“What is the value of my data?”
If you know Acxiom at all, you won’t be surprised to learn that we get this question a lot. I’m not talking about the value of an individual’s personal data, rather the potential dollar value of consumer data generated or aggregated by an organization.
The question “what is the value of my personal data?” is actually an easier one to answer: not much. In fact, the Financial Times built an interactive calculator to shed light on this with valuations tied to an “analysis of industry pricing data… in the U.S.” The real value in sharing my data with marketers is receiving more relevant offers and content, and I’m okay with that as long as it’s a give and take relationship.
So, back to the more complicated question of “what is the value of my organization’s data for consumer marketing?” As with most complicated questions, the answer is: it depends. And it depends on a number of things…
When we first evaluate consumer marketing data for commercialization, we ask a lot of questions up front to help understand the path to value and potential financial opportunity including:
- How was the data originated/sourced?
- Were consumers given appropriate notice of the potential uses of their data and choice in the matter?
- What permissions and restrictions come with the data that create risk or opportunity?
- What value-added effort, subject-matter expertise and resources are required to make the data actionable for its intended uses?
- How will the data be distributed, managed and tracked?
- And most importantly, what are the data-driven applications?
Acxiom and other reputable data companies develop and help activate data based not only on what “can” be done in the market but also on what “should” be done. This goes beyond legal and regulatory guidelines to also consider the ethical uses of data.
If we have visibility into answers for the first few questions above and determine that the data is viable, we typically focus on the application(s). That is, what specific purpose(s) are the data being used for?
While this is oversimplifying a bit, consumer marketing data is typically applied to three primary use cases:
- Recognition – linked sets of consumer contact data updated over time and used to connect disparate data sets to a specific consumer or household
- Targeting – known and modeled data at the consumer, household or geographic level that enable marketers to select and reach the most relevant consumers
- Analytics & Measurement – segment-level data used for planning, measurement and attribution
When we begin to estimate the value of a data set, there are three key measures we evaluate in the context of the applications above:
- Coverage – What percent of the marketable population does this data set cover? Who are we missing and what are the biases?
- Quality – How accurate is the data in reflecting reality?
- Recency – How current is the data relative to how often it changes? While the year you were born never changes, your tastes in music or food for example may evolve significantly over time.
To avoid the tl;dr syndrome, I’ll limit the rest of my answer to the targeting application. Targeting – selecting the right consumers to engage – has the biggest impact on marketing ROI and therefore provides the largest financial opportunity across channels for data providers. Digital targeting is the fastest growth area for consumer marketing data, and is generating both a lot of interest and new entrants.
While there are a number of different data licensing models in this area, the industry as a whole is moving more towards usage-based pricing which ties payment to action. This could be represented as a percentage share of the media spend, or a CPM (cost per thousand) based on number of media impressions. Here is an example of some of the pricing we see today for typical digital targeting data:
The exact answer to the question “what is the value of my data?” is often difficult to determine, and was perhaps too ambitious a topic for my first post here. However, understanding the details of how the data was sourced, permissible uses, value-add required to activate the data, the coverage, quality and recency as well as how the data will be applied are all critical considerations to defining the potential opportunity. In the end, the data are only as valuable as the value they help create for businesses and consumers.