With automation and AI doing more and more of the heavy lifting in performance marketing, activating your data in innovative and unique ways will be crucial to gain an advantage over your competitors.
In this article, Joel Florén, Performance Advisor at Bluebird Media, digs beyond the buzz and provides a few concrete examples of how to put your data to use (he promises that not a single line of this text is written by Chat GPT).
Way back in 2016 I was at an industry event arranged by a digital marketing school. At the event, I told all the young, aspiring digital marketers what I thought about the industry's future: “your future job won’t exist in three years - the AI is going to steal your job”. Strangely enough, I didn’t receive too many recruitment leads from that event.
Fortunately for the students I encountered that day, my prediction was proven generally wrong. However, over the past few years, reality has finally started to catch up with my gloomy expectations. The use of intelligent algorithms for bidding and audience targeting has become commonplace, Google ads and shopping have paved the way for the automated black box Performance Max, and now even video ads can be generated from scratch by AIs.
In this new world where everyone has access to the same automated algorithms, how do you win against the competition? I see three primary strategies:
Provide the AI with better targets and optimization criteria
Provide the AI with better and more relevant data
Use data-driven insights to create a better offering, customer experience, and make sounder marketing decisions
So, what are the insights still available to us in the era of black-box AI? Here are a few examples:
Better targets: Google Ads performance planner
Getting your budget and profitability targets right is a key driver of performance. Along with content and customer experience, this is the number one input for modern performance marketing campaigns. To simulate the expected outcome on total sales and profitability, Google offers the tool performance planner, which uses AI to simulate conversion outcomes based on different investment levels. By actively adjusting and following up on your targets in this way, you can improve the total return from your marketing investment.
Better data: predicted customer lifetime profit
The main KPI of performance marketing has steadily developed over the years. First, we only chased clicks. With time, we learned to optimize for conversions, then for revenue, followed by profit, and now lately, we've moved on to predicted profit. This method uses your historical customer data to define an expected lifetime value for a customer, both new and existing. By using relevant first-party data and merging it with powerful machine learning, we can maximize not only short-term profits, but also long-term growth. Understanding the true value of different customer segments will help us make better business decisions.
Better offering: Price elasticity and price optimization
The worlds’ best marketing campaign won’t fix your sales if your pricing is way off. By tracking how your historical pricing, as well as your competitors’, has impacted your overall sales, you can use predictive AI to estimate the added sales effect of a discount or price hike and find the optimum price that will help you maximize the bottom line. Google merchant center offers a light version of this method with its price suggestions tool.