Continuing with our collection of Lotame partner posts on the value and use cases for DMPs, we’ll be talking about how you can use a DMP to achieve effective content customization and personalization.
Consumer Insights obtained through the DMP can be applied to adjust your site content in several ways.
From the previous example, you know that 70% of people watching videos at least 3 times in the last 5 days are men, 40% are age 25-34, and 35% are interested in sports. Perhaps the video producing team should make a few videos about football (regulation or American). Knowing the makeup of your audience allows content to be built specifically for them. When content is relevant for individuals, it keeps them engaged and more likely to be loyal consumers.
Customization helps to modify the types of content your editorial team produces, which helps to narrow in on a few broad categories. But how can we ensure that the user is getting the most relevant content to their specific desires?
Let’s say that 1 out of 10 articles were relevant to the users coming to the site. With Customization, we can say 4 out of 10 articles are now relevant. How do we increase that percentage?
Instead of making articles more relevant (i.e. customizing the content) why don’t we reduce the irrelevant ones so they aren’t displayed to users who are not interested and only show them to users who ARE interested?
We know from the Consumer Insights that many consumers are young men interested in sports. What other major audience groups are there that make up consumers’ collective attributes (and those who aren’t regular consumers)? Well, women still make up 30%, which is a large chunk. And maybe some other important interests beyond sports are ‘finance’, ‘fashion’, and ‘politics’. Therefore, the editorial team can build out content around these topics as well. But how do we ensure the right articles are delivered to the right users?
That’s where Content Personalization comes into play. Through a CMS engine, DMP audiences can be fed to ensure only the most relevant articles are getting displayed to the current user.
If a user has a finance audience in DMP, when the user visits the site, a finance article is presented on the home page (through the CMS). If the user is a member of both the finance and sports audiences, does the user have different frequency or recency for these? If they are part of finance 1 time in 30 days and sports 3 times in 7 days, then sports is more relevant. (Or perhaps you as the publisher are weighting one vertical over the other?)
Now instead of 4 out of 10 articles being relevant (from just using customization), it’s 4 out of 8 articles that are relevant. It’s not perfect, but we’ve gone from 10% relevancy (1 out of 10 articles) to 50% (4 out of 8), an increase of 500%!
So now we know how to ensure the right content is shown despite the users’ interest or demographics. But we can’t just keep showing the same article or type of article to the same user.
Content Recommendation can help solve for that. As a user browses the page, to one side or at the bottom of the article a selection of relevant articles should be offered to the reader as additional content to consume. If the user is reading an article about sports, but also has finance and politics in their DMP profile, perhaps the list of articles being recommended is 1 article each of sports, finance, and politics. Integrating the DMP with a content recommendation engine (proprietary or 3rd party like Outbrain) will allow these relevant articles to show based on the DMP audiences.
We weren’t perfect in making every single article provided to the user be relevant through Content Customization and Personalization, but by offering the consumer a choice as to what content to read, we can help minimize that inefficiency.
About the Author
Since joining Lotame in 2012, Hunter Terry has held a variety of technical and account management positions. Currently he is a Solutions Architect for the APAC region, where he focuses on cultivating healthy business relationships and fostering communication with clients and partners. Prior to his current role, Hunter served as a Technical Account Director, where he used his technical chops to onboard and train new DMP and data clients. From account management to solutions selling, Hunter has led and been a part of countless technical SaaS implementations in both APAC and the US. He is based out of Singapore, and holds a BA from the University of Virginia.
Read more from our partner series with Lotame:
- Are DMPs Worth It? Assessing Value using Sales-Based ROI
- The Value of a DMP and what a Consumer-Based ROI Approach Can Tell Us
- How to Leverage a DMP to Enhance Content Customization and Personalization
- The DMP Use Case You Probably Didn’t Think About
- The Definition and Future of Audience Data and Audience Targeting
- The Most Creative and Complementary Uses of Publisher’s Data
- Best Practices for Supplementing 1st Party Data with 3rd Party Data