Data Analytics: Interview with Professor Wayne Winston by Gerry Park

Author:Gerry Park [Park, Gerry]
Language: eng
Format: azw3
Tags: Exclusive Interview with Professor Wayne Winston
Published: 2018-11-24T16:00:00+00:00

On marketing analytics

well many of you probably bought a product from amazon.com and you may not know that roughly 35% of all products purchases from amazon.com come from product recommendations. The tool here is called is collaborating filtering. It involves filtering through all the books you might want to buy. And it collaborating because it uses information on the web. And so Netflix uses collaborating filtering to recommend movies to you. And Netflix had a $1 million prize to improve the recommendation algorithms. And a bunch of computer scientists won that, so they are very serious about the importance of that, if they would give people a million dollars.

Another example comes from Match.com, okay. Now, Match.com if you could keep as Match.com, the average customer. Add the average client on match.com on that site, one more day, and match.com would make $10 million more a year. So, they have plenty of analytics professionals who work on trying to make people not leave match.com. And it is tough there, because people leave match.com because either they find success or failure. There is not many industries where that is true. Now, the airlines, you are probably not happy with this example.

But basically when you buy a plane ticket you know the price varies from day to day. And that is an example we call yield or revenue management that is a very complicated method in analytics, which helps the airlines make the most money from the seats on the plane. And of course takes the most money out of our pocket, but the airlines, many of them would go bankrupt if they did not have the revenue management or the yield management. Direct mailing. You probably get mailing from catalogues. So a catalogue company wants to decide if they wants to mail out 100,000 catalogues.

Who do you mail to that will get the maximum response? And basically, you can use analytics to sort of identify the type of person who's most likely to respond to a mailing. Media allocation is another example of marketing analytics. If you work for a major car company, you will see a lot of your company's car ads on TV. So what TV shows should they advertise on? Should they be advertising on sporting events? Should they be advertising on basically a cable a cable will show on lifetime. And so basically trying to figure out where you put the car ads to sell the most cars is a very important decision for the company that make cars or any product.

Drug companies are big into sales force allocation. So a company like Eli, Eli Lilly wants to know for a given drug how many sales calls should I make on that drug? Or should I get more benefit from having a sales call on a doctor about a cancer drug or a diabetes drug? Cause you have limited sales resources. And you can even use these programs to try and figure out how big should your sales force be.

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