Segmentation is a process that aims to divide consumers into groups with specific characteristics and behaviours. Correctly performed segmentation allows for making better business decisions and reaching customers more effectively with one’s offer. How can segmentation encourage consumers to make a purchase and increase sales?
What is behavioural segmentation?
Each consumer group is a separate market with diverse needs, expectations, and behaviours. Behavioural segmentation enables to specify certain types of behaviour on a website, in an online store or application. It is performed on the basis of actions taken, such as time spent on the site, most frequently viewed products, response to advertising, time of order completion, browsed blog articles, or clicks on links. Segmentation also applies to the way consumers shop – on a mobile phone, tablet, computer, or using all devices (e.g. searching for a product using a smartphone and completing the order via laptop). Behavioural segmentation also comprises customer loyalty, purchasing patterns, decision making process, motivating factors in the form of discounts or promotions, or expected benefits and their weight for a given group. The brand perception and feelings after the purchase are equally important.
RFM analysis – a key to customer segmentation
RFM (Recency, Frequency, Monetary) analysis allows for evaluation of customers based on previous purchases and increasing conversion opportunities. Thanks to the RFM indicator, we can determine customer’s value and predict their behaviour and response to future advertising messages.
Recency – thanks to historical data we will be able to divide customers according to the time that has passed since the last purchase.
Frequency – conversion analysis will provide information on how many times a given customer has made purchases in an online store and whether he or she can become a loyal customer (heavy user). It is also worth identifying users by the value of purchases.
Monetary value – determines the value of a given customer based on all historical data. It is worth analysing the purchase values compared with the frequency of finalising orders.
Based on the collected data, it is possible to better estimate customers’ value, as well as make decisions on further investments and advertising activities. RFM analysis is a simple way of segmenting users, which allows for optimising expenses on online store promotion, as well as getting answers to key questions: when, where, and how customers shop.
Use of behavioural segments in push notifications
Thanks to push notifications it is possible to easily segment users based on their behaviour and customise the offer accordingly. Given the frequency of recipient visits to the site, it is a good idea to send a short message encouraging them to return or remind them of an abandoned shopping cart. An equally good solution is to program dispatch of notifications for customers who need more motivation to buy the product they are interested in. This can be a special discount or free delivery.
To further increase the effectiveness of messages, it is worth observing users’ reactions and, if necessary, assign them to another segment – purchase patterns, needs, and expectations of recipients are likely to change over time. Customers who change shopping patterns are not particularly attractive to online stores. It may happen that despite taking advantage of the attractive discount, they go to the competition. Therefore, it is worth giving users extra benefits, e.g. delivering valuable blog articles via push notifications – not necessarily of purely advertising nature.
