Customization has become a must in marketing strategy. One of the first steps is to identify your personas in order to adapt your communication. Customization at the core of the marketing strategy When implementing customization actions in your marketing strategy, you must first improve your understanding of your different targets. In this case, the creation of personas can be of great interest. From a statistical point of view, typology will play an important role in this process. What is a persona? The main interest of the typology is that it will allow you to create personas representative of your customer groups. Indeed, in marketing, a persona is often defined as a fictitious person representing the group to which he belongs. The persona is endowed with characteristics specific to its group, whether it be socio-demographic, relational or transactional. To this we can often add qualitative data, from surveys or round tables, in order to improve our knowledge of each persona’s profile. The typology will make it possible to synthesize the information from the different types of data available in order to group individuals according to their proximity, measured in relation to a set of criteria that they have in common. We will thus be able to define a certain number of groups of individuals with their own characteristics. Tailor your offer to your persona The final objective is to facilitate the understanding of the different customer profiles that constitute your file. And this in a transverse way in all the company. A good tool to allow this information to be disseminated is the creation of summary sheets presenting the main characteristics of each group. This will also allow you to identify the specific needs and expectations of each group and ultimately to build action plans and a product offer adapted to each group. How does datacadabra support you on the subject? Within datacadabra, the Segment module allows you, thanks to its Typology method, to build your customer typology by associating different statistical techniques allowing you to create homogeneous groups and to obtain the assignment rules allowing you to assign this typology to your entire database. The report associated with this method will provide you with a set of group characterization elements that will allow you to define your personas. Want to know more? Do not hesitate to contact us or to ask for a demo of datacadabra.
The Sales Animation Plan is a strategic document that defines all the animation actions planned over a given period. The role of the sales animation plan The sales animation plan will allow you to plan all your marketing and promotional campaigns in advance, including the budget for each of them and the expected results. A sales animation plan is often fluid, as it will have to adapt to the context of the moment and to the results observed. A fundamental point to adapt your animation plan is to have an objective measure of your performance. As a general rule, performance can be measured on two levels. The 2 levels of performance measurement 1. Macro analysis of the plan as a whole The first level is a macro level, at the level of the plan as a whole. This level of analysis will be based on the establishment of a blank zone, a non-animated population, for a specific period of time, generally the semester or the year. During this period, the blank zone will not receive any solicitations and will thus serve as a benchmark for measuring performance. The level of activity of the animated customers can be compared to the one of the non-animated customers in order to determine different key performance indicators: additional sales, additional margin, and even the ROI of the animation plan when the gains generated are compared to the expenses made to implement this animation plan. 2. Detailed analysis at the operation level The second level is a detailed level at the operation level. In this context, we will be confronted with different problems. First of all, it is important to know how long to follow the returns. Depending on the sector of activity, the return curves are very different. It is therefore necessary to study them in order to know how long to measure the results. Next, it is necessary to plan a control population for each operation in order to measure the incremental impact of the operation itself. This will make it possible to know if the operation generates additional activity or not. This point depends on another important element: the reallocation of performance. Indeed, when many campaigns are reconciled, the question arises of knowing to which operation to attach the performance. Many techniques exist to manage this allocation: last click, equi-partitioning… The trick is to define the most relevant method. Note that without reallocating the performance, there is a risk that a transaction will be counted several times in the sales figure for customer animation. The complementarity of the different levels of analysis These two levels of analysis will provide a different but complementary reading of the results. The first level of analysis will allow us to understand the contribution of the animation plan to the company’s overall activity and the overall coherence of the system. The second level of analysis will allow us to understand if the animation is coherent in itself, and what are the factors that lead to the success of the communication plan. Thus, it will be possible to identify the types of campaigns to be favored, those to be limited, and even define the campaigns to be stopped. How to treat the subject with datacadabra? Within datacadabra, the Follow module offers, with the Campaign Follow-up, a simple method that allows you to work on the detailed performance of the operations performed. This method natively proposes the calculation of the additional per operation taking into account the reallocation of the performance. This method has its own performance reallocation algorithm which allows to take into account the different messages received by the client over a given period by attributing a different weight to them according to their proximity to the transaction. We thus obtain a rather fine reading of the results obtained. Want to know more? Do not hesitate to contact us or to ask for a demo of datacadabra.