Segmenting your data
You need data such as location, job title, and interests to accurately segment your audiences.
Segmentation goes hand in hand with personalization. It allows you to target large groups at once, while still delivering specific content that’ll engage those readers and lead to conversions.
An example is a fashion brand could create a segment of customers who they know have a preference for a specific category, in this instance, let’s say dresses. By grouping together all of those customers and prospects that they know are interested in dresses – whether they know this from asking customers in a preference center, or from behavioral data – this segment would be great to target with an email focused on dresses. Similarly, B2B brands could segment based on authority level. Collecting job titles to identify budget holders and decision-makers to create a segment, ready to send relevant messages to.
Once you have segments identified, you can either create specific campaigns targeting individual preferences, or you can create a single campaign and use dynamic content blocks to personalize for each segment.
The bigger and more diverse your offering is, the more vital data gathering is. Large businesses such as department stores need to be driving customers to update their preference centers. Doing this regularly will ensure customer demands are being met and you’re not sending campaigns to customers who have no interest in the content, leading to an unsubscribe.