In 2012, we saw the incredible power of data to drive elections, and to help enable the next generation of hyper-efficient marketing. This year promises to fully demonstrate how big data, small data or just the right amount of data is driving online advertising success for brands and marketers. Right now is a great time for a gut check to reassess your strategy and audit how you’re managing the process.
To help you along, here is an overview of how to look at your data management platform (DMP) and what you could (and should) be doing to make the most of your investment. We need to consider what the top agencies and brands are doing and follow their example. The leading players are leveraging data management platforms to address three specific purposes:
1) To enable marketers to integrate audience, contextual and geographic data across a company’s multiple touchpoints;
2) To enable a company to segment their audience and take immediate action on these segments;
3) To enable a company to discover new insights about their audience.
Those who want to lead and not follow in the new techno-marketing era must ensure they are able to deliver on these abilities and they must ensure that their DMP is helping them get there.
To achieve the first purpose of integration requires a robust set of import capabilities from real-time pixels (also known as Tag Management) as well as batch files. Once the data is on-boarded, the system allows a marketer to transform the information, by bucketing transaction values from a shopping cart into a set of marketer-defined buckets. Transforming the incoming data enables downstream processes of segmentation and targeting to be faster and easier by standardizing the raw event data into more usable information.
Segmentation and Action
To achieve the second purpose, a DMP requires an easy-to-use interface for manually defining specific audience segments, such as combining third-party demographic information with first-party registration, activity and customer value information. These segments should be expandable through lookalike modeling to find similar audiences that are likely to behave in a similar manner to the “seed” audience segment. Many DMPs stop here.
However, it is important to have real-time feedback to two additional criteria before generating the audience. First is the audience size. Marketers do not have the resources to craft specific campaigns to only a handful of consumers. Accordingly, a DMP should provide the feedback to the total addressable market that matches the segmentation rules both in terms of unique user counts and in terms of frequency of exposures at given price points. Even if a segment of users is large enough to warrant a campaign, a DMP should provide insight into the cost of reaching this audience with an increasing frequency of exposure. Stand-alone DMPs that do not have tight integrations into action-taking systems, such as Web site content management systems or ad-serving systems, are often unable to provide this feedback.
Another important aspect of defining the audience segment, especially for digital channels, is the latency from creating the segment to being able to target this segment. Since the anonymous user identifiers used to target segments frequently change, to increase the latency between defining a segment and synching this information with an action-taking system would lead to a higher overstatement by the original forecast of available unique users. The lack of accurately understanding the number of unique users, the cost of reaching them in the desired context and the frequency are what we call premature “audience activation.”
The third purpose of a DMP is to uncover new insights about a marketer’s audience segments. The DMP should provide easy access to understand what other attributes index most and least highly with the selected audience group. The platform should also recommend the best Web sites and content to reach that audience, as well as information about the best geographies to target. Furthermore, it should ensure that a marketer understands the cost implications of overlaying geographic, third-party attributes and contextual data with forecasting the cost of various advertisement placements.
The online advertising ecosystem has never been more competitive. With consumers’ activity and attention increasingly fragmented across a variety of channels, such as video, mobile and social, it is of the utmost importance that marketers today have the technologies in place to ensure they fully understand this activity as they plan their segmentation and targeting strategies. Armed with a robust DMP, marketers are better able to locate, target and understand their desired audiences, ultimately increasing the effectiveness of their campaigns and improving ROI. By understanding and utilizing the capabilities provided by a complete DMP, marketers can ensure they are using the best planning and segmentation tools to achieve their goals.