Marketing may just be the most complex profession in the world right now. There’s new tech, new media platforms, new consumer habits and constantly changing attitudes, needs and behaviours. And all of it is evolving, faster than ever. Now throw AI into the mix. It’s like marketers are running on a treadmill that’s moving faster and faster. But it’s not just speeding forward (and up and down). The treadmill marketers are on is also spinning both left and right (sometimes simultaneously). And making giant leaps forward faster than any runner could respond to. Welcome to the data-driven marketing world in 2021. I hope you have good shoes on and lots of water!
To make sense of this seemingly chaotic situation, In Partnership With explores the latest in AI machine learning and data-driven decision making with Reagan Zuzarte. Reagan is the Founder and President of Triangles, an ROI-centric marketing optimization firm. Over the last 12 years, Triangles has worked with innovative customers in the real estate, financial, retail, spirits, hospitality and events spaces and more. Their AI-enabled process uses structured learning to establish baselines for paid media. From there, they test which additional media spend drives impact; adjusting and efficiently scaling parameters that are reliably adding incremental value. It’s a proven approach that yields an optimized result for customers.
DATA-DRIVEN MARKETING TODAY
Reagan’s team has a primary focus to bring a data science aspect to media media performance. Key questions they consider include: How do you measure the incremental impact of media on their consumers, whether they are consumers or businesses? How do you measure the impact of media across your consumer journey? The Triangles thesis relies on being as agile as possible with your media mix. That way, you can let the data decide for your campaigns.
Triangles strives to ‘tell the story’ with data-driven marketing to understand how to actually optimize marketing efforts. This includes things like spend, creative messaging and geographies a brand is active in. It’s about taking the signals that come back from consumer behaviour. Once successful – which takes some testing phases to gain – you’re eliminating the guesswork from the equation. This foundation of a strong experiment design allows his team to make more reliable predictions. When a customer sees the data transparently, in a normalized way, making decisions become easier and efficient.
With the latest marketing tech, the guesswork is being removed and now brands are optimizing targeted messaging at an incredible pace. It’s the opposite of trying to be all things to all people.
Instead of ad saturation, Triangles’ campaigns allow brands to speak with those who really are most engaged and who are converting to revenue for your business.
CHANGES IN THE MARKETING ECOSYSTEM
Reagan acknowledges that there is part art and part science to the marketing industry. So when asked what the secret is behind his team’s data-driven marketing formula, he admits there is no one set of answers to any customer question. But there are some common forces at play.
Brand teams that are data and digitally savvy, while being broadly knowledgeable about marketing strategy are performing at an all time high.
Five or 10 years ago, performance marketing – whether by outsource or internal – was the first domino to fall in the data-driven marketing landscape. Reagan observes that has now led to more and more tech with the tech stack helping to do things like optimization and attribution. But, even with advanced tech, it’s still complex. Sure, there’s more tech for evaluation, but it hasn’t really made things easier. It’s still quite murky in terms of what ‘good’ looks like. Often, Reagan notes, there’s different and often conflicting methodologies on measurement. For instance, what you would measure internally on your own analytics versus what you might see in an external data management platform. Plus, layer in the data a brand will receive on a publisher exchange or programmatic exchange like Facebook or Google. Aligning all that disparate data is still a challenge.
PRIVACY BECOMING A MAJOR FACTOR
Take all that context and then add in…
