What data and for what uses?
In addition to the traditional socio-demographic, product (equipment) detention and purchasing data, the new challenges that have emerged involve the behavior patterns that characterize the use of digital channels and media. Digital interaction logs, coupled with conventional data, are a real source of added value that is just waiting to be exploited. You must make the data talk, so to speak! This is now the main focus of the development of customer knowledge.
Now that we have discussed the creation of a preference center, let's examine the most practical steps that can be taken in this area, bearing in mind that our second objective is to make the data actionable. We will focus on a number of themes and priority areas for development:
Define the affinities of each customer as regards communication channels
Can you measure each consumer's use of the interaction channels that you make available to him and that you have used to communicate with him? First find out what his preferences are and then identify the most frequently occurring customer "journeys". I am referring to the different phases of use and switches from one channel to another that now characterize a consumer journey from the initial stimulus to the hoped-for opt-in, subscription or purchase.
Exploit the behavior and expressions of interest connected with the use of the email channel
Email is and will long remain a reliable channel as far as the relationship with customers and consumers is concerned. Beyond the traditional campaign-based measures, it is now in our interest to control the opening and clicking behavior by consumer and by type of terminal used. Just think of all the people who now read your emails on their smartphone (the advantages of responsive design) and who have a two-tiered response (filtering via smartphone, reaction via tablet or PC) and of the period that might elapse between receipt and opening, etc. The second priority area for development within the email channel is the exploitation of the actual clicks, which provide information on the areas of interest of each consumer/reader and therefore provide you with many opportunities for high added-value retargeting.
The introduction of the life cycle concept
This concept enables you to determine for each consumer in the database the precise stage of the relationship cycle he is at in relation to your brands. The classification methods according to frequency/recency are among the basic components of this approach. The state of the art consists in identifying the key moments in the relationship with your consumers, and in putting down markers to track the progress achieved in the degree of intimacy and loyalty that characterizes the relationship between your brand and each of the consumers in the database. Examples include the traditional welcome pack, the satisfaction survey that follows the delivery of the first purchase, the encouragement to make a second purchase, the sending of a "getting to know you better" questionnaire, the transition from one RFM segment to another, the crossing of thresholds in terms of "loyalty points", etc.
The introduction of methods based on "event-triggered marketing", multi-stage approaches based on the scripting of interactions
This approach naturally follows on from the previous stage. Once the key moments have been identified and mapped, they should be transformed into opportunities for added-value contact. Automated mechanisms (the interaction scripts) must then trigger this individualized communication and industrialize a systematic follow-up of restarted customers and other actions in response to the requests made and the fulfillment of the promises made.
The tracking, interpretation and aggregation of the digital space visiting behavior
Why not apply methods on your own media (sites, e-commerce applications, pages on the social networks and mobile applications) similar to those used by panelists and online advertising people to describe and assess audiences? By placing cookies in the browser of a large number of consumers who visit their websites or the websites of the members of their networks (subject to compliance with strict rules), these operators gather large volumes of behavioral data relating to what people do on the Internet. They then assess these data while permitting retargeting by email or via the publication of banners or packaged content. There are now solutions out there that allow all advertisers to use these same methods on their own customers and prospects, totally independently and using first-party cookies. So I ask you, would you like to be able to send targeted and personalized offers to customers and prospects either by email or the next time they visit your own digital media? You can be among the most seasoned operators in the field of interactive marketing and learn:
- To retarget visitors to your digital spaces by email
- To retarget in real time the people who are connected to any of your digital spaces
The systematization of "test and learn" approaches
The advantage of the digital media is that they provide a means of implementing the systematic tracking of browsing, opening and clicking behavior. They therefore open up the possibility of making effective use of multiple test methods. The basic components of these approaches are the traditional "split testing" or "AB tests" and multivariate testing (MVT). These techniques provide a means of optimizing opening and clicking behavior in relation to emails, banners and landing pages. However, these are not mere tests of the components of a given marketing mechanism. They also permit comparison of alternative tactics relative, for example, to the number of customer restarts (repetition) or the combination and chronology of channel use within the framework of a given process.
The exploitation of datamining and customer intelligence tools
This is of course the final stage that allows you to go beyond the results obtained after having used the techniques discussed above. This stage involves:
- The profiling tools
- The methods used for segmentation and the definition of personae
- The methods used for scoring and the "next best action" concept
Each of these methods would merit an entire article.
Digital marketing and interactive marketing methodologies provide a means of capturing massive volumes of behavioral data. Coupled with the data relating to profile, product detention and transactional history (purchases, consumption, transactions, etc.), they have proved very useful tools for the development of customer knowledge, in particular through the methods of advanced statistics. In addition to the major contribution that they make within many statistical models, they have tremendous operational value insofar as they provide a means of implementing retargeting tactics and the multifarious methods of event-triggered marketing.
Faced with these various challenges, only an "integrated" approach to information systems will enable you to develop your action plans (operational marketing) at a steady pace in the areas of customer knowledge and efficiency. I wish you all every success.