Blog 92: Crafting a personalised experience for customers?

In blog 78 we looked at different ways to segment or bucket our customers. There are broadly six ways to do that i.e., demographic, geographic, psychographic, behavioural, need-based, and technographic.

In this blog, we will be delving deeper into behavioural. Using behavioural segmentation, we can create more personalised marketing campaigns and experience. The more patterns we recognise the better we can match our product experience with customer expectations. Thus, increasing the chances for customer loyalty.

According to a McKinsey survey, 76% of respondents were likely to stick with brands offering a ‘personalised experience’. Because marketing messages that tick with one segment may not work with another. A segment may be attracted by our YouTube content while another by one specific feature. This will mean proactively understanding different customer journeys (that continuously changes - refer blog 16 for more on customer journey map). Followed by A/B testing various scenarios to identify what works best for each journey type. And then communicate with a precise message applicable to that segment.

Behavioural segmentation will result in segments based on frequency of purchases, frequency of usage, purchase timings/occasions, customer’s journey stage, customer intent & motivation, loyalty & satisfaction levels etc.

Some real-world execution tactics when we use behavioural segmentation:

·       Send gift ideas with discount codes (if applicable) when a customer's special occasion is round the corner.

·       Send upsell offers once the customer is satisfied with the original purchase.

·       Create customised win-back campaigns targeted towards unhappy customers.

·       Craft tiered loyalty programs that work for the company and the customers.

·       Design product experiences that ensure customer stays connected and engaged (for example, with a subscription plan).

Each of the above tactics need to be measured for its effectiveness. Use metrics such as open rate, returning customer rate, average order value, retention rate, satisfaction or NPS (net promotor score), customer lifetime value etc. Refer blog 34, blog 58, blog 83 for more on metrics and product analytics.

Jump to blog 100 to refer to the overall product management mind map.

All the best! 😊