Creating personalised customer experiences is all about customer insights.
Indeed, in order to offer a loyalty programme that meets customer expectations and needs, it is necessary to secure and analyse information about them.
To be able to create relevant segmentations, you will first need to collect your data records (including loyalty data) and find distinctive behaviours and elements, such as frequency and type of purchase, amount of purchase, frequency of activity (opinions, purchases, etc.).
Once your data has been collected and unified, you have all the information you need to analyse your data and segment your customers. This is the first step that will allow you to set up your loyalty programme and tailor it to your segmentation.
Segmenting customers through data analysis
Before you can set up and customise your loyalty programme in your loyalty management solution, you must first segment your customer base.
From the data collected upstream, you will be able to analyse the wealth of information collected and identify the missing information for possible recovery if necessary(using the Scal-e platform’s DataViz function).
Then, a first segmentation can be set up. You can segment your customers according to a variety of criteria: transactional, geographical, behavioural, demographic, etc.
For example, you can choose to create an RFA segmentation1 , by taking into account your customers’ activity to set out SML (Small, Medium, Large) profiles. Thus, you can classify your customers by status and define different segments: VIPs, Very good customers, Good customers, Occasional, Opportunistic, etc.
Scal-e’s SegmentViz feature facilitates the visualisation of segments and allows immediate identification of areas of overlap (product or social network consumption) or separation (belonging to a single qualifying segment, such as status segments).
| 1 RFA segmentation: 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). |
This segmentation can easily evolve to get a better view of your customer portfolio. Each member is attached to a segment and can be activated individually (e.g. Birthday, or by the After Sales Service) or collectively to create, obtain or use benefits.
In Scal-e, as segmentation is based on the same engine as targeting, you can also create permanent audiences, which can be addressed in different ways according to your objectives.
Examples of segmentation for your loyalty programme
Here are some examples of segmentations you could create:
- Inactive: People whose last activity was more than 24 months ago.
- Sleeping: People whose last activity was between 12 and 24 months ago.
- Prospects: People who have not yet made a purchase and whose last activity date was less than 12 months ago.
- Customers: People who have made a purchase in the last 12 months.
- New prospects: People registered less than 30 days ago.
- Recent buyers: People who have made a purchase in the last 30 days.
- VIPs: People who have spent at least “XXX” euros over the last 365 days.
There are also functions in Scal-e to calculate the length of a subscription, the time since the first/last purchase, etc.
Avec Scal-e, toutes données, qu’elles soient importées ou calculées, de tous les champs du datamart Fidélité (module CDP nativement connecté au module Fidélité), peuvent être utilisées pour créer des segments en mode drag and drop (donc no code) grâce au module Audience Builder (segment, score, agrégat et champ calculé).
With Scal-e, all data, whether imported or calculated, from all fields of the Loyalty datamart (CDP module natively connected to the Loyalty module), can be used to create segments in drag and drop mode (therefore no code) thanks to the Audience Builder module (segment, score, aggregate and calculated field).
With a set theory solution like Scal-e, you can easily create segments by exploiting all the data (marketing, transactional, relational, etc.) in the CDP, specific criteria (status, number of points), similarities or common behaviours to improve personalisation.
| The advantage of set theory for your business teams The Scal-e solution uses set theory (intersection, union, exclusion, etc.) to segment your contacts according to characteristics linked to their profiles, purchase behaviour, visits, reaction to a message, etc. Unlike highly technical tools, this approach makes creating a segment much more fun than an engine based on queries using “IF… THEN…” that don’t really resonate with business teams. In addition, most query engines only provide a final result, whereas an engine based on set theory provides all the intermediate calculations, which makes it much easier to understand and modify a segment. |
Do you want to implement a loyalty programme or upgrade your current one?
To learn more about customising your loyalty programme:
- Read the article The essentials of setting up a loyalty programme.
- Read the article Customise your loyalty programme based on segmentation.
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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.
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Scal-e, the cloud marketing platform listed in Forrester's Now Tech CDP, makes it easy for B2B and B2C brands to implement and improve the results of customer acquisition and retention campaigns.