The main focus of LiveRamp’s RampUp 2017 conference was that most brands are in the process of transitioning to people based marketing, and the discussions primarily focused on how data plays a role in this transition. LiveRamp’s chief product officer Anneka Gupta encouraged everyone to begin creating curated, personalized content that surprises and delights their customers every time by being individually relevant and timely, which is a major shift from today’s blanket segmentation approach. She went on to say the only way for brands to produce this type of content is to utilize the data they have, and the only way to properly use said data is to know how to organize it.
Is there such a thing as too much data?
The over-arching conversation around the importance of data in a customer-centric world eventually led to the subject of data quality, and whether there is such a thing as having too much data. There seems to be two schools of thought on this; one that believes the more data the better and one that believes leaner, cleaner data is more efficient and useful. Steve Gerber from Zeta Group noted that
“It’s not about how much data you have and what coverage you have, it’s what you can do with that data.”
The thought-process behind Gerber, and many others’, reasoning is that with less, more accurate data brands are better able to organize and utilize the data than when they have a lot of unorganized and/or inaccurate data. This issue is actually the perfect example of how brands are struggling to use the data they currently have to its full potential, but as people begin to figure out how to better organize data then the issue of having too much data will slowly become nonexistent.
So, how are brands looking to better organize data currently?
As is true with any large initiative at major corporations and minor organizations, alike, teams are working towards programmatic approaches toward data organization and utilization. The two most prominent of these approaches in the field today seem to be AI (Artificial Intelligence) and identity resolution (the ability to match cookies and devices to users and households). The consensus on AI as a tool to mine data seemed to be staggeringly positive as long as it is being used properly and on a case by case basis. People seemed to all agree that AI is efficient at organizing data and ignoring the useless noise, but that if it is being used in a blanket way across all programs then it isn’t as efficient. The AI conversation then led into the debate on probabilistic vs. deterministic approaches when using AI, and the consensus ended up being that accuracy is what’s important and not the method that you use to get there.
In the same vein, identity resolution is seen as a great capability as long as accuracy is prioritized, as well. It was universally agreed on that identity resolution is great at optimizing marketing dollars and ensuring that the right users are targeted the appropriate amount. That being said, the biggest risks of this method were identified as difficulty with compliance and misuse of data findings. The simple truth is that what data brands are able to legally collect and use is always going to be a hurdle that must be conquered, but the second risk is one that will fade as marketers become better versed on how to read and use data. Then again, the two are not mutually exclusive in that the more data brands are allowed to collect on individuals the easier it will be to become more and more targeted to an audience of one.
What is the key takeaway from the conference?
While the theme of the conference was people based marketing, and most of the conversations really focused on data, it felt like many of the attendees were not “there” yet. Conversations still leaned toward segmentation, geo-targeting, and 3rd party data; rather than focusing on how to deliver a truly personalized experience to an audience of one. Meanwhile, SundaySky’s customers are creating and delivering the curated, personalized content that Anneka Gupta spoke about to their customers every day! If bringing your personalization strategy to the next level is something you’re interested in then I suggest you check out our Beginner’s Guide to Next-Gen Personalization. Hopefully some day soon, data organization will be as streamlined as sending emails, but until then you can follow us to keep up-to-date with the latest trends in personalized video, and data-driven personalization as a whole.