Perhaps the most well-understood of the marketing tactics that make up an identity-driven marketing strategy, segmentation is an alternative to the spray and pray method of marketing that relies entirely on sheer number of impressions and top-of-mind awareness to convert customers. Put simply, it's a way to get a better, more compelling message in front of a smaller, or more targeted group of customers who share similar characteristics, Russell Loarridge at Janrain.
While basic segmentation is relatively easy to do based on broad and even anonymous demographic data such as age and gender, the most effective segmentation results in small clusters of individuals who have similar interests, values, beliefs and attitudes in common. Additionally, layering in behavioural data can help inform when and in which channel a message will resonate the most.
A typical marketing technology ecosystem includes several point solutions that each generate and capture customer data that can be used for segmentation not only within the channels that particular system directly serves, but across other channels as well. Email marketing response data, like opens and click-throughs, can inform content delivery on-site, and social profile and other first-party identity data, in turn, can inform your email marketing campaigns.
Marketing messaging should always be crafted and designed with a target audience in mind to some extent across every channel, with interactions on more personalised, one-to-one devices and media becoming increasingly relevant as more granular customer data is available. From localised television commercials to customised onsite content recommendations, segmentation is the first step toward building a relevant, meaningful and personalised customer experience.
Although personalisation focuses on creating a one-to-one experience based on what you know about a specific individual, segmentation enables marketers to identify customer personas and group like-minded individuals who demonstrate similar behaviours and characteristics, together. How you determine those segments depends on your objectives, and segments may change over time as customer behaviours evolve and additional, deeper data is collected.
Good segmentation models try to get as granular as possible, including criteria like Customer Lifetime Value (CLV) to help marketers prioritise their advocates over fair-weather friends, as well as identify opportunities in customer groups who may be one or two compelling offers away from transitioning into a more valuable segment.
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