How To Make Data Pay You!

When I say pay, I am talking about over $3 billion this year alone. This is expected to hit nearly $50 billion by 20181. Where is all this money coming from?

There are four main uses of data to gain a benefit: advertising, marketing, product development and data management itself – yes, money is even made from managing the information! With the growing number of data entry points like: smart cars, wearables, smart cities and smart homes this is only going to grow.

We are all familiar with the ways Facebook, Google, Yahoo use our search and preference data to place adds in front of us that (or are predicted) to relate to our lives, wants and needs.

Information is sent to advertisers to enable them to target certain groups – Netflix, for example, will use data from its mega-archive to create algorithms to offer better suggestions of what its users can view. In this way it’s often about offering a better service to keep customers, rather than buying in new ones.

From my experience here are the ways I see that data can pay!

Reduced Cost

  • Process efficiencies – Reduced man hours
  • Less rework – Data accurate first time
  • Accurate logistics information – Efficient storage and transport of products
  • Accurate reports – Reduced compliance charges as is submission based on accurate rather than estimated information
  • Less returns – Customers receive what they expect as description information is precise and complete
  • Stock prediction – Analytics predict the buying pattern to ensure stock is adequate but not overstocked or sales are lost due to out of stock situations
  • Model real time exposure to catastrophic risk for insurance, financial companies health and aviation industries
  • Prediction based analytics – For health to help predict disease, illness and even help prevent accidents. This helps services be prepared for future situations
  • The infrastructure changes – Moving from legacy technology to the cloud quickly fix network bandwidth and latency hiccups, Internet connection problems, and payment processing issues for customers to avoid lost sales and cost effective management of server usage
  • End to end cost of items – Changing a part of the process may be seen as efficient, however how does that impact the full process? Are costs hidden in more work required upfront or at the end or does the product cost more to procure only to make future steps more efficient
  • Event success tracking modelling – Should you repeat the same event next year / quarter? Which event was the most successful and why?

Increased Sales

  • Increased sales from reduced marketing activity – Activity is targeted based on buying patterns and other metrics, using analytics
  • Complementary selling – To increase average order value
  • Upselling – Suggest the next model up to the customer with the benefits over the chosen model
  • Trust – Accurate information provided to customers. Easier to work with suppliers who provide the best data, reducing rework, amendments and incorrect ordering bringing efficiency to the organisation, cost reductions and increased sales
  • Lead conversation – Using better data on customers to bring them the service they need – sometimes they will not know they even need it until you show them the benefits.
  • Marketing promotions – Real time analysis of promotions, providing the ability to tweak any deals to improve effectiveness, refine targeting or as market / weather conditions or sporting results change

None of these ideas are new…What’s new is the aggregation and simulation of data from different sources is the volume, type or variety (from tweets, photos and web searches to emails, transaction and location data) and the speed of that data being available all of which can benefit the organisation in a number of ways.

What is your experience in making data pay you?
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