Bringing Conflicts of Interest in Mobile Attribution Analytics into the Light
If I had a nickel for every time I heard the word transparency come up in marketing lingo, I would become the app store’s top spending user.
Don’t get me wrong. Transparency is the only way to go in a marketing ecosystem that runs on data. But when this term is often abused, it’s important to understand — and I mean truly understand — what lies beneath.
Now, let’s zoom-in on the mobile attribution space.
When we talk about attributing credit where credit is due, it’s obvious that we need someone with a view from above. Someone trustworthy who is able to rule which channel or network from among the thousands out there did the trick that led to an install, engagement or purchase, and which did not. And make it count. Like a judge.
But just like in the judicial system, the only way it can work is if the judge is impartial. No hidden interests or axes to grind. In short, unbiased, and you guessed it, transparent.
What we’re seeing in the mobile attribution analytics ecosystem are companies that offer a so-called end-to-end solutions. They do it all: buy the media, measure and optimize the campaigns. Now these providers are indeed bringing value as they reduce overhead and simplify workflows. Busy as they are, this is appealing to most digital marketers.
However, what they’ll probably find less appealing are the inherent conflicts of interest such a marriage may bring. Let’s explore some of these conflicts.
Follow the Money Trail
Many companies want to expand their business in order to drive growth. So they add more components to their offering. What usually happens is that the new additions are still considered the side dish to the main course.
In our space, the core business of media companies is media buying and arbitrage. And it is the core business that generates the vast majority of revenues. The side business — in this case the attribution platform — serves the core business — which can lead to little or no R&D resources to improve the side business’ product.
The Phone’s Ringing in Support…
Advertisers seeking support from a biased attribution provider will probably find that if they are not a major source of revenue, support of their account would take a heavy blow. It simply won’t be economically viable to invest in such accounts if another part of the business generates more revenue.
Networks are also likely to suffer from a lack of proper support – either because they are competitors of a provider that has its own network, or because they do not belong to the provider’s elite club of preferred networks (those who offer the best commercial terms).
Your Data is Your Own — or Is It?
Attribution analytics providers are big data companies. They collect petabytes upon petabytes of data about ad campaigns, installs and in-app events. If a media company owns an attribution solution it has a trove of data at its disposal which it could use to optimize and monetize its campaigns across the board.
An unbiased provider would never ever use your data or sell it to third-party companies. It would also back away from any agreements with companies that could abuse it. A business that raises the flag of neutrality, transparency and reliability will never engage in such tactics because it would shoot itself in the leg by doing it.
[Lack of] Network Integrations
An unbiased attribution provider will always do what it takes to best serve the advertiser. If the latter wants to run a campaign on an ad network that is not on the list of the provider’s integrated partners – it will go ahead and integrate the requested network to win the business while at the same time adding yet another partner to its list for future use.
A biased attribution provider, however, may try to sway the advertiser towards other networks on its list, whether owned or preferred. Integrating with the network requested by the advertiser would either drive traffic to a competitor – if the company actually owns a network, or may lead to a drop in revenues – if it runs with a new partner with whom it has less favorable terms.
What Happens When There Are Measurement Discrepancies?
Since we’re dealing with some grand, complex tech platforms, measurement discrepancies, although rare, do happen. When they do, an unbiased provider will get to the bottom of it and expose the truth. However, if the same company is both the media buyer/publisher and measurement solution, it may have different priorities in mind.
When you ask an unbiased provider to investigate, it may decide not to invest in such a probe but rather “rule” in a way that would best serve its interests (for example, if it owns a network it would make a hefty sum if attributing most of the credit to its own network).
To sum up, it’s important to realize that choosing an attribution provider is a big decision as it will have a major impact on the success of your advertising efforts and business operations. To make the best decision, understanding the level of support and other potential conflicts of interest in our space is paramount.