Personalization Glossary

Micro Segmentation


Oct 30, 2017

Micro-segmentation refers to the practice of dividing online traffic into numerous small groups of visitors who share common interests and online browsing patterns. While traditional data-points allow for high-level technical, demographic, or geographic segmentation, micro-segmentation incorporates a vastly wider range of data-points, made available due to recent technological breakthroughs.

A Quick History on Segmentation

No business ever just targets one type of customer. Therefore, traffic segmentation is the foundation for marketers seeking to understand who their customers are, how they engage, why they engage as they do, and what triggers might drive them to take further action.

All of the above can be gleaned from an analytics platform, tracking and recording paths and actions each user takes. Once all users are analyzed and bucketed by common attributes, an experience targeting platform can be used to target these users, serving them messages and content tailored to them.

Traditionally, marketers have been able to leverage a limited selection of user and data-attributes to slice and segment their traffic. Such data includes the user’s geography, available demographics, marketing channel, online behavior, lifetime-value, and more. However, these traditional attributes lead to relatively high-level and fragmented segments.

For example, two users who live in the same geography may, in fact, have a few preferences in common, such as weather or local brand-based considerations, but they most likely do not have much else in common. On the other hand, one user could show identical preferences across two devices, a desktop, and mobile device, but end up segmented in two different buckets, due to unsophisticated, siloed technology.

Free Guide: Mastering Micro-Segmentation for Personalization
How Personalization Still Falls Short of Consumer Expectations.

With the advent of big data integrations, omni and cross-channel capabilities, and advanced machine-learning engines, segmentation has endowed much more refined and granular capabilities, introducing marketers to the concept of micro-segmentation and micro-targeting. In fact, with every additional data-point accessed, the number of segments can grow exponentially (read further about predictive segmentation). Platforms that enable micro-segmentation capabilities are required to ingest data from multiple sources (3rd party user data, offline data, CRM, etc.), as well as identify the users across the channels through which they are active (web, apps, email, brick and mortar stores, direct mail, and more).

As a result, micro-segments can consist of small groups of users who share interests in the same brands, product categories, age, extracurricular activities, income level, pets, hobbies, spending patterns, preferred devices, and much more.

Considering that serving the right message to the right visitor at the right time is the best way to boost performance, micro-segmentation has the potential to improve business’ performance multifold. Since figuring out the best experience for each micro-segment requires a lot of time, effort, and resources, marketers are required to restrict the number of micro-segments or use a platform like Dynamic Yield to automate the process.

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