual revenue, or by the number of employees?

The same types of questions arise when we break down leads by geography. How do we determine what makes up the geography segment? If one team divides leads by region, another by state, and yet another by metro area, and each methodology works well, we don’t want to take away their autonomy by forcing them into a single geographic breakdown. It’s vital to empower teams to work in the way that fits them best, and still keep the underlying data intact.

Grading: The ABCs of segmentation

One of the goals of defining target prospects is to understand which attributes you need to focus on, based on which data is most important to the company. For example, at Openprise, we realized that the attribute “number of employees” is strongly correlated to a couple of things we care about—namely, conversion rate and the number of churns. Looking for the most robust correlations, we determined the attributes we wanted to focus on, which helped us reach the segments to apply.

When we build out segmentation, we layer a set of processes onto the data that leads us to any lead or contact truth. Every company’s approach to segmentation is unique, but the processes for great segmentation remain the same:

  • Start with clean data. We can’t say this enough: the quality of a meal depends as much on the ingredients as it does on the chef. In segmentation, that means you’ve ensured that the raw data is cleaned, standardized, and in the correct format.
    • Normalize all your typical values: country, states, provinces, etc., to make segmentation easier.
    • Remove “junk” values
    • Convert your leads to contacts and associate them with the proper accounts.
    • Enrich the data to fill in any missing blanks that will help you choose the segments for each account.
  • Give each account a grade. At Openprise, we don’t use MQLs and SALs. Instead, we give each lead a letter grade—A, B, C, or D. Based on the attributes you’ve defined, which account or contact is worthy of an A grade—someone most likely to convert? Who needs more support, time, or resources before they can buy? Those can be B-grade companies. Which businesses aren’t yet at the maturity level required for your product now, but might be interested in the future? Those are C-grade companies. Once you’ve sorted this out, you’re ready to add segmentation.

Let the segmentation tell a crisp story

Once you’ve done the prep work—choosing the attributes, identifying and applying the correct segmentation—a straightforward, crisp story should start to emerge from otherwise loosely structured data. It’ll be easier to spot the best prospects so the RevOps team can concentrate on the right things, like identifying the proper nurture tracks for each segment.

Segmentation is like a bag of potato chips: once you get started, you can’t stop

Segmentation isn’t a one-time job. It’s an ongoing process that you can iterate on and improve over time. Data comes in every day, and you need to clean and optimize that data so it can be graded effortlessly. When the grading is correct, marketing can work its magic, creating offers and nurture campaigns, and getting them out to the right segments quickly.

But keep in mind that companies’ needs are always in flux. What you assume about leads one day could completely change the next. At Openprise, we meet periodically to re-evaluate our model and review accounts. We look at the correlations to validate our assumptions, and we make adjustments as needed. That way, we can be sure that we continue to grade and segment correctly as if we’re anticipating the prospects’ next thoughts.

Holistic segmentation with Openprise

Openprise automated data segmentation software gives you the ability to reach prospects quickly with an offer or nurturing track that you already know will resonate. But you can’t get to accurate grading and segmentation unless your data is clean and optimized. Your results can only be as good as the data you have. So think about RevOps holistically and remember you can only do proper automated segmentation when the data’s good, and good data is clean and optimized. When you look at it that way, the process is pretty clear.


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