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I am a budding data scientist and I regularly participate in data science contests on CrowdANALYTIX and I found a recent one extremely interesting. The contest is closed but its an interesting problem where the solvers were asked to forecast the market estimate for Digital Wallets in the US through years 2015-2020 (contest link and description: https://www.crowdanalytix.com/contests/digital-wallet-market-estima...).

4 forms of payments as digital wallet transactions were to be considered-

  1. Paying online
  2. Paying on mobile
  3. Paying in-store
  4. Peer-to-peer payments

I started off by identifying Paypal, Google Wallet and ApplePay to be the biggest players and collected overall consumer spending figures and spending using digital wallets for the year 2011-2012. I tried to forecast population, consumer spending and digital wallet spending for the years 2015-2020 to build a prediction model around it. I could not devote a lot of time to finish this task due to commitments at my full time job, but now I want your expert help in understanding how you could tackle this problem and how one approaches a problem like this. I just want to learn how to approach a prediction problem, and how what you think and plan while solving this problem.

Thanks

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