Digital marketing: analysing the customer journey and simulating win-win scenarios



Problem

Digital marketing and ADV campaigns base their strategies and budget planning on the return on investment (ROI) calculated on last-click conversion. Marketing and communications departments of product and service companies, however, need to know not only which channel determines the last click, but also the customer journey, i.e. how the customer gets to that last click. In multichannel digital marketing and ADV situations, understanding the overall user behaviour from the very beginning to the last click allows companies to obtain objective value indices of each channel that influences conversion but not just impressions. In fact, standard conversion analysis models only take into account one or a few channels analysed altogether according to the last-click method, rewarding therefore the last media visited even if in order to get to that last purchase click, the user has gathered information elsewhere. In terms of strategies and allocation of resources and budget, it becomes important to know also the value of those channels that do not lead to conversion but play an important role in the customer journey.

Moxoff Solution

To analyse and gain a global insight into the behaviour of the user’s customer journey, individual (first party) data acquisition models are used, encrypted and reprocessed, of all channels visited by the user from the very beginning to the last stage of the conversion, and mathematical models and algorithms capable of calculating and attributing a value to each channel. By combining simulation analysis models, the system provides, in a very short time, both performance data on the ongoing performance of ADV campaigns and simulations of cost-effective scenarios for the planning of future ADV campaigns and marketing strategies. The proposed simulations are based on the performance history of previous campaigns and valuable mono- or multi-channel information from the customer journey. The computing and forecasting systems used allow the rapid analysis of a large amount of data generated by the customer journeys of all users, with a high degree of customisation of the analysis according to the user’s needs.

  • Customised, autonomous, accurate and rapid simulations of investments and revenues of digital marketing and ADV campaigns
  • Extensive analysis and interpretation of customer journey and multichannel value attribution
  • Processing of big data, generated from each user’s customer journey



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