Using the Pareto Principle's 80/20 Rule to Improve Your Marketing ROI
I've got a coupon sitting on my kitchen table for 10 percent off an oil change from the dealership where I bought my first car - a Toyota Camry - in New Jersey 20 years ago. While I appreciate the thought, I've since moved to Chicago and traded in that Camry, making the cost of the postcard basically a waste.
It's a harsh marketing truth that many businesses fail to realize: only a small percentage of people they advertise to will ever make a significant contribution to their bottom line. It follows what's called the Pareto Principle — also known as the 80/20 rule — which states that 80 percent of your marketing payoff will come from just 20 percent of your customers. What my dealership failed to realize is that by moving and selling my car, I've fallen out of the top 20 percent into the bottom 80.
The 80/20 rule was first espoused by Italian economist Vilfredo Pareto in 1895 and has been accurately applied to analyzing most areas of business, from sales to human resources, finance, and manufacturing.
“Many high-performance organizations remain passionate about Vilfredo Pareto," says Michael Schrage, author and research fellow at MIT Sloan School's Center for Digital Business. “And I'm betting that next-generation algorithms will supercharge Pareto's empirically provocative paradigm."
The Costs of Over Marketing
Nineteenth-century U.S. business leader John Wanamaker coined the famous marketing adage, “Half the money I spend on advertising is wasted; the trouble is I don't know which half." Wanamaker's words go right to the heart of how the Pareto Principle can be applied to over-marketing.
Let's go back to my car dealership coupon. What are the odds that I'll ever use that coupon back in New Jersey? Probably zero. Let's estimate that the dealership is spending 70 cents on the postcard and another 35 cents on postage. If you consider that the average car dealership sells about 22,000 cars over a twenty-year period and that about 14 percent of people move out of state each year, just imagine the number of marketing dollars the dealership is wasting on physical mailers to myself and others.
For AI to address a situation like this, you need to take advantage of the data you have and use it to become aware of when a shift out of the 20 percent has happened. It's not enough to just have the current information; if the car dealership has your new address in another state but continues to send you mailers for a discount on your next oil change, that's a failure to recognize the shift, not a lack of information. This shows how shifts out of the 20 percent can be recognized by simply leveraging AI to examine the existing data.
“Greater volumes and variety of data guarantee that AI algorithms get the training they need to get smarter," says Schrage.
As these AI algorithms get smarter — by analyzing first and third-party data, for instance — businesses can begin implementing that machine learning into their Pareto marketing segmentation. Machine learning provides systems the ability to learn from experience, without being explicitly programmed. That means an AI algorithm can be applied to automatically segment your customers based on the Pareto model.
Taking a Predictive Pareto Approach
Marketers are, in fact, already taking a more data-driven approach than ever in identifying their most — and least — valuable customers. For example, AI algorithms can now analyze vast data-sets of potential and current customers — including factors such as internet behavior and purchasing patterns — to determine who fits into their top 20 percent and who doesn't. As the use of AI in business analytics increases, experts like Schrage predict that the power of the Pareto principle will supercharge target marketing.
Advanced Pareto analytics using AI will eliminate the poor prospects from your marketing database. Customer complaints, for instance, are typically an indication that an individual might be in the bottom 80 percent. Some of those customers might not be good prospects anymore. But some complaints are due to legitimate product or service issues, and AI algorithms can analyze individual customer datasets to determine which Pareto bucket the customers fall into.
AI will also help marketers understand which products a customer wants. That way, the company won't waste time and resources advertising things the customer is not interested in (such as driving across the country for a discount oil change).
Then there's what Schrage defines as a “Super Pareto" approach, in which marketers can start implementing a more predictive model in terms of how they address potential over marketing. A customer might currently be in the top 20 percent, but powerful AI software might predict — based on individual behavior and larger trends — that he or she will fall out of this tier in a matter of weeks, months, or years. Marketers can then taper their communication efforts to certain individuals or clusters based on those predictive analytics.
The Pareto Principle is something that's been used by marketers for decades to identify, win, and keep the most valuable customers. But winnowing out the least valuable customers is just as important due to the high costs associated with over-marketing.
Beyond target marketing, AI systems can automate the process of tracking and analyzing its customers in order to determine if and when they eventually move into the top 20 percent. This sounds a lot easier than it actually is, which is why technologies such as AI — combined with an organizational commitment to taking a data-first approach to marketing — can help you optimize your marketing resources.
Getting started can be challenging, but Keyence is experienced in data first strategies and data analysis and is ready to help you get your projects off the ground. To learn more about how our AI, Ki can help, download the 3 Key Features Digital Brochure.
LATEST POST : What is Data Visualization and Why is it Important?