Tuesday, July 19, 2016

Partnering With Data Scientists: How Market Researchers Make the Most of Big Data At LinkedIn

An interview with Sally Sadosky, Group Manager in Marketing Research, and Al Nevarez, Senior Manager in Business Analytics, from LinkedIn

The introduction and evolution of big data has opened up a whole world of new opportunities for market researchers. However, it has also brought with it a set of challenges, not least around the skills gap traditional market research teams are facing.

With 400 million members, maximizing this wealth of data is more pressing for LinkedIn than most. We spoke to Sally Sadosky, Group Manager in Marketing Research, and Al Nevarez, Senior Manager in Business Analytics, from the social media giant about how internal partnerships between departments has helped them gain invaluable insights from their data.



How has market research changed with big data?

SS: “There’s been lot of changes and all for the positive. At LinkedIn because we are able to look at the behavior of the members, we are able to do a lot more research in advance – looking at behaviors, looking at trends, testing hypotheses. When we actually talk to members, either through quantitative surveys or qualitative methods, we can really focus our questions.

We have already fully analysed what we know to be facts, so we don’t have to spend time asking them what they do, now we can spend all our time on the ‘whys’. Our surveys tend to be a lot shorter, which is great for response rates and completion rates. Our in depth interviews tend to be a lot more focused as well, as we can say ‘we noticed you do this, tell us why.’



What skills does a market research team need to take advantage of the big data opportunity?

AN: “It starts with a healthy, inquisitive, imaginative mind. We like to look at this Venn diagram of skills that refers to software skills, maths skills and business skills. We look for folks that have all three. If you only have two of those it is dangerous; if you’re the hacker with the business but don’t know the math and statistics, you can come to erroneous conclusions.

At the end of the day, it’s about being comfortable with all kinds of data – we have 400 million members on LinkedIn which is a lot of data. But we don’t collect 400 million survey records – that data is smaller. It’s about being creative and understanding the technology well enough that you can bring the little data and the big data together to help make big decisions.”

What tips do you have for other market researchers interested in collaborating with the big data aspects of their organization?

SS: “It’s a little bit of a scavenger hunt in the beginning because the data scientists are scattered throughout the company and they don’t report in to marketing where I sit. You have to create those relationships. I focus on small wins. We are jointly storytelling and that gets people asking for more, so I can go back and ask for dedicated resource, hire more people or ask for 20 hours rather than 5 hours.

It has to be a very proactive thing as in many companies they are still considered very separate disciplines with very separate approaches. We think about the same thing; we think about member empathy and telling the story of our members, and now we have a lot of facts and a lot of opinions and we are able to put those together in a seamless way which tells really good member stories. It’s being proactive and being persistent in getting those small wins.”

AN: “If you’re thinking about a data science team, think about how that team can really drive the bottom line for the company and then that will help that team thrive and grow and therefore be able to support all these other organizations.”

Watch the full interview below: 

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