Over the last decade, marketing has drastically shifted its foundation from innate intuition to calculated analysis. It shifted from an art form to a science.
Strategies are now driven by unprejudiced analysts instead of committal creatives. More importantly, strategic data insights give each marketer the ability to provide the best experience possible for the customer.
Yet one area of digital consistently lags behind the rest. As disruptive and momentous as the data revolution has been, digital advertising has been slow to embrace it.
Twenty years ago, advertising was the most data-driven industry in the market. It utilized demographic data through publishers to identify target markets. The problem is, many digital advertisers haven’t evolved since then. They’re still relying, in many cases, on demographics.
And as we all know, no brand can settle in the digital age; it’s a constant evolution. Marketers probably tell their kids bedtime cautionary tales about the brands that lost their edge because they stopped moving forward. The list is long.
But there’s light at the end of the tunnel for digital advertising. Programmatic’s ascendance has opened a path forward to evolve from the era of Mad Men to the age of Silicon Valley. Although, data points run a broad spectrum of quality.
Data is quite similar to making sausage: you don’t often know what you’re getting and there’s good quality in some, but there are also some shady practices to dupe the unsuspecting buyer.
You get what you pay for with quality and you need to unpack the data to see what you’re buying.
The majority of data in digital is currently unrefined, broad and hard to action – it’s filler. Marketers need to avoid that data pitfall within the digital sphere.
Most of the unrefined data that brands utilize to target consumers digitally is considered third party data. It’s the data that publishers love to offer brands based on their readership.
Third party data, in essence, is demographic. It’s your age, your gender, what you read, where you live, and while demographic data is better than no data, it’s often a false promise that looks glamorous when presented, but lacks in execution and results.
In other words, demographics are filler, they can help plug cracks in your customer view, but they will never give the information necessary to execute a successful campaign.
Let’s consider a quick example of third party’s downfall. Let’s say you and I have some similarities in our demographics and preferences. We are both 54-year-old males, we live in the same city and we both subscribe to a sports publication.
While it may seem like we have a lot in common, what can we truly correlate from those identifiers? We may be the same age, but where the Rolling Stones might be more aligned to my age, I might actually listen to the same music as today’s 15-year-old kids.
We may live in the same city and have similar jobs, but that doesn’t mean we both wear suits and shop at Brooks Brothers.
With third party, there are no actionable insights to draw conclusions on behavior. If marketers want to have a true view of their customer, they need transactional data to be the foundation.
There are two forms of data that are reliable and actionable for marketers – first and second party. The important difference between good data and fluff is that with good data, there’s a retail action performed by the customer.
It is based on transactions; the only measurable form of data marketers can develop strategy around. A transaction is a sign of intent; it provides guidance on what the customer is looking to buy. If we can build up enough of a history with transactional data, the patterns emerge.
First party is data collected through your brand based on transactional history and account preferences.
It’s your data; nobody else can use it unless you’re selling. It’s by far the best form of data to market against, but it is somewhat limited to re-targeting since the consumer has already purchased with your brand.
Within a strategic mindset, first-party data is going to be amazing for current customers – its value as a retargeting tool is unparalleled, but it’s not as useful with acquisition. Focus on up-selling and increasing return frequency. Use it to drive product newness and seasonal initiatives.
Second-party data is where things get really fun for marketers. It’s the type of data that’s going to support all of the acquisition objectives for the season.
Second-party data is usually going to be transactional, as well. The difference between first and second-party, is that second-party data is collected from another brand.
In essence, we can take first-party data from other companies and market against it as if it were our own. This form of data is also available through an exchange and it avoids some of the filler you get from aggregators that don’t have as much clarity into what you’re buying.
So instead of focusing on whether or not potential customers live in the same city, or subscribe to the same publication, marketers should be focused on finding like-minded brands with a similar customer base.
In the next example, let’s use second-party data. Let’s say we are running acquisition for a high-end chain-store fashion retailer with an AUR between $70 and $90.
It makes much more sense to harness the transactional data of J. Crew, or even Pottery Barn, than it does to target 54-year-old men that live in the same geographic area. There are more similarities between the consumer base and we also know intent since they have purchasing power.
In the end, what marketers want to target is an actionable lifestyle, not passive demographics.
The rise of programmatic is one of the most exciting developments for the digital sphere. It opens a new window for advertisers and it is already shaking the foundations of how publishers operate.
If programmatic is to evolve and have continued success, it needs to follow the path email, CRM, loyalty and site-marketing have taken of utilizing actionable, reliable, first and second-party data to prove out acquisition and investment.
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
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