Declared Data vs. Inferred Data

Not all data is created equal.

As data privacy continues to evolve, from GDPR to CCPA, how we approach data collection as marketers is more crucial than ever. Additionally, with these initiatives and changes in consumer opinion, the relevance – and in turn value – of various forms of data will inevitably change.

Two major groups of data that concern online marketers are Declared Data and Inferred Data. What are they? Which is better? Do I need both? Let’s find out.

Declared Data is data that has been willingly shared by the user. This could be a form-fill, opting-in for cookies, opening social media accounts, etc… this tier of data usually carries the highest value to marketers, as this data is 100% based on user activity. This form of data is typically error-free, except of course when a user lies in a form fill or social media profile, but users are usually honest about such data (versus surveys) since what they enter determines their access to the products and services they desire.

What good would it do to lie about your location on a dating app only to be served matches nowhere near you?

Inferred Data, as the name implies, is data developed around the user without their express input, systematically generated based on search histories, content consumption, purchases, and social media activity. This data, while useful, doesn’t carry the same value as Declared Data (not better, not worse, just different) as it is based on a series of assumptions, albeit well-informed ones. To put it in other words, Inferred Data is when a system assigns a value to a user based on their observable activity.

If you spend a lot of time on a blog about cycling, you’ll find yourself getting served ads for cycling products – this is a result of inferred data.

So which type of data do I choose? Both! One enhances the other. You can validate your Inferred Data with whatever Declared Data your users are willing to share and vice-versa. When you apply both datasets, you can fine-tune your personalization initiatives through cross-referencing and creating the most accurate user profile.

Say you have a user who declares via an online survey that they’re vegan. Okay, but how can you validate that? Inferred data might validate that declaration (one way or the other) by way of social media follows, dining establishment check-ins, coupon downloads, or a cookie trail of blogs.

Use! Your! Data! Most companies aren’t even scratching the surface: A recent report from Forrester stated that up to 73% of company data goes unused. Given the acquisition costs associated with that data, does it make sense to throw away almost 3/4 of it? Review your data, prioritize it, make an action plan, and put it to work!

At Enilon, we understand the changing roles and value of your data and always promote a balanced approach towards leveraging your data to best serve your marketing needs. The current climate tends to favor declared data, but there will still be a place for inferred data, whether to help as a litmus test against declared data or to support your marketing needs in the absence of declared data, all data is valuable – if you know how to use it effectively.

If you think your data isn’t reaching its maximum potential, let’s have a conversation about how best to put your data to work for you – we’re always listening.

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