Advertising companies strive to have as comprehensive a view of their customers as possible in order to be able to target their communication in a more targeted manner. Data Management Platforms (DMPs) can help to make existing data in the company usable to optimize digital marketing.
A DMP is aimed at collecting and managing Internet user data for advertising purposes. This includes all types of interactions, including media campaigns and on-site activities. The DMPs are also striving to incorporate customer data from the CRM, such as previous transactions - even offline - into the system. The connection to a demand-side platform (DSP) makes it possible to activate data segments for marketing in the form of programmatic advertising. Companies that introduce a DMP usually pursue the following objectives:
In contrast to DMP, there is a customer data platform (CDP) that is designed to collect customer interactions at the point of sales (POS), via call centers or even via e-mail. The contact information in the CDP is personal and therefore cannot be activated for programmatic advertising from this system. The data in it is often used for analytical purposes, for example to calculate customer lifetime values and use predictive analytics to predict customer behavior. On this basis, applications for more intelligent dialogue marketing are possible. The DMP can also be used for customer dialogue, but offers further options. The challenge is that only anonymized profile data is used. Programmatic advertising can generate high reach when addressing existing and potential new customers and makes it possible to precisely design advertising management and precisely measure user interactions. In order to achieve the goal of bringing together all relevant data for this purpose, it is necessary to establish links to both CRM data and the advertising delivery page. This is done by matching cookies and advertising IDs.
What can a DMP do for marketing
Programmatic marketing management from the DMP is usually aimed at (if necessary, also very granular) customer segments that have common characteristics. By excluding existing customers from the campaign and modelling statistical twins of the most valuable buyers, prospecting or lookalike targeting can be used to attract new customers in a targeted manner who have comparable customer value. In the same way, targeted measures to reactivate existing customers can be implemented. Since programmatic management is bid-based, it is possible to assign different (appropriate) prices in media purchasing to different customer values, so that higher campaign efficiency is achievable. Taking into account interactions with advertising materials and your own website, so-called sequential messaging or storytelling can be implemented when approaching new customers. An automotive manufacturer, for example, can address its interested parties, who have already carried out a vehicle configuration, more individually and incorporate personal desired colors in the advertising material shown to them. An airline would consider the destinations sought and include them in advertising aimed at the corresponding users. Previous advertising contacts can also be taken into account, so that the consumer is shown a different commercial (ideally based on the previous one) than the last contact. The programmatic advertising is displayed on both desktop and mobile via display and video advertising. In principle, the DMP makes it possible to address the user profile across devices and to optimize the overall contact frequency in order to increase the efficiency of the media budget. Advanced DMP scenarios for adding the offline buying behavior of your own customers take into account data from your own customer card programs or from mobile apps - for example via coupons. In this way, it is possible to show which accessories or which additional service can be usefully offered to the customer or even which product no longer needs to be advertised. Since companies' own database is subject to restrictions - including due to the number of customers and possibly also limited options for online interaction between customers and the company - the DMP usually enables enrichment with external data. 3rd party data from specialized providers as well as 2nd party data from data partnerships agreed by the company itself can be integrated. For example, external purchase intent data is available, which in turn enables a tailored approach. For example, an insurance company could specifically advertise motor vehicle insurance to a prospective car buyer. In the area of data partnerships, it would be conceivable that the airline would join forces with a telecommunications provider to share B2B customer data.
What are the challenges for use in companies
In addition to the willingness of the participating departments to combine different data, companies that want to implement a DMP are primarily faced with the problem of how to evaluate individual providers. It is therefore essential to develop a data strategy in the company first. These should then be translated into concrete marketing use cases, the feasibility of which the individual solutions must finally be tested. There are, of course, legal challenges, particularly against the backdrop of the European General Data Protection Regulation coming in May 2018. Advertisers are therefore faced with the decision whether to manage the implementation process in-house, through external consultants or in collaboration with the selected solution provider. For the operational sector, there are quite complex challenges in creating a corporate culture that welcomes and understands data-driven marketing and in attracting or qualifying specialists. In order to develop effective strategies and show the right advertising messages in the right context to the right customer segments, marketing experts need both analytical, technical and customer-focused, creatively oriented understanding - quite high demands on marketing managers to ensure future corporate success using the technological options that a DMP also offers.
This text is first published as an expert contribution to ChannelPartner appeared.
