In digital advertising first-party data rules supreme.
When faced with a choice between utilising first-party data – relating to a user’s previous interactions with a brand or digital property – and third-party data – vague trends about wide consumer groups that anyone can bid on – it’s not hard to see why marketers should place a higher value on the former every time.
Many brands and advertisers are sitting on more data than they are aware of and are struggling to effectively extract the value associated with multiple data points, including paid media, to create their own robust first-party data set.
The inevitable result of this increased emphasis on first-party data is a rise in adoption of data management platforms (DMPs), which brands, agencies, and publishers are using to store valuable data. Now an established part of the digital marketing landscape, DMPs are already used by more than two-thirds of media professionals, with this figure set to rise above 90% in the next two years, according to a report by ExchangeWire and Weborama.
Despite their popularity, simply having a DMP is not a strategy, and without one in place both advertisers and publishers will fail to realise value from their investment.
So, how are brands currently using DMPs and how can marketers ensure they are implementing an efficient strategy to exploit the full potential of the technology to gain actionable insights from data?
Power of data
Marketers face a number of challenges in effectively implementing DMP, and the most frequently cited one is integrating disparate data sets to gain a single view of the customer. This is particularly problematic when teams work in silos, each with their own data stores – think e-commerce, content, paid media, for example. In-house expertise to bring these siloes together is often lacking, and brands struggle to recruit talent with the necessary skills.
While this situation may improve as data-driven marketing becomes the norm, many brands currently rely on external expertise to extract insights from the data held within their DMPs. Responsibility lies with the agencies to educate marketers and brands on the power of the data they have at their fingertips, just waiting to be understood.
Depending on their functionality, DMPs can be used to make the most of first-party data via techniques such as audience segmentation, advanced analytics, and lookalike modelling, which knits together disparate data points to provide insights that can be used to inform effective marketing strategies. But many marketers are failing to fully utilise their DMP, simply using it as an advanced data warehouse.
When the respondents of the ExchangeWire/Weborama survey were asked about the limitations of their platform, 33% of UK media professionals reported it doesn’t provide enough insight, while 37% of European respondents complained about a lack of marketing activation capabilities.
Clearly there are technical limitations to what DMPs can do in analysing patterns in customer data to uncover actionable insights and trends. Every brand has different expectations of its DMP – there is no one-size-fits-all approach – so smart technologies are required to provide the unique insights needed by individual companies to drive informed marketing strategies.
Having a DMP is not a strategy in itself and will not necessarily get you closer to understanding the power of the data stored therein.
To fully maximise the potential of DMPs and the first-party data they collect, marketers must look to emerging new technologies such as first-party advanced profiling to extract actionable insights.
These smart technologies provide a solution to disparate data sets, bringing together all sources into a single aggregated process and create a continuous feedback loop. Data such as cookie history, user IDs, the content users previously engaged with, time of day, location, as well as navigational and click/completed view data can form missing pieces of the user profiling puzzle.
With this data tied together and pushed back to the DMP, marketers instantly and consistently receive much deeper insights to influence marketing decisions before targeting those users with insights gleaned from the data, or using them as a model for prospecting similar-looking users.
The ability to fully interpret data by combining statistics and machine learning algorithms to observe user behaviour, and by using semantics to enrich specific data sets, and to integrate the resulting insights with unique business experiences and needs, goes far beyond the standard uninspiring functionalities of a DMP.
First-party advanced profiling empowers brands to build detailed, actionable profiles of their existing customers, or those users who have previously interacted with their properties, understanding what interests them at a given moment and - when paired with machine modelling - can uncover their future propensity to interact with a brand or product.
There are many uses for this data, from sophisticated targeting to creating personalised content, that appeals to individual customers. Brands no longer focus on retargeting broad audience segments but should want to understand what content individuals engaged with as an inferred interest. Using these smart technologies, existing customer data sets can be stitched together and enriched for real-time campaign optimisation and enhanced creative messaging.
The skyrocketing adoption of DMPs proves their efficiency as data warehouses, but their full potential in generating actionable audience insight is still yet to be realised.
To make best use of the valuable first-party data stored within DMPs, marketers must embrace emerging technologies, such as first-party advanced profiling, to truly understand a consumer’s behaviour and deliver what their audiences want.
Activating the potential of data sitting through DMPs using cohesive technologies that tie the data points with a clear end goal in mind will empower marketers to truly deliver more targeted messaging and create greater value for their customers.