Randall-Reilly & BlueConic: How Publishers Can Engage New Audiences Using a CDP
Last week Publishing Executive explored how publishers can implement Customer Data Platforms (CDPs) in a free webinar featuring insights from Randall-Reilly VP of data product development Geoff Deakin and BlueConic VP of marketing Cory Munchbach. The speakers packed the webinar with valuable information such as how CDPs differ from other data management platforms, the potential ROI for CDPs, and how Randall-Reilly uses the technology to activate, engage, and monetize its audience.
At the end of the webinar attendees submitted several questions to the speakers, many of which asked about specific applications for a CDP in their business. Deakin and Munchbach have responded to the questions that they could not answer during the webinar below.
Our discussion of CDPs will continue in a second webinar installment on August 24th, which will delve deep into the practical applications of CDPs. Innovative media executives will share how they are using CDPs to increase revenue and grow audience.
How can CDPs help with identification of users cross-device and cross-browser?
Munchbach: By creating a profile that’s channel agnostic in terms of the data it collects, you have a mechanism that works across devices, channels, and sessions. Thus, behavior that occurs on a mobile app can be reconciled with the same person on a tablet browser, for example, using the profile as the link. Profiles are only merged deterministically; this ensures that you have the utmost confidence that two profiles belong to the same person before merging.
Can a CDP leverage data science and predictive models to help publishers increase engagement and conversions?
Munchbach: While capabilities in this area will certainly vary from CDP to CDP, overall I’d say that most CDPs have at minimum the ability to incorporate data science into their own models to leverage within the platform. Also, there’s an array of support for these kinds of capabilities whether you’re talking about the profile attributes, segments, and/or activation – different CDPs have different functionality in each of these core competencies.
One particularly effective way BlueConic uses machine learning with a lot of our publishers is for our content recommendations engine, which suggests content from a combination of algorithmic determinations based on that individual user’s profile attributes. Compared with other recommendations engines, we’ve seen 50% and up improvements in click through rates on the content BlueConic recommends.
What were Randall-Reilly’s metrics in converting unknown readers to known?
Deakin: To be honest, since conversion of unknown to known users was a bonus for us—my first goal was to improve our efficiency in activating our currently known users through email and digital marketing channels.
While unknown-to-known wasn’t a KPI for us, we do have another metric that I keep an eye on: Profile merges. Since turning on the merge rules, we’ve had more than 3 million profiles merge based on the rules in place in our CDP. Sometimes these come in large sets -- from an import, for example -- but on a daily basis we see between 5,000 and 7,000 profiles merge based on previously known users arriving on our websites as unknown and being reconciled to the known profile.
How did the CDP help Randall-Reilly uncover new audience segments?
Deakin: We use the CDP in a couple of different ways to explore. When we have a hypothesis -- often based on research that indicates a new niche audience, driven by a client request, or jut someone’s hunch -- we can build the segment using either our rules-based segment builder or one of our two visual inspectors (Segment Discovery and Segment Overlap).
The real gain here is in efficiency: What would previously have required multiple individual contributors shuffling and manipulating spreadsheets can now be done pretty quickly and painlessly in our CDP. Depending on the desired goal of the market segment, we would engage differently. Building as a niche newsletter that is offered to the target contacts is perhaps the most obvious way to engage a new audience like this, provided that you have the editorial content and/or bandwidth to create it. We’ve also run targeted lead content marketing programs against these groups to warm them up for future offers and engagement, keeping a list on a monthly-or-so drip.
How could a publisher use a CDP be used to increase paid circulation for a magazine?
Munchbach: We work with a lot of publishers who are still “traditional” in the sense that subscriptions to their print products is still tremendously important for their business. They use BlueConic to personalize and time the calls-to-action and offers made to digital readers to become subscribers to the newspaper or magazine. For multi-brand publishers, this is also valuable for cross-selling into an existing subscriber base.
There are some relatively simple use cases, such as collecting interest data about a reader and then suggesting that they “read more about their <interest> by getting the magazine” which can grow subscriptions by double digits consistently.
What CDP use cases is Randall-Reilly considering or hopeful for in the future?
Deakin: Editorial use cases -- often the lead pitch for a CDP -- are our next frontier. Augmenting or replacing our existing dynamic content and offer tools, optimizing recommended content, and creating conditional, behavior-based lead capture forms to progressively profile our users. Also in discussion is the idea of putting our CDP to use in our content marketing programs for clients. While we’re activating users on their behalf through email and social (among other channels), our optimized landing pages are not currently tracked by the CDP.
Related story: Why All the Hype Around Customer Data Platforms?