As brands develop their data management platforms (DMPs), combining consumer media behaviour, website engagement activities and CRM presents a more powerful picture and the potential to connect the dots for true precision targeting.
Tying rich CRM data with second- and third-party data is where effective marketing planning synergies can be found, closing a loop on customer activities to build custom segments that create efficient communication design and deployment. This is, ultimately, what the point of a DMP is: collecting, storing and managing the flow of potential and existing customer information to build deeper, more precise audience profiles for marketing and media targeting.
A recent joint exploratory research between ZenithOptimedia and Nielsen of over 20 China-based marketing and media senior leaders highlights a clear disparity between knowledge and execution:
- Half (52 percent) of clients are very familiar with the concept of DMPs
- A clear majority (86 percent) say DMP is important to the business
- Nine-in-10 (86 percent) think DMPs and CRM help enhance on-target rates
- Yet, despite most (86 percent) also saying they use programmatic, only one-quarter (24 percent) use it for proper segmentation for the business
The main concerns with building active use of CRM into DMPs are diverse, including critical points directed at data quality, budget funding, consumer privacy and leveraging the right expertise. In a fast-moving and constantly evolving market like China, these are all real and legitimate challenges.
Data quality is an ongoing question for the industry to address and answer: how data can be properly assessed, cleansed and streamlined begins with managing transparency. The challenge in China—with newer structures and growing checks and balances—are acute and, though improving, continue to dog operations. Uncertainty about consumer privacy regulations invariably plays a part in this, especially since an uncertain grey area exists on acceptable and unacceptable practices, placing a drag on implementation procedures.
Though the topic of “digital transformation” is a top agenda item for many organisations, budget funding continues to be source of questioning and, when the time comes to allocate investment capital to DMPs, difficulties typically arise. Companies with a proper vision and framework set up from the top down are navigating the transition more easily, though most admit developing organisational consensus (and priority) is proving tricky.
The crucial area that can be sensibly managed is in the incorporation of expertise to develop and manage the integration of analytics with DMP, both in-house or with consultancy partners with relevant experience. This is important given the nuances that exist within domains. Within the CRM world, how customers are viewed by the business, how data is sourced, what’s available and what additions are required is crucial to understanding how proper segments can be created to adapt to marketing and media goals. On the other side in the media world, key factors include how a DMP is created, what other data from sources (DSPs, publishers, third-party partners, for instance) is feeding into the DMP, which media opportunities are most appropriate or relevant for consumer communication. With this unique perspective the analytics criteria can be easier addressed to meet overarching business and marketing objectives.
Segmentation is a powerful practice to build into the consumer profile, if the appropriate perspectives are taken and segmentation is properly applied. As well documented by “How Brands Grow” and the Ehrenberg-Bass Institute, for instance, the ability to tie consumer product consumption history and partition audiences on such factors as past usage, usage frequency and place of consumption can all help to build stronger cases in determining consumer type and the best-suited communication to influence future habits. In some cases this approach may fly against common marketing convention, which says that brands best target consumers by lifestyles or demographics. And having a data science expert well-versed in marketing, media and CRM domains can guide stronger strategic thinking. Connecting to media profiling data—by triangulating and connecting to DMPs on consumption behaviours—ultimately provides the case for appropriate targeting measures to take place.
What are some of the important points to watch to ensure building a strong DMP program?
- Objectives: Develop a reasoning for implementation in the first place. Is the purpose to build or expand in-house data management capabilities? Is the primary function of the DMP for audience development? Or is it, ultimately, to develop avenues for maximising media investment ROI? Not formalising objectives will lead to long-term uncertainty of all the hard work required for implementation.
- Buy-in: From top to bottom, stakeholders must see value to justify heavy implementation requirements for a DMP. What is the overall business benefit of having a DMP? What internal and external marketing synergies can be formed? How can a DMP build organisational cohesion and, potentially, break down work silos?
- Investment: Subsequently, with proper buy-in, how to manage capital expenditures for a long-term DMP program. Some short-term, step-by-step gains can be highlighted, though the real impact will be observed in the long-term, once more data is collected, connected and managed. This can require investments in excess of RMB 1 million to RMB 2 million.
- Operations: Creating strong DMP infrastructure is crucial in order to ensure effective building, flow and output of data. This requires managed expertise in areas of data management, IT, marketing, media, CRM and analytics, as well as strong leadership to enable cross-function production to take place.
- Usability: Sharing the vision and practical application of a DMP, importantly, needs a communication backbone for the end-users of the DMP. Having both a proper visualisation and management software tool, as well as regular training and coaching to staff on use, is crucial.
2016 will see a growth in programmatic spending to RMB 60 billion, rising to RMB 81 billion in 2017. As the growth outpaces both the UK and US markets, the practice of analytics in China must continue to mature if businesses are to successfully leverage the value of data.
Chris Maier is head of research and analytics at ZenithOptimedia China