Lisa Bradner leads Yieldmo’s AEROS Attention Analytics. Attention Analytics uses consumer attention signals to improve online advertising.
Twentieth-century manufacturing and marketing have operated at scale. Media scaled large audiences across big platforms, such as television, where a single commercial could hit screens in every household in its target demographic. Warehouses and distribution were optimized to ship pallet loads of products to large retailers. Mantras such as Walmart’s “Every Day Low Price” became a religion as consumers flocked to low-cost goods. Mass production was the name of the game, and as factories moved overseas, companies focused on squeezing out costs and finding efficiencies.
In the advertising world, companies brought their portfolio of brands to large agencies and asked them to negotiate media tonnage so they could get as many impressions as possible for as cheap as possible. Measurement was challenging, and it was difficult to know which ads were making the most impact, but it was cheap so you could cover up the unknowns with sheer volume.
The rise of the internet challenged the “gospel of scale.” Suddenly, long-tail manufacturers and consumers could make their voices heard. The internet made advertising inventory theoretically infinite, and new direct-to-consumer brands proved they could sell differentiated products without a retail presence or mainstream media.
Yet, the “gospel of scale” persisted. It turns out that physical retail and mass media still have a role to play in reaching and engaging new audiences. Even what I consider the greatest internet upstart, Amazon, proved that massive scale is still a competitive advantage.
Twenty years into the new century, it’s time to rethink the dichotomy of scale versus precision, mass versus intimate and large versus niche. It’s time to see that brands can achieve both precision and scale.
We tend to think of precision and scale as opposites because we’re coming from the scale perspective: top down, the biggest first and efficiency over everything. Media, which has used reach-based planning for years, works this way. It uses television to cover as much of an audience as possible and then uses other mediums to fill in the holes TV leaves behind.
But what if we thought about the problem from the bottom up? What if we took the most granular data and insights available and built our business plans from there?
As a leader in a company that specializes in gathering this type of data to help inform brands’ online advertising, I believe that if more of us approached marketing challenges this way, media buyers would stop thinking about just reach and think about the individual impression. Marketers would stop talking about audience segments and focus on individual behaviors. Real-time technology could replace annual plans, and a brand’s focus on relevance would supplement lifetime value.
This kind of thinking feels radical and instinctively seems difficult because historically, we’re coming from a perspective of aggregation and averages. When we turn this equation on its head, atomize our data and lean into real-time technology and predictive analytics, it actually makes a ton of sense.
As individuals, our digital footprint is massive, and it allows marketers to find, for example, a 25-year-old man who lives in New York City, went to a Big Ten school, doesn’t own a car, eats fast food for breakfast and is looking to open a Roth IRA. With machine learning and real-time technology, brands can understand the digital signals that man emits when he is in the market for a product or service. They can also extrapolate that information to identify all the other people who show similar interest signals, regardless of whether they are demographically similar.
You can still target a big audience, but how you build that audience is not on old “birds of a feather flock together” marketing adages. When you look at data through this end of the telescope, you can even address the last mile of retail challenges through more accurate product forecasting and the ability to adjust warehousing and distribution strategies to meet that demand.
From toilet paper shortages to the increasing adoption of online grocery shopping, 2020 has proven the limitations of 20th-century media and marketing. No one should expect things to go back to the way they were. Instead, our job as business professionals is to capitalize on 21st-century thinking by building the technology infrastructures needed to store massive amounts of data, operate in real time and support businesses in responding to individuals whenever they signal their needs.
Simply put, brands cannot solve the challenges of the future by relying on approaches of the past. They need to embrace working with precision at scale.