As marketers, we are bombarded with new concepts, like predictive modeling and predictive data analytics, that we need to quickly understand and integrate into our daily work. The good news: marketing segmentation is not new.

The earliest use of the word “market” refers to a meeting of people at a time and place to exchange goods. So from the beginning, marketing — and market segmentation — has been about groups of people, a time, a place, and offering. With predictive analytics, we’re adding predictive analytics solutions and data to the mix.


Predictive analytics solutions segment people by using automated techniques to do what we do naturally: notice differences and categorize. In both B2C and B2B, predictive analytics techniques discover which characteristics help to combine like people or companies into meaningful groups.

Once these groups are understood by the marketer, she then treats them differently: some people are targeted for certain campaigns based on their segment membership. Data is collected on their responses, which feed the next round of segmentation.


Marketing segmentation is also done based on a time dimension. In B2C, it may be the recency or frequency since the last purchase. In B2B, the time dimension may be based on a longer buyer’s journey: is the person researching a solution or showing signs of nearing a decision?

Again, the marketer will want to use a predictive analytics solution to identify the stage that the buyer is likely in, and treat the buyer differently based on this stage. It would be off-putting to an enterprise buyer to try to close during a research phase. If a shopper is on an e-commerce site, every instant of the buying process is considered, measured, tested, and improved.

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Place may be a channel or it may be considered more broadly as a situation or context. Predictive Sales is a type of predictive analytics that is concerned with identifying not only the timing of accounts noted above—are they ready to buy?—but also in finding the right type of account to consider in the first place. For example, a company that sells CRM software may need to know the accounts that go to market with a direct sales force.


As consumers, we probably see this dimension most often: “people who bought this also bought these items” – we see this language all the time in our digital lives. What we may not realize is that marketers have come a long way with predictive modeling-driven segmentation in tailoring the offer.

Modern predictive analytics solutions have progressed to such a point that there is no separation between grouping and targeting. The automation seems like personalization: each individual person and/or account are treated as if the company is interacting with that person and not a group member. It certainly feels like we’re talking to a company when we talk to a chat bot, shop on Amazon, or review Netflix recommendations.

With Syntelli Solutions’ advanced predictive analytics solutions, you understand what is likely to happen so you can make meaningful decisions to improve sales and marketing effectiveness, reduce risk and fraud, and streamline operations.