To customise a loyalty programme, you must first segment your customer base, as we explained in our article on how to segment customers for a customised loyalty programme. Secondly, you will need to have set up your loyalty programme bearing in mind certain essential elements that will ensure that your programme performs well (read our article on the essentials of setting up a loyalty programme).
As a result of these first two steps, you will now be able to identify your customers’ status and their level of loyalty, plus their similarities and their specific behavioural or purchasing characteristics, all of which will enable you to continue to develop your loyalty programme.
Indeed, segment analysis is a crucial step that will enable you to make the most of all this data to customise your loyalty programme according to these differentiating criteria.
How to customise your loyalty programme based on segmentation.
Testing, measuring, analysing and improving are the key words that will enable you to offer a personalised customer experience. Setting up scenarios to A/B test your activities makes it easier to monitor how each segment reacts and to adapt them accordingly.
Also, you can vary the types of content (product information, games, polls, etc.) according to each segment’s interest and reactions.
Similarly, setting up a preference centre can enable you to monitor and respond to your customers’ changing expectations.
Here are some important segmentation elements to consider when customising your loyalty programme:
Each segment’s engagement
The RFA method1 enables you to set out KPIs for the different groups and to be able to move each group to the next level, increasing the proportion of the group in the segments that bring you the most turnover, etc. For example, what is the share of VIP customers in relation to the overall population? How can you increase this share? How can you move “very good customers” to the next “VIP” level? And so on.
Membership of these segments may then trigger the allocation of personalised benefits (temporary or permanent) or specific treatment (such as priority after-sales service).
1 RFA method: a segmentation method that classifies customers according to their buying habits. It takes into account the criteria of Recency (date of last purchase), Frequency (number of purchases over the given period) and Amount (sum of purchases accumulated over the given period).
Recency of last visit
By creating a calculated value for the recency of their last visit, you can target your customers according to the time that has elapsed since their last visit (more than 6 months, between 3 and 6 months, less than 3 months, etc.) and incentivise them with specific automated messages or with specific offers.
You can also identify customers who are drifting away and understand why they are coming back less often, so that you can offer them communications that are more tailored to their needs, so as to encourage them to return.
Identifying the proportion of active and inactive people in each segment is crucial. On the one hand, inactives do not generate turnover and, on the other, you risk losing them as customers.
This information enables you to find a way to reactivate them as soon as possible in order to keep them in your customer portfolio and avoid the risk of losing them. For example, you can set up A/B testing campaigns to identify which types of campaigns or which communication channel they are more responsive to. Surprise them and make them come back, show them you love them!
Concerning inactivity, it is important to differentiate between relational and transactional inactivity. It may be that an occasional customer has a strong relationship with the brand and may even be a brand ambassador who publishes reviews even though they only buy occasionally, just as a VIP customer may buy frequently but prefer not to be approached by the brand.
Numerous segmentation methods allow you, after analysis, to offer personalised benefits to your customers according to various criteria and your objectives.
As we said earlier, analysing your segments’ reactions should be an integral part of your strategy. Tracking the results of the actions you have taken allows you to rethink how you personalise your loyalty programme and set out new objectives. Then, you can mainstream effective operations and adjust others.
With its CDP (Customer Data Platform), its Loyalty and Audience Builder modules, Scal-e facilitates the creation of statuses, on the one hand, and segments/audiences within each of these statuses, on the other. Through these, it helps you to identify your most loyal customers, as opposed to occasional customers, and therefore offer them personalised benefits and exclusive offers.
Scal-e is a CDP (Customer Data Platform) that enables you to connect several data streams (website, points of sale and others) in a single datamart. In this way, brands can access their data, such as unified customer profiles and real-time information, to get to know their customers better and respond to their needs at the right time, through the right channel. From the same platform, brands can also build their marketing strategy (audience builder, scripting, planning, loyalty and referral programme) and apply it without having to change software.