Home Data-Driven Thinking Don’t Become ‘That Brand’

Don’t Become ‘That Brand’

SHARE:

nancy-hall“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Nancy Hall, senior vice president at Conversant.

Whether it’s a phone, laptop or tablet, cross-device matching accuracy is essential to overall marketing success. The largest obstacle of optimal accuracy is personal data leakage, which occurs when valuable pieces that make up consumer profiles are passed between multitudes of third-party sources.

What does this look like by the time the information is passed all the way down the line? Like a bunch of marketers who are uninformed about their target audience. While one brand may think a customer is an 18-year-old male who loves extreme sports and Mountain Dew, it may really be targeting a 35-year-old female who wants nothing to do with those things.

Brands understand that users don’t want to receive poorly targeted ads. Not only will the ads get ignored, but users begin to lose a certain sense of respect for the brand in the process. To illustrate this, here are three recent, real-life examples of brands targeting me poorly online.

I visit my gym multiple times per week. I also pay a personal trainer for weekly sessions. So imagine my annoyance when my gym recently targeted me with ads to join at rates – both for the membership and the trainer – that were lower than what I am currently paying. What made the situation much more laughable was that each ad featured my personal trainer. Nothing makes your members or subscribers feel valued less than blatantly showing them that you don’t know they exist.

Another example: my bank. When it comes to companies that should have all the necessary information on its customers, banks should be right up there at the top of the list. Why, then, is my bank sending me ads for Apple Pay if I use an Android phone? The bank was able to target me based on my location in New York but the miss in ad targeting content completely destroys any personalization they were hoping to build with me. Again, this is a brand that is spending money on digital advertising and not extensively using the valuable data they have to get their specific messaging to the right people at the right time.

Finally, there’s the retailer that sold me my new suitcase. I purchased the bag after doing some extensive research and have used it on multiple occasions in the two months I’ve owned it. I absolutely love the suitcase. It’s great. What I don’t love, however, are the ads the retailer is still serving me to buy it. I have received multiple mobile ads every day since the purchase. So while I love the bag, the retailer is an entirely different story and I won’t ever buy from it again.

While these are just three examples of data targeting errors that happen each and every day, the key takeaway is that these brands aren’t fully valuing the power that their data possesses, and they’re prioritizing scale over quality. Not only is this approach annoying for consumers and potentially a detriment to the future of the brand, but it’s also a complete waste of money for the brands.

Marketers are paid to ensure that our brands are seen in the best light in as many consumer interactions as humanly possible. Are there going to be instances when that isn’t the case? Of course. But to the extent that we do have control, like in the case of our customer data and what we do with it and who we share it with, we must be vigilant in protecting its integrity or we risk becoming “that brand” over time.

Follow Conversant (@conversant) and AdExchanger (@adexchanger) on Twitter.

Tagged in:

Must Read

Predict Bowl Icon. Magician Element, Forecasting Symbol – Vector.

Why This Marketing Measurement Company Just Open-Sourced Its Forecasting Engine

MMM can tell marketers what worked, but Lifesight’s open-sourced forecasting tool aims to tell them what to do next.

Podcasts Are Becoming More Programmatic. But Now Advertisers Have To Keep The Ad Load In Check

As programmatic buying becomes more common in audio, marketers and platforms fight the temptation to cram in as many placements as possible.

PubMatic Jumps On The Show-Level CTV Targeting Bandwagon

Connected TV advertisers are still pining after show-level control. And PubMatic announced contextual targeting at the episode level is available to media buyers accessing CTV inventory through its platform.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

SQREEM Touts The Large Behavioral Model – Not The LLM – As The Winning Predictive Engine

Rather than relying on machine learning, SQREEM uses a mathematical AI model to track how systems change over time and predict audience behavior.

Comic: Game Over?

The Google Antitrust Remedies Are Too Little, Too Late – But Publishers Will Take What They Can Get

Given how much the market has changed since the Google trial began, and the wiggle room in the ruling itself, publishers aren’t expecting much relief from the court’s behavioral remedies.

Comic: "Deal ID, please."

Can Sell-Side Curation Solve The Cookieless Audience Problem For Advertisers?

Indie agency KWG says sell-side curation can target more high-performing inventory with better match rates and lower data fees than buy-side curation.