50% of enterprises use a Data Management Platform (DMP) either directly, or through an agency partner, according to Gartner’s 2017 Marketing Technology Study. Despite high adoption, many companies struggle to understand the value post-implementation.
I’ve attended DMP pitches where providers acknowledge this fact by sharing that they often successfully migrate advertisers from a failing DMP solution to theirs.
Changing provider is certainly one option when you aren’t seeing value from your DMP, but I would argue that there are usually underlying factors that should be addressed first.
In this blog post I describe 4 common reasons advertisers aren’t seeing value from their DMP. Addressing these issues avoids the time-heavy and costly process of RFPs and data migration.
1. Incorrect Strategy
This may seem obvious, but having a well-defined strategy is essential to drive success with a DMP.
Too often advertisers start their DMP journey by simply aiming to ingest all the data they have into the platform without considering how they are going to use it. Integrating data without a purpose is a huge task and one that will seem almost never-ending if the data isn’t organised and easily accessible.
Before writing an RFP, create use cases to focus the task of selection and onboarding against your business goals. By focusing on specific use cases for the DMP, you can quickly identify the data needed, integrate it into the platform and see tangible progress against a specific, relevant goal.
On the other side of the coin, there are some advertisers that have set their use cases but are not focusing on the quick wins available. A long-term vision for success, such as a complete, centralised view of the consumer is a great ambition but this use case will take time to achieve and drive return on investment (ROI).
Quick wins can be achieved by identifying and integrating data that is readily available and of high value. Testing in real-time, programmatic channels means you can evaluate success rapidly.
2. Lack of Ownership
DMPs have many moving parts and successful use requires expertise from different teams across the business. Success often requires input from website management, CRM, media planning and trading trading teams (to name but a few). Typically, these teams have enough on their plate already without having to worry about another platform and may not see the value of a DMP for their role. Therefore, DMP implementation is often not prioritised over the other tasks.
To avoid this, appoint someone with the skills required to understand and explain the business benefits of a DMP and then to bring these teams together to work towards a common goal.
3. A Lack Of Quality Data
Good output from a data management platform relies on good data going into it. In my opinion, good data is a combination of: scale, ability to integrate with buying platforms, quality, relevance to, good organisation and accessibility.
Scale is important because despite even with high match rates across buying platforms, there will be some data loss as both the DMP and buying platform will need to recognise each user. Match rates will vary depending on the technology so avoid a situation where you have invested time and energy into onboarding data that can only use a fraction of your advertising budget when being bought against.
Quality data accurately represents the traits of your users. First identify the type of user data that best fits your use case, then analyse the data you have. If you have very little data or can’t trust the data, then you need to rethink your use cases and improve the quality of your data. On a side note, be aware that the scale and quality of your data will likely be impacted by GDPR!
Organised data is vital for successful integration with a DMP. Regardless of the amount of data you have, a clean taxonomy will dramatically improve the ability to understand the data, create audience segments.
Cleanse your data by using naming conventions and standardising collection methodology across data sources. Ideally, this is done before signing a DMP contract but if not, focus on the most relevant data sources for your use cases.
4. Incorrect Measurement
Measuring the success of a DMP is typically defined by impact on marketing performance or cost saving. The challenges are: difficulty in accurately measuring the impact of marketing spend before implementation and difficultly attributing any change in performance to the DMP.
One way that value can be attributed back to cost is to isolate tests within programmatic channels to understand the incremental effect on performance. Another is to prioritise use cases that facilitate frequency capping where previously unavailable. By multiplying average CPM by reduction in impressions and dividing by 1,000, you get an estimate of the investment saved by the DMP.
While representing value as a financial figure is important there are also some softer gains outside of marketing performance and efficiency. DMPs drive insight either directly from the platform or through the data it provides to analysts.
This can bring tremendous value to advertisers because it unlocks insights that were previously unknown. The data and insight generateed can be applied to existing measurement techniques and goes a long way to proving the value of all marketing investment.
While these are common problems, every advertiser has their own unique challenges when implementing new technology. The most useful advice I can give for DMPs specifically, is to focus effort on specific, measurable use cases and to have someone responsible for driving this forward.
For further advice on how to drive value from your DMP, please feel free to drop me a message.