Don’t Answer to Algorithms, Put Data to Work for You

Jim Ganzer, Chief Strategy Officer | The Adcom Group

From tracking campaign KPIs to monitoring fundamental business metrics, leading organizations rely on data to guide their decision-making. While analytics have become table stakes in marketing, many great brands have found their competitive advantage by using data. What separates good from great is the role data plays in the decision-making process. Does it drive decision-making, or does it inform decision-making?

I have seen data-driven decisions work. They can increase web traffic, boost site engagement, improve ad performance and drive leads. While data-driven decision-making can generate positive results, just following data can lead to misinterpretations and numbers without context.

A data-informed approach, however, leverages your greatest asset in decision-making: your people. Inquisitive people tend to ask intuitive questions, and the questions we ask of data – How was the data collected? What does it really represent? What isn’t there? – are crucial.

A data-informed approach, however, leverages your greatest asset in decision-making: your people.

With curious and challenging minds, an understanding of the business and data-specific contexts, people can answer critical questions that are difficult to quantify and inform future questions that could lead to breakthroughs.

We saw this play out in the widely cited story of the Netflix Prize. Netflix’s mission has always been about connecting people to the movies they love. To help customers find those movies, they developed a recommendation engine in the early 2000s called Cinematch to predict whether someone would enjoy a movie based on how much they liked or disliked other movies.

When Cinematch failed to meet its standards for personalization, Netflix decided to crowdsource a technology solution through a contest known as the “Netflix Prize.” A $1,000,000 prize was to be awarded to any team of developers who could reach a prediction accuracy bar that was 10% better than the results from Cinematch. The catch was that they had to share their method with Netflix for the tech giant to implement.

Hundreds of teams worked on algorithms for years, tinkering and testing toward incremental progress. It was three years before a winner was finally declared. Oddly enough, Netflix opted against implementing the winning code. Why? Because human intuition already solved the problem. Netflix was so focused on data that they never truly thought about the problem.

Why weren’t a user’s movie ratings a stronger predictor of preference? Because several people were sharing a single user’s profile. The problem is obvious once you see it. That’s the danger of siloed thinking. When intuition led Netflix to test multiple profiles on a single user account, relevance scores shot significantly past 10% overnight.

Inquisitive people who keep the bigger picture in front of them are essential components in data analysis. To optimize those components, the analysis requires designing: start with the problem, then refer to the problem and continuously reaffirm the problem throughout the decision-making process to ensure alignment.

Position your people to put your data to work when designing strategy and have them use it to answer key questions throughout implementation. Don’t outsource your decision-making process to an algorithm.

Jim Ganzer is Chief Strategy Officer at The Adcom Group, a creative marketing resource that partners with leading organizations and growth-minded companies to help them achieve their business goals.

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