Today’s marketing industry relies more on data than ever before, which has led to a burgeoning data market. While the lines of who actually owns the data are blurred, it’s crystal clear that everybody wants the data in order to monetize it.
This mentality has led to the commoditization of data; there is no longer any value in simply owning or accessing the data itself. Value comes from what can be done in terms of analysis and application. So while everyone wants the data, the amount of value each party can deliver differs dramatically. It doesn’t really matter who has the data unless they can apply intelligence to the data, and that ability varies greatly across the ecosystem.
Let’s start with the most common third party in all of advertising: the agency. These partners will insist that they should have unlimited access to advertisers’ data so they can strategize future campaigns and optimize the results. But is there anything an agency can do that a marketer can’t do in-house or with another technology partner? Perhaps, but savvy advertisers are starting to take more control of their digital media, and specifically their data. Many already have CRM systems or other repositories for data that they can access for insights, segmentation and targeting. Bringing this in-house and then using a DSP to buy media with the insights is a trend we are seeing, and it’s the right move for advertisers willing to make the investment in knowledge and human capital.
Leading agencies do add value by looking across multiple clients. An agency may see that two clients are trying to reach very similar audience profiles and use insights to help both customers. Agencies can also use the data and insights to help them plan and price publisher inventory to negotiate better deals for their clients. The agency proves itself very valuable in these situations, which is one reason so many are focusing on data now.
Data also makes the agency “stickier” with the advertiser. While agencies may provide good insights, problems arise when advertisers decide to move their accounts elsewhere. Advertisers clearly own their customer data, but who owns the campaign data? What about the insights derived from the data?
Then there are technology vendors, like data management platforms (DMPs), which are used by advertisers and publishers. From the advertiser perspective, these partners provide a central system to store, analyze, activate and transport the data. When tied to ad-serving logs, this becomes increasingly more valuable for advertisers. The DMP creates a continual, fluid process so each campaign informs the next. Advertisers have a better understanding of which audiences reacted to the ads they saw. The software then optimizes for future campaigns, helping advertisers meet their campaign objectives.
From the publisher perspective, the DMP is an expensive investment, but a potentially worthwhile one. Publisher-side DMPs maintain information about on-page audiences, and everyone in online media knows that audience is a publisher’s biggest asset.
Publishers want to create data segments, then put various rules behind them, allowing their advertising partners (or those advertisers’ agencies) to leverage those segments for audience targeting. DMPs also allow publishers to port their data off their network, allowing advertisers to find and target the same consumers on other sites.
On top of all of this, advertisers and publishers need to understand the range of value of their data. Those in possession of high-value data (affluent audiences visiting the site, conversion data from major brands, etc.) will want to carefully consider the benefits of sharing that data, even if it comes with the promise of increasing the value or providing other benefits. Some data owners may find that they’re investing money and getting no tangible benefit. Indeed, some brands are bringing data in-house, with tight control over who has access.
Those with low-value data are more likely to benefit from almost any offering, as additional data sources can increase the value of the data in their hands.
There are plenty who fall in between high- and low-value data as well. The trick for everyone involved is assessing the value in a realistic way. Nobody thinks their kid is ugly. But your data may be less valuable than you hoped.