Our customers testify – Florence Vadivelou: Marketing Product Manager How did you come to work with datacadabra? In 2022, following the end of the collaboration with our previous service provider, we wanted to call on a partner who would provide us with greater transparency and education in the creation of our scores and targeting.Previously, we were equipped with a tool that was certainly a “button-press”, but ultimately a “black box”, as we only had the result of our target, but not the chain of processing that led to this result.Today, datacadabra meets our needs. Thanks to the platform and the support we receive, we can easily regain control of our targeting strategy and understand how our scores are constructed. How did you regain control of your targeting strategy? datacadabra allows me to be autonomous, I can adapt my targeting infinitely according to my marketing plan. Beyond the platform, the teams are available and responsive to our needs. So we’re not alone with the tool, which is a real plus.We have regular copil meetings where we can discuss the results of our operations and get advice from our account manager accordingly. These exchanges have enabled us to improve the quality of our scores and the relevance of our targets. In 2023, our return rate on the operations concerned rose by an average of 30%.We are starting 2024 with a number of projects. For example, we are currently reviewing the sequencing of our selection criteria, setting up new scores for new targets, and looking at parts of our file that we did not address in the past. How do you manage your file activity? All the specific dashboards produced by datacadabra as part of our datacadabra Insight subscription enable us to manage our file activity on a daily basis. As our products are not sold on newsstands but only by subscription, we needed dashboards adapted to our business sector. We can now track subscriber activity and subscription results, while also monitoring more traditional indicators such as attrition and recruitment. What’s datacadabra’s little plus? Without question, their responsiveness, thoroughness and advice. The commitments made are fulfilled, and it’s a pleasure to work together in this relationship of trust. If you’d like to learn more about datacadabra, don’t hesitate to request a demo!

It is essential to identify the segments to which your customers belong, in the long term it is even more relevant to analyze the transition matrix in order to improve your marketing strategy. The challenges of segmentation: setting the foundations  If we compare data exploitation to building a house, then customer segmentation will allow us to set the foundations. Firstly, segmentation will allow you to understand the structure of the customer base and to identify the different groups to be animated. The resulting indicators will allow you to build a strategy based on customer value and loyalty. However, simply looking at the picture of the segmentation at a given time may not be enough. You must also pay attention to the transition matrix. The interest of the transition matrix Indeed, when analyzing segmentation, it is important to take into account long-term dynamics. In particular, it is essential to study the flow of customers between two segmentation periods, which is called the transition matrix, or flow matrix. The idea of the transition matrix is to determine in what proportion the customers of a segment at a given moment in year N will migrate to another segment in N+1. Two types of matrices can be calculated. The volume matrix allows us to know how many customers have moved from segment A to segment B between two periods. The percentage matrix will allow to measure the proportion of customers migrating from one segment to another. Example and analysis of a datacadabra transition matrix As an example, this percentage transition matrix will allow us to see the proportion of customers who move from one segment to another between the segmentation calculated in N-1 and the segmentation calculated in N. We are thus interested in three types of movements. The first key piece of information to analyze is the stability of clients, i.e. the proportion of clients who remain in the same segment between two dates. This information will allow us to validate the level of loyalty of high segments (VIP / TBC here). We can then analyze the upward flows, i.e. the customers who have seen their segmentation level increase over time. This will allow us to measure the extent to which the actions taken by the brand have improved the quality of the base over time. Finally, the downstream flows, i.e. the customers who move from one segment to a lower one, will allow us to see to what extent attrition is an issue to work on as a priority. If we look in detail at the results presented in this matrix, we can see that 43.6% of VIPs have remained VIPs, 34.3% of very good customers (TBCs) have remained TBCs, etc. These levels of stability are fairly average and highlight a problem of loyalty among the core target. It will be necessary to implement specific actions on these segments to increase their commitment. It should also be noted that 53% of new customers (N) become inactive after one year. The nursing plan could therefore be improved in order to improve the quality of recruitment over time. We also note that nearly 25% of good customers (BCs) and more than 50% of COs become inactive after one year. It would therefore be interesting to work on the anti-attrition processes for these targets. To sum up, the analysis of the transition matrix will make it possible to identify the major issues on which to focus the animation strategy (nursing, anti-attrition, reactivation, loyalty of the core target group, etc.) and to determine the additional analyses to be carried out to optimize the action plans. How does datacadabra support you on the subject?  Within the Segment module, the different segmentation methods natively propose the transition matrices over different periods. They are enhanced with automated comments to measure the observed performance. Want to know more? Do not hesitate to contact us or to ask for a datacadabra demo.

RFM, relational, behavioral, there are many types of segmentation, many complementary methods at the service of marketing performance. Types of segmentation for differentiated marketing  When you want to implement differentiated marketing, the first question is how to determine which customer groups you will be able to animate, as there are many types of segmentation. For this purpose, the basic concept of “market segments” will be used. This concept is used in market research, but also in relationship marketing in order to structure your actions and communication. In the context of differentiated marketing, market segments are groups of customers that are homogeneously characterized by a combination of factors, such as their needs, preferences, actions or size. They can be identified by a multitude of different criteria. It is these criteria that are used to identify the type of segmentation used. Transactional segmentation: the RFM method The first type of segmentation that comes to mind is transactional segmentation. Indeed, this type of segmentation, which is based on the purchases made by customers, is often the basis for any differentiated business strategy. Based on customer value, RFM segmentation is the most common method of customer segmentation. It takes into account the Recency (date of last purchase), the Frequency of purchases over a given period and the Amount (the turnover over the period studied) to establish homogeneous customer segments. The purpose of this segmentation is to help you approach the 20/80 law to identify the customers who contribute most to your company’s results.When you have a more limited transaction history or when the frequency of purchases is very low, you can also use the PMG segmentation. This is essentially based on the notion of the cumulative amount of purchases over a given period of time to constitute the groups of customers. Relationship segmentation: measuring the level of commitment. When you animate a population of customers, it is often interesting, in parallel with identifying the transactional value of individuals, to measure their level of commitment.Indeed, we often ask ourselves the question of the commercial pressure we apply to our customers. Are we asking too much of them? Or not enough? Do some customers systematically open our communications? Do some of them show a significant lack of interest in my messages despite the solicitations we send them? While there are different methods for calculating relational segmentation based on available data, the purpose is always the same: to better understand customer engagement with the brand. The results will show how many customers are most loyal, most supportive, most critical or most disengaged. By organizing customers into these groups of segments, marketers can more easily target their actions. Product segmentation: how your customers consume   Another interesting area of analysis is the products consumed. A product segmentation will thus make it possible to identify how customers consume your different products, which ones are the most loyal or which ones should be highlighted in communications. This type of segmentation will also allow you to better understand product mixes. Behavioral segmentation: reconciling data typologies The last example of segmentation is behavioral segmentation. This will make it possible to reconcile different types of data (sociodemographic, transactional, relational, etc.) in order to create groups of customers with homogeneous behavior. Combining the different types of segmentation There are a multitude of segmentation techniques. By combining these different areas of analysis, you can determine, for example, which customers are the most profitable, which are the most loyal, or which customers should receive more attention in communications. How does datacadabra deal with this subject? datacadabra offers a large number of segmentation methods natively within the Segment module. Want to know more? Do not hesitate to contact us or to ask for a datacadabra demo.

Dividing your customer file into homogeneous groups has many advantages in marketing efforts, segmenting your customers is therefore a key performance factor.  Why segment your customers? What is segmentation?  Very often, the knowledge you have of your database corresponds to the image you have of your average customer. The objective of segmenting your customers is precisely to “break” this relationship with the average and to identify different groups of customers through segmentation. Segmentation is defined as the action of dividing a population (customers, prospects) into homogeneous sub-groups according to different criteria (sociodemographic data, purchasing behavior, etc.). The segmentation criteria chosen must make it possible to obtain segments of homogeneous populations of sufficient size and operational. The main objective of segmentation is to understand the similarities between customers in the same segment and the differences in behavior between the different groups. Segmenting your customers: a key performance factor Marketing segmentation is an essential strategic step that will allow you to optimize your marketing efforts, to better satisfy your customers and therefore to increase your profitability. In particular, segmentation will bring key benefits that will increase performance. Segmentation to help customization of the customer relationship Firstly, segmentation will allow a better customization of the offer and messages to existing customers. Indeed, a well-constructed segmentation will allow to identify distinct groups of individuals in terms of consumption and profiles. We can therefore move from mass marketing to segmented marketing. This first point will have a direct consequence: the improvement of the global performance. Indeed, by having more targeted speeches, closer to the expectations and needs of customers, we will be able to increase the overall performance of our animation plan. As a general rule, without any other optimization tool (scores for example), segmentation can lead to an increase in sales of around 2 to 5%. This obviously requires a reflection on the animation strategy to be adapted to each group according to the problems to be solved: increase loyalty, fight against attrition, improve customer reception and the commitment of new customers, boost reactivation… Adapt and reduce your commercial pressure At the same time, customer segmentation will allow you to better adapt your commercial pressure to the different groups. By analyzing the needs and expectations of the different customer groups, it will be possible to define the optimal commercial pressure and send only the necessary messages. Beyond the economic (and environmental) impact of a reduction in the number of messages sent, this will also have a positive impact on customer satisfaction, as they will perceive the brand as more attentive to their needs. Optimize available resources More generally, segmentation will also allow the company to better allocate resources. By having a more precise vision of the profitability of each group, it is indeed easier to define the right rate of generosity, to adapt the types of promotion, to manage the time to be spent by the sales representatives on such or such target… In short to define the means adapted to each group of customers. Define your target audience to increase your brand awareness  A better control of your customer knowledge resulting from the segmentation will allow you to better know your core target. As a result, institutional and general public communication will be better adapted to its target. It will therefore be more effective and will increase the brand’s awareness among your target audience.  Strengthen your acquisition strategy  Finally, the segmentation of your customers will allow you to optimize your acquisition strategy! For example, when you set up a digital acquisition strategy, if you base it on the average profile of your customer file, you will recruit very loyal customers, occasional customers and future inactives without distinction. By focusing your strategy on the best customers of the segmentation, you will probably recruit a little less but in a more targeted way and therefore more profitable in the long term! How can datacadabra help you?  Within datacadabra, the Segment module allows you to build different types of segmentations based on your available data. Want to know more? Do not hesitate to contact us or to ask for a demo of datacadabra.