Big Data is on everyone’s lips. The amount of data processed through companies, agencies and other institutions, is continuously growing. In 2020, worldwide 44 zettabyte of data will be sent. In 2013 it was 4,4 zettabyte. 22 % of it was useful and could be employed for marketing activities according to a recent study by EMC. So far, only less than 5 % is used. The potential of Big Data is still insufficiently exploited. Big Data however presents a significant competitive advantage according to 63 % of surveyed companies in a study carried out by IBM.
One of the biggest beneficiaries of Big Data is digital marketing, especially online direct marketing. Modern online direct marketing is individualised, context-sensitive lifecycle marketing in real time, which approaches the user at each point in his customer lifecycle using exactly the communication, which matches his preferences. In order to generate information about user profiles, we will first need personal data, which is left behind by users at different (digital) touchpoints. This could be transaction data from online shops and bonus systems, response data from email marketing campaigns or other digital contact points. By assigning this data to a dedicated user profile (profiling) and by using different analysis tools from scoring models to complex data mining procedures, we can gain a marketing-relevant insight about individual users. For which products is there a particularly high affinity? Where are the cross and up-selling potentials? How high is the user’s willingness to pay? At what times and with which offers and which communication can the user be activated the easiest? In which time and spacial context is the desired user behaviour the most pronounced?
Collect the Right Data
The marketing potential of Big Data still lies idle in many areas. Data may be collected, but not used in a sensible way. First saving everything and then looking at what to do with it, is still the rule in many companies. Even data, which is not relevant, is collected. Potentially useful data is often insufficiently processed: unstructured, untagged, saved in the wrong location and partially not even legally-compliant. To convert this data into useful data, means a significant expenditure. Companies must move away from the random saving of data. Instead, from a start, they should collect only the data really necessary and manage it in a structured way, ensuring consistent legal security from the collection to the use.
Which data is required in online direct marketing depends on the specific marketing targets in each company, e.g. the measures, which are chosen to fulfill these targets. Firstly, we need to define which types of individualisation would be sensible for the individual measures, i.e. which can verifiably increase the success of the measure. The next question is: Which information about users is necessary for this individualisation? An then: Which data is required to generate this information with the existing analysis methods? Once the requirement of data for individual communication is identified, we need to check all available touchpoints so see if they can generate the required data. However, personal user data can only be collected with explicit user consent. One of the great challenges for online marketing therefore is to generate sufficient consent for the use of personal data within the framework of a legal data use management.