Digital media continues to redefine the landscape for marketers, brands and consumers alike. As these technologies continue to grow in complexity, collecting information that’s more personal and unique than ever. It has presented marketers with a wealth of opportunities to be more targeted.
User data today no longer refers to a group of key audience, but individual identities. Essentially, as we move through the world, we generate pathways of data that make up who we are. Brands collect this information, and with the right tools, can link a unique set of data back to a single consumer.
However, as we integrate further with technology, living more of our lives in the digital space, the amount of data at marketers’ fingertips is also growing at an immense rate. While this seems promising in theory, with so much data available on their target audiences, how exactly can marketers ensure they are using information to its fullest potential?
What brands can ponder on is developing a data management platform (DMP) and working with the right partners.
What exactly is DMP?
A DMP is essentially a data warehouse – a piece of software that houses, organises, and presents data in a way that’s useful for marketers, publishers as well as other businesses. These platforms can also be used for everything from ad targeting to channel integration, personalisation, measurement and audience extension.
However, according to Gartner, only 50 per cent of enterprises currently use a DMP, meaning only 50 per cent of enterprises are maximising the potential of their ad campaigns[i].
Data must be managed and analysed properly to ensure that it can be applied in a targeted way to maximise the efficacy of campaigns. One way to achieve this is by implementing a DMP.
A how-to guide to DMP
DMPs work across three key stages – data aggregation, audience segmentation, as well as data analysis and optimisation.
1. Data Aggregation: Firstly, the platform imports and houses lots of information (the data). It primarily manages digital audience data like cookies, online behavioural data, and look-alike audiences (models built from smaller audiences to reach larger prospective customers). While most offline data can be onboarded onto the platform, it will require external technology to do so – like an identity resolution service.
2. Audience Segmentation: Segments are then built from that data. These segments are the cornerstone of people-based marketing, allowing marketers to group people with common characteristics and target each individual in specific ways.
3. Analysing and Optimising: After building segments, the platform will be able to manage and present all campaign activity and audience data based on those segments. This enables marketers to optimise present campaigns and establish best practices for future campaigns.
In a nutshell, these stages will help in driving more data-driven marketing strategies, which allow for effective targeting and unique messaging.
To take your data one step further, brands might want to consider building their DMP with an identity resolution service partner, which ties unknown user data back to real people. At LiveRamp, we focus on identity resolution across channels and getting your data in different apps. Our services are complementary to a DMP provider – which focuses on being the execution hub for data segments with many applications.
LiveRamp supports DMPs (like Lotame, MediaMath, Sizmek, and KBM Group) ingest more offline data, apply verified, people-based identity to their data feeds, match audiences at a household level, and augment additional integrations for distribution. This enables marketers to deliver more relevant messaging and meaningful connections, to ultimately maximise the efficacy of their campaigns.