Customer Data Platforms and Programmatic Media

How to optimise programmatic media spend using the power of a Customer Data Platform

Customer Data Platforms (CDPs) are most commonly used to drive personalised communications through direct marketing channels including email, direct mail and SMS. They ingest, transform and deliver a combination of first, second and third-party data to marketing automation platforms, enabling more relevant customer experiences.

CDPs are also powerful tools for optimising programmatic media spend (e.g. display, video, social and mobile). Programmatic media buying platforms, commonly known as Demand Side Platforms or DSPs, primarily deal in audiences derived from anonymous behavioural data. However, they also have the ability to upload audiences derived from personalised (first party) data. These audiences can then be used as targets for specific campaigns to reinforce messaging already received through direct channels (or to suppress existing customers from acquisition campaigns).  

In most cases, DSPs will not let you to upload customer Personally Identifiable Information (PII) such as email addresses directly into audiences (and in any case this would be inadvisable due to privacy concerns). Instead they require that the PII data is cryptographically (one way) hashed to ensure that a user is only added to an audience if the supplier is already in possession of the PII as well.

CDPs have the capability to act as central marketing data platforms to power both direct marketing and programmatic media campaigns. As CDPs can store both PII data and anonymous audience data in a single location, they have the ability to generate both hashed PII and identifiable cookie-based audiences and share them with DSPs. This centralisation of audience data can ensure consistency of targeting across direct and programmatic (indirect) channels.

Where do Data Management Platforms (DMPs) fit in?

Data Management Platforms (DMPs) store and transform online visitor data into behavioural segments that can then be shared with other marketing platforms. They differ from CDPs in two key respects:

  • They generally cannot be used to store PII data, as they deal in anonymised audiences

  • They often cannot achieve real-time performance with uploaded data (i.e. there is usually a significant lag between the upload of data and when it can be made use of within the DMP and therefore shared).

This means that they are generally used to generate segments for sharing with DSPs and web personalisation tools, rather than as centralised marketing data platforms.

Although DMPs are good at segmenting online audiences and sharing them with DSPs for targeting of media to specific visitors, they can struggle with allowing first party data to be used in a similar way. For example, they can enable the targeting of customers vs non-customers (e.g. - if a cookie is associated to logged-in customers) but cannot enable targeting based upon customer attributes that aren’t derived from online behaviour (e.g. – age, gender etc).

Most DMPs also have a time lag between when data is uploaded and when it is available to be shared with DSPs. In some cases, this delay can be as much as 24 - 48 hours, driving a lack of immediacy which can significantly impact the conversion rate of the programmatic campaign. As CDPs typically have more flexible data models, they can operate closer to real time, delivering audiences to DSPs much more quickly - thereby increasing the probability of conversion.

What about Cloud Marketing Automation Platforms?

Most of the major marketing cloud platforms include some form of programmatic media optimisation capability (known as ‘lead management’ or something similar) as part of their offering – albeit usually at an extra cost. This capability enables the creation of audiences from customer data and the sharing of these audiences with DSPs for programmatic media campaigns. The best platforms optimise spend to improve conversions and can automatically associate conversions of leads with customers. 

However, using a cloud marketing automation platform to feed your DSP has a number of disadvantages:

  • It requires first party (PII) data to be stored inside the marketing cloud environment, which may result in legal jurisdiction or regulatory issues.  

  • Licensing and storage costs may increase as your business becomes increasingly ‘locked-in’ to a particular vendor’s marketing cloud environment. 

  • You may be required to adopt the online ID/tagging/analytics system of the marketing cloud vendor - and this may require relatively significant changes to the setup of your online presence.

  • It can cause significant integration issues if you are using technology from multiple different vendors to power your online customer experience programme.

  • Extraction and management of large indirect (programmatic) audiences can cause performance degradation in the marketing platform, even in those with self-hosted components. 

  • Marketing cloud platforms can struggle to leverage conversion data from offline channels (e.g. – phone and face-to-face) due to issues integrating that data from other systems. This can result in potential customers being excluded from online campaigns during their offline service journey.

How Customer Data Platforms can help

CDPs enable the creation and maintenance of a single marketing customer view which can include online and offline lead information. They also provide the flexibility to deliver audiences to marketing cloud platforms and to DSPs, mitigating the limitations of both. 

Deploying a CDP into your programmatic media buying ecosystem achieves the following:

  • Legal and regulatory compliance through the retention of your first party data within an on-premise or otherwise customer-owned and controlled environment.

  • If your existing marketing cloud platform does not support programmatic (indirect) channels, using a CDP can prevent the need for data integrations to platforms that do provide support. 

  • Reduction in the performance impact on direct channel message decisioning from the extra load required to support programmatic channels.

  • Removal of the need to retag or switch analytics providers to support programmatic channels.

  • Centralisation of campaign targeting to ensure consistency of campaign communication in both direct and programmatic channels.  

  • Increase in programmatic media performance through the ability to supply PII-derived data directly to DSPs.

  • Integration of offline data about conversions and other activities into programmatic media campaigns.