Create a Bucket List

Many B-to-B marketers, on the other hand, may prefer to use a segmentation model based on Firmographic variables, such as industry, number of locations, annual sales, job function and so on. Many software companies, not surprisingly, trend toward usage-based profiling, which includes variables, such as type of device used (desktop, tablet, mobile device), Operating System and so on.

One important fact that's routinely overlooked is that successful customer segmentation requires taking a holistic approach. This includes aligning a firm's segmentation goals to its marketing objectives and data acquisition investments. In other words, the data you have will determine not only which model you use, but also what marketing campaigns you're able to run.

Now of course both data inputs and needs are in flux throughout the firm's lifecycle. As Banasiewicz points out, for a firm in high-growth customer acquisition mode an Attitudinal model might work effectively for demand generation initiatives among qualified and segmented pools of prospects. Marketing campaigns in this scenario, we can assume, would speak to customer desires and affinities, with purpose of lead generation/nurture.

On the other hand, once the firm has acquired a large pool of customers, it's not unrealistic to think that transitioning to a Behavioral model using inputs from past purchases will be more effective for running what are now CRM campaigns, focusing on driving lifetime value and repeat purchases.

Different groups not only have different attributes and attitudes, but consume different types of media. As such, they will respond to different types of offers, communicated in different ways and in different places. Where should a firm spend its marketing budget? Online display, email, direct mail, social media, print? … The choices are dizzying in today's multichannel environment. Having a robust customer segmentation model can definitely help in the decision-making process.