: Analytics

What Should You Do When a Test is Flat?

A/B testing is a bit like the Olympics. You always go for gold. Ideally, you’re looking for Michael Phelps-style wins: long-term, consecutive, and (seemingly) effortless. And if you fail to make it to the top-level...

What Essential Skills Should You Look For When Hiring an Analyst?

The importance of a good analyst can’t be overstated. If your organization is data-driven (and it should be), an analyst provides unparalleled guidance and insight: He or she identifies where to allocate resources, influences company strategy,...

Is Personalization a Net Positive?

“A squirrel dying in front of your house may be more relevant to your interests right now than people dying in Africa,” Mark Zuckerberg once said. There was some gray in that statement. His use...

March Madness: Why an Algorithm Probably Won’t Give You a Winning Bracket

Although I have a master's degree in advanced analytics, I filled out my NCAA March Madness bracket in 5 minutes, just seconds before the tip-off of the first game. Maybe you’ve heard of the model...

Go Beyond the Online Calculator to Determine Sample Size

The premise of statistics is simple: “We have a population we want to understand, but we can’t measure everyone. Let’s collect a sample and use statistical inference to make the best decisions we can.” For...

Personalization: What You Need to Know Right Now (Part 2)

When it comes to personalization, how important is data collection? What’s the best advice for companies that want to step up their game? And how might personalization technology be improved in the future? In this two-part series...

Personalization: What You Need to Know Right Now (Part 1)

How can you measure the success of personalization? How many user segments should be used? Is real-time personalization a current reality—or a far-off dream? In this two-part Q&A series, we ask a senior member of...

Dealing with Outliers (Part 2): Avoid These Common Mistakes

Part two of a two-part series. In the first post of this series, I discussed the different types of outliers and why they’re important. If you haven’t already, take a couple of minutes to read...

Dealing with Outliers (Part 1): Ignore Them at Your Peril

Note: This is part one of a two-part series. One of the foundations of testing is repeatability. If you can’t repeat a test and get similar results, you can’t trust the data. And one of...

Can Your Quantitative and Qualitative Data Work Together?

“It would be nice if all the data which sociologists require could be enumerated,” sociologist William Bruce Cameron wrote in 1963, “because then we could run them through IBM machines and draw charts as economists...

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