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by: David, Data Scientist @ Bennett Data Science

If you’re here, asking yourself this very question, you probably already know that the world is becoming a much smarter place and that data science is a big part of the cause. Companies of every size, maturity, and from every industry are leveraging the incredible power of this field to drive profits through personalization, automation, and more. As a CEO or Head of Product, you ask yourself: Does my company need it too? Am I out of the loop? 

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At Bennett Data Science, our ears perk up when we hear statements like: 

  • “We have a complicated process for doing ____.”
  • “Our product isn’t smart enough.”
  • “We don’t know much about our clients/users.”
  • “Does ____ really need to be done this way?”

Data science can be an entire product, like for Netflix, or it can be used to optimize a product that just isn’t quite as sharp as you thought it would be. In terms of optimizing your product, right now, you may very well have a logic tree with “if’s” and “else’s” that you update every week or month when there’s a new idea. Eventually, this becomes way too complex to maintain or even come up with new ideas for. Instead, data science will turn this tree into a mathematical model that is 100% tailored to your user/client base. Are you ready for the best part? We set it up so it does it by itself, and can update itself every click, hour, day, week, month, year – you name it.

 

Another example of where data science shines, is in providing insight into what made ____ work. You have people using your product and some come back to use it, some don’t, and you want to know why. Is it their age? Where they’re from? How often they use your product? Did they click on your suggested offers one, two, or three times? Without data science, this exercise takes a very long time to get very few, actionable insights. Instead, data science can reveal the most and least effective parts of your product, that your organization can leverage, to retain and impact more users. I’ll walk you through it:

You have four people using your product and you collect three data points from each of them. You are interested in drivers of a second use of the product:

 1. Gender  2. Age  3. Acquisition  Second Use
 Elsa  Female  25  Organic  True
 James  Male  29  Organic  True
 Mary  Female  19  Referral  True
 Michael  Male  23  Online Promo  False

Data science models, when you build the right ones in the right way, give us insights like:

  • Females are slightly more likely to use your product a second time.
  • Online Promotions are related to users not using the product a second time.
  • Age is not a factor in using your product a second time.

Not only does that cover only some of the insights based on only a single variable, but data science can handle many more thousands, millions, and billions of data points. Doing this sort of analysis only by hand would take immense amounts of time, if possible at all.

These are just a small portion of the number of ways data science can help you. Still not sure if you need data science? Contact us. We’ll come talk to you for free and give you a comprehensive outlook on what you can do with data science.