puppy with cat head in its mouth
In our rush to embrace data, we've possibly become over-reliant, forgetting that we did just fine for years before the internet PHOTO: Markos Mant

As digital marketers and advertisers, we rely on data to map our route to success. 

But while we need data, it’s not as easy — or as reliable — as we’d always like it to be. It may give us a partial picture of our customer, but it can also simultaneously scare customers or inadvertently ruin their online experience. 

My Love-Hate Data Relationship

So, while I understand and appreciate the need for data, here are a handful of reasons why I don’t love it right now:

It's Messy

We want data to be clean, accurate and easy to manage, but it’s not. 

As much as we try to narrow data-based profiles to a single person, or type of person, it’s never as simple as we make it out to be. Even as unique individuals, we typically represent more than one persona in the internet world.

Consider this example: while testing a DMP deployment, I observed who came through as me on my personal computer. According to the data, I was an African-American male, aged 45 to 54. Which was interesting, considering I’m a Caucasian female, aged 35 to 44. 

While it was obviously inaccurate, I could see where the discrepancies might have occurred. After all, I’m a human who exhibits many different behaviors on any given day. So, which version of “me” had the data identified? The women shopping for household items? The mother shopping for a kid’s birthday present? The wife shopping for her husband?

The reality is that, from the data’s perspective, we are really an amalgamation of the people for whom we shop and with whom we share interests. A brand tempting me with offers of women’s hair care products would likely have missed me with the given classification. That said, a sports promoter trying to target me with tickets for a game might have won a solid conversion.

It’s scary

Consumers worry that brands know too much. And while nearly all the data we work with is non-PII, we have to take the responsibility seriously. They don’t always understand how we’re using their data, or what we have access to, so the idea of sharing their data with advertisers and corporations causes concerns. While we assure them no personal data is collected, users still may not necessarily want to be retargeted.

To illustrate, let’s go back to the shopping scenario: When I’m shopping for others, I don’t want to be retargeted with offers featuring items I looked at on their behalf. It’s pretty obvious that I’ve been shopping for him when my husband sees ads for golf clubs all over the websites I visit. There goes the surprise!

It’s incomplete

Cookies frequently fail, and we may be missing a lot of data without even realizing it. There are a million reasons why cookies may not be a reliable tool for us: they may be blocked, a cache may have been cleared or a million other things may have happened. You might be missing someone because they’ve just gotten a new computer, and they aren’t “classified” yet.

Also, without certain tools in place, we can’t always identify the same user across devices, so we could be incorrectly targeting someone we already know — or someone we don’t.

How to Avoid These Data Pitfalls

It’s possible we rely on data too much sometimes, and in some cases, it may be worthwhile to consider reeling it in. After all, we got along just fine without all this data for decades, and even for a few years after the internet emerged. Publishers typically know who their readers are, often without cookies or third-party data.

With that in mind, why not tap into “cookie-less” users: they’re less bombarded with ads and potentially more receptive. Furthermore, by reaching out to a broader audience without the encumbrances of data, marketers may be able to tap into a pool of new users. Data can tell us a lot about the users we have or want, but it can't necessarily tell us who our next great customers might be.

Finally, marketers should consider allocating a portion of their budget to “old school” marketing. Instead of buying audiences, go to premium marketplaces and buy media. If you need to reach affluent males, try a site-specific PMP with a publisher that’s known to draw a loyal, engaged, predominantly male audience. 

That may feel like a step backward in the programmatic era, but traditional media planning is still valuable — and becoming more valuable — as cookies crumble and fraudulent data continues to plague the market. As a bonus, marketers may find these audiences equally engaged, but significantly less expensive.

To ease users’ fears, whether you intend to take a step back from data or not, marketers and publishers alike may want to educate them on how your organization is using data, and provide a clear opportunity to opt out. You may also consider offering them a survey to allow users to indicate if they’re shopping for themselves or someone else. You can then ask if they’d like to be notified about related items, or offers relevant to the items for which they’re shopping. You could even go a step further and give them the opportunity to classify themselves.

Relationship Status? Still Complicated

I understand data is a good thing, but let’s try to remember that it isn’t everything. If our use of data scares users away from our sites or our ads, is it worth the risk? Marketers always strive to use data to be customer-centric, but if the use of data makes the user uneasy, is it really customer-centric? Or marketer-centric?

Data complicates everything, and until we can iron out all the kinks and make our use of it safe, seamless and clean, we should consider balancing our data relationship by giving a little distance and considering alternatives — at least part of the time. 

So I’m not breaking up with data, and I don’t intend to. But our status is still “it’s complicated.” I’m just planning to take it slow.