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Business, Science

Tips to Making Great Data Products

  1. Don’t try to be too clever. Simple, straightforward approaches beat cleverness 9 times out of 10.
  2. Start with something simple, then make it more complex if needed. Don’t start with something complex and then simplify.
  3. The hardest part of data science is getting good, clean data. Cleaning data is often 80% of the work.
  4. Try to get clean data from the front end (i.e. the user) instead of cleaning it on the backend. For example, if you’re trying to figure out what company someone works for, it’s easier to guide them with auto-complete or “did you mean ___?” suggestions, rather than accepting whatever they type and trying to understand it later. You’d be surprised at the number of ways in which people can input the same thing if you don’t give them any guidance.
  5. Use humans in general and Mechanical Turk specifically for early versions of your product, then try to automate and streamline as desired.
  6. Build easy products first. For example, start with collaborative filtering before diving into fully personalized recommendations.
  7. Showing users their own data via charts, blog posts, etc. is a great way to engage them.
  8. When showing data, think about 1) what you want the viewer to take away, 2) what actions you want them to take, 3) and how you want them to feel. Don’t overload people with too much information or creep them out with inappropriate details.
  9. Set user expectations low. If you set high expectations and screw up, it’s very hard to regain a user’s trust. For example, if you tell someone, “We know you will love XYZ!” and they don’t like XYZ, they’ll be skeptical of your future recommendations — or even ignore them. If you reframe as, “Are you interested in XYZ? No? Okay, sorry!” then users will be more forgiving.
  10. Unfortunately, the best way to test data products is in production. It’s the only way to find out if your recommendations are effective and to learn about all of the warts and corner cases that lead to embarrassing mistakes.
  11. Simple beats clever 9 times out of 10, but you need to be able to recognize when to build something sophisticated.
  12. Try to augment humans and make them more efficient instead of trying to replace them. People generally dislike feeling unnecessary or replaceable.
  13. Minimize friction in your product. If you’re asking users to answer questions or input data, make that as easy and painless as possible — otherwise users won’t do it. Nobody reads manuals and instructions anymore. Strive to make products that are as intuitive as the iPad or Angry Birds.
  14. Every time you ask for data, your conversion funnel takes a 10% hit. Try to keep all questions lightweight and easy to answer so that you can minimize the damage.
From: http://blog.relateiq.com/the-data-revolution/?mkt_tok=3RkMMJWWfF9wsRonvqXNZKXonjHpfsX77e4uT%2Frn28M3109ad%2BrmPBy%2B3ocFWp8na%2BqWCgseOrQ8mFwIV82iSc0TraE%3D
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