If You Really Want to Be Privacy Compliant, Be Accurate
A new wave of identity solutions won't allow our industry to have its cookie and eat it too. Digital privacy is here to stay. Either we choose to live in denial by investing in less transparent, more wasteful versions of the past, or we fully embrace privacy by committing to data and accuracy.
Accuracy Is How We Guarantee Privacy
Today, more than 90 percent of digital display dollars are spent programmatically, according to Insider Intelligence. Why? Programmatic was a breakthrough that gave control of the ad dollar. It took marketing from an accidental affiliation with content to the right people, at the right place and at the right time. But, despite overwhelming adoption, the ad tech ecosystem is still a long way off from delivering on the original promise.
Couched in consumer protection terms, regulators and privacy activists have kept themselves busy trying to unwind data use without breaking the economy. But even as walled gardens took steps to hide their cookie pools, and while others took to branding them as proprietary universal IDs, a cookie by any other name is still a cookie. The open secret we know all too well is that cookieless match rates look a whole lot like the original cookie match rates – and that isn't good.
And this is where the problem has become systemic. We can continue to create workarounds to replace the public cookie with private cookies or go wide and unqualified with cloned and lookalike audiences to fill orders in hand, but doing either is just diluting outcomes. Poor data quality and a growing lack of transparency simply lowers the value of advertising spend and removes accountability for performance.
Consumers are pushing back on two fronts – the redistribution of their personal information and a business model that pounds them with unqualified ads. Does anyone think that less accurate workarounds will improve things? If anything, opt-out privacy schemes and workaround identity resolution with lower match rates will cost the consumer more because campaigns will turn back the clock to carpet bombing to compensate for poorer targeting. In turn, carpet bombing will turn off even more consumers and further exacerbate the two consumer trends that brought us to this point.
Our response to the privacy and data deprecation challenge needs to be better than just legal posturing for liability protection or managing share of wallet. Perhaps we need to pause and consider that the answer to a sustainable privacy policy may not be in restricting data access, but rather in making the use of authorized data transparent and the application of advertising more consistently aligned with the audience.
We truly do need to find a better way to shield the consumer from advertising they may not be qualified for and may not wish to see. To do that we need to accurately know who they are.
Respect for data accuracy is missing in our response to the privacy challenge and cookie deprecation. Today, there are no standards whether the consumer is a first-party member of the advertiser base, a prospect, or random filler defined through cloning or the least expensive data point available on a DSP. There is no flag, score, or transparency into matches from the onboarded list or segment.
A rational response is to respect user data and apply structure and transparency to every campaign. When consumers say they want privacy, very few mean that they never want to hear a marketing message. Most people want to know about life-saving drugs, better mortgage rates and new cars. But those messages shouldn't be targeted at consumers, unless they either opt-in to receive those messages or the advertiser has a permissible purpose that is validated to the audience membership.
When that purpose is inaccurate, the consumer can and should opt-out. Economic forces will direct marketers to enforce a standard of accuracy and transparency if the regulations allow them to.
Rethinking Accuracy with a Privacy-First Mindset
Under the old model, data accuracy was short-hand for a variety of attribution models — last-touch, first-touch, location-based. They came and went due to budget pressure and a lack of timeliness. As we moved into a multi-channel, multi-device world, multi-touch attribution became the prevailing methodology. Unfortunately, multi-touch attribution often means multi-touch across multiple platforms. Even when third-party cookies were a thing, there wasn't a universal or a common match key that scales across platforms. Uneven identity matching dooms a multi-platform attribution study to an unsatisfying forecasted conclusion.
But instead of trying to incrementally improve the accuracy of a broken attribution methodology, let's rethink accuracy from the standpoint of the first-party data owner's responsibility to safeguard privacy.
Member service marketing is customer communications. It is an approach to audience targeting where you limit your reach to a particular constituency of users who are either your customers or member prospects you want to engage. Member marketers won't and shouldn't accept reach outside those constituencies.
A member list can come from a variety of sources: first-party opt-in customer lists, loyalty programs, membership groups, party affiliation, site engagement, etc. However, the key point is transparency into the audience members and the ability to achieve deterministic answers to the following questions: Which members of my first-party audience saw my ad on CTV? Who saw it on display, and who didn't see it at all? If you can answer those questions — either from a scaled onboarding solution to a member list or working backwards by matching a real person to a DSP browser ID — you close the loop.
Now imagine an ad tech ecosystem where you, as the first-party data owner, were also responsible for the identity graph. What if you owned and controlled the IDs for interacting with the DSP, the mobile devices, and the connected TVs at a record level. What if the brand had access to a transparent system where digital IDs were part of an always on identity graph? The first-party data owner would know exactly who was reachable on which platform and (more importantly) when they were reached.
Addressing identity through a lens like postal CASS (Coding Accuracy Support System) and NCOA (National Change of Address) in the direct mail world means audiences never get commingled with look-alikes and constituencies that may not appreciate being contacted outside the authorized membership.
The Economic Impact Is Transformative
Making marketing more accurate and safeguarding privacy are good goals on their own. Consider how many billions of dollars financial services companies, automotive brands, pharmaceutical companies, and marketers across verticals spend on misdirected media in the name of lead-gen. The vast majority of outreach is wasted because you don't know who you're reaching, or where they prefer to hear from you.
Today it's a lot like playing "Battleship" — you fire in the dark, and if you hit something, you can begin to guess the target's identity. As a result, the cost of acquiring new customers has a significant impact on the marketing budget, but also has a big impact on the narrative around digital advertising and privacy.
Engagement that addresses the right level of reach and is accurate to the audience supports personalization that speaks to their buyer's journey with greater precision. That's a transformative change because marketing becomes a matter of conversation and conversion, instead of making educated guesses to locate audiences. It also douses the flame that makes select users and regulations so hot about data misuse.
Eventually, this transformation will impact the rest of the business too. Financial services companies, for example, could take the relatively large amounts they currently allocate on customer acquisition and redeploy those dollars into more impactful and profitable products and services. Pharmaceutical companies might see their way to apply marketing overhead toward reducing the cost of their products.
Perhaps the most transformative benefit is allowing regional vendors to confidently turn to the Internet as a replacement for engaging a relatively small number of people who might be candidates to buy an in-ground pool, replace their heating system or participate in a clinical trial for a niche drug.
Transformation of business models is what we are supposed to be good at, but all these transformations depend on data accuracy. It's not enough to say you want to improve accuracy or solve the privacy challenge. You must stop pitting accuracy against privacy, and understand that inside a member marketing services model, privacy and accuracy are two sides of the same coin.
The views and opinions expressed are solely those of the contributor and do not necessarily reflect the official position of the ANA or imply endorsement from the ANA.
Ray Kingman is CEO of Semcasting.