Digital brands such as Netflix, Uber, Tencent and Amazon are using their mastery of data to redefine their markets with highly customised, on-demand services and products.
Incumbent companies in nearly every industry must learn to use their data as effectively as possible in order to optimise marketing costs and personalise their customer experience to reinvent their business models in the face of digital competition. This is why data management platforms (DMPs) have emerged as a critical element of the marketing technology and data infrastructure. These platforms enable organisations to collect and manage data from digital interactions across multiple devices and channels, and use it to craft better customer experiences. DMPs enable brands to unify behavioural and transactional data sets and get a holistic view of the customer, in a world where they have a deluge of data from their own systems and from second- and third-parties.
As Forrester Research stated, “Data management is the differentiator for customer-obsessed brands.” Forrester research indicates that customers who have a high-quality experience with a brand are 3.6 times more likely to buy additional products and services from them and are 2.7 times more likely to keep doing business with that brand.
A holistic view of the customer
The DMP’s purpose is to capture data from multiple sources – such as customer relationship management, enterprise business intelligence, ad-serving, email, social, video and search platforms into a single place to make it more accessible to business stakeholders. This, in turn, enables enterprises to drive richer and more personalised brand experiences across all channels and touchpoints.
DMPs are essential in a world where most consumers own multiple devices and interact with brands across multiple channels. They give brands the ability to recognise the same person across channels and devices. This in turn offers marketers the capability to understand the customer journey across multiple devices, channels and contexts.
This is important when trying to obtain a better understanding of existing customers as well as tracking existing customers, prospects and leads through linking data across various sources. It is also beneficial when obtaining more behavioural insights about customers, including interaction with its website, content, ads, apps and store.
Data can be utilised for journey insights, algorithmic segmentation, and addressable attribution, based on a holistic view of the customer across every touchpoint. It enables organisations to deliver the right experience to the right customer on the right channel at the right time. Often in an automated process which will become even slicker as machine learning and artificial intelligence mature.
- Targeting search, social and display ads and email at a high-value customer segment that recently browsed a product or product category.
- Building a lookalike audience based on second-party data, using a frequent buyer CRM profile segment as a seed, with the goal of reaching a wider target audience on display.
- Preventing wasted spend by capping the number of impressions of a display ad that individuals see across display ad networks.
- Avoiding wasted spend and frustrated customers by only showing paid search ads to audience segments who are not customers.
- Sequencing ads across video, display and web channels, to reinforce the marketing message without boring the audience with repetitive content.
- Personalising the web experience, by building segments based on previous purchase and browser behaviours, then showing those segments banners specific to their interests.
For organisations looking to control advertising costs and improve ROI, while getting insight into cross-channel performance metrics, the DMP is a big part of the solution. Those that begin implementing a DMP today will be able to build compelling, data-driven customer experiences that give them a real edge in the market.