A company doesn’t necessarily need a fully fledged data science team and expensive tools to start doing data analysis, executives from PayPal, MailChimp and Import•io argued at Structure:Europe 2013 on Wednesday.
“I would argue one of the most sophisticated data science tools we’ve had in the past 20 years has been Microsoft Excel,” Andrew Fogg, founder and chief data officer at Import•io, said. “Businesses run on this, and not just small businesses.” A company that wants to move beyond a tool like Excel should “think about the limitations” of that program and “think about what you need from there.”
John Foreman, chief data scientist at MailChimp, said smaller companies have gotten more comfortable with data science as they’ve seen more use cases for it. While large companies like hotel chains and airlines have used data science for decades, recently storage has gotten cheaper and there are more use cases at small companies. For instance, sites that recommend entertainment to customers — “you should watch this movie or listen to this song” — “allowed people to see how they can use it.”
When it is hiring data scientists, PayPal looks for “math and stats, programming and the ability to deal with data, and domain knowledge,” said Sam Hamilton, the company’s VP of data technology, suggesting that while some of the skills have changed over the years, some of the background is the same.
And smaller companies might want to look at the data they have internally before going out and collecting social data, Foreman said. “Everyone wants to use social data. That’s fine if there’s a use for you, but look internally and see if you have valuable data, such as purchase data. That will probably be more valuable first,” and you can layer social data on later.
Check out the rest of our Structure:Europe 2013 coverage here, and a video embed of the session follows below:
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A transcription of the video follows on the next page