For marketing, single view of customer is history, context is the future?
The real time context in which we operate is now something which can be tracked, measured and acted upon, paving the way for new forms of digital messaging. This leads to the question, is customer history relevant and if so why are we spending so much time and money building the illusive single view of our customer? Let's explore what's going on.
Tagging and tracking the consumer’s movements and actions – real time context
There have always been mechanisms for tracking on line activity, with cookies being the favoured variant, leading to regulations on whether we are tracked or not on a particular site. The rapid growth of data management platforms means that activity can be correlated across multiple sites and locations, giving a richer picture of a non identified user’s behaviours in a near real time view. These near real time profiles can be used to drive ad management platforms through programmatic advertising. Platforms such as Oracle BlueKai are a good example of these aggregation platforms that rely on non PII data to create targeting profiles.
We can now add to this the ability to track users as they move across channel on owned media creating detailed journeys and profiles. Platforms such as Thunderhead enable these cross channel profiles to be built up supplying data to optimise journeys and inbound messaging and offers.
Mobile apps with their inbuilt SDKs provide rich sources of data which people (knowingly) sign up to even for non logged in apps. This is particularly the case when in a physical environment attached to a wifi or geolocated via another form of beacon. Copenhagen airport led the way in tracking mobiles to provide traffic data though it's terminus. We now see this opportunity landing in retailers as they seek to change from dealing with footfall to targeting customer behaviours in store and across channel.
Gathering a view of a known consumer’s interaction history – the illusive SVOC
The idea that we can build a single view of our customer’s interactions across multiple touchpoints has been an illusive goal for over 15 years. The concept spawned the CRM wave and wide ranging investment in data mining of back end transaction platforms and Master Data Management systems to reconcile the result. However, the processing cost of data extraction and analysis, coupled with the lack of consistency of permissions cross channel and the rapid explosion of new channels and interaction mechanisms has meant that a single view of customer remains an illusive concept for most organisations.
For most organisations customer data is distributed across multiple platforms supporting different channels, with differing identification mechanisms. Creating a common identity and access management service can provide the route to real time reconciliation of data and enable federated data management. This real time cross channel view is critical for modern marketing techniques as next best action techniques require marketing messages to be determined and communicated in near real time to be effective.
So to create a usable single view one either needs aggregation of data in near real time into a single database supported by MDM or (and) implementation of a global user ID to and effective data transport to allow aggregation of relevant data on demand. The cost of such system investments then need to be balanced against the potential return.
The changing marketing mix and convergence
As outbound messaging and click through rates become less effective, we are seeing new forms of marketing emerge, taking advantage of mobile applications and new social media platforms. In such an environment we are seeing a convergence between the demands of different mechanisms and the types of customer segments they serve. For example advertising driven from Data Management Platforms (DMP) can now share segmentation data and profile data with outbound marketing and campaign management driven off the CRM platform. In such an environment messaging will be driven primarily by the real time context of the customer, underpinned by the historical data. With advertising itself becoming personalised then the decision making processes for creating the unified messaging becomes more and more complex. This is the spawning the use of machine learning systems to drive the unified messaging.
Context drives complexity and a need for rapid evolution
The ability to drive marketing messages in response to a consumer’s real time and historical context is creating new opportunities for more effective, measurable marketing campaigns. This brings with it considerable complexity in operational management, data management and systems integration. In such an environment a clear focus on the potential and realised benefits is essential, however, these benefits are difficult to predict so then the ability to test, measure, learn and evolve at speed becomes critical. In my experience, for most organisations it is this change in delivery model that is the most difficult to embrace, rather than the concept of the opportunity presented by new means for digital consumer engagement.
So, to seize the marketing opportunity that digital tools provide, to leverage near real time knowledge of the consumer’s context and history, focus as much on the ‘how’ as on the ‘what’.