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Why data is like a crystal ball for business

Despite having a relatively short history, the world of big data is increasing and evolving at an astonishing rate. Now, we’ve gone beyond pure data analytics and moved into the predictive realm – where artificial intelligence and machine learning solutions are being applied to help businesses actively predict and forecast trends based on existing data.   

Writing recently for RISMedia, Nick Caruso suggests that predictive analytics is becoming a competitive differentiator, driven largely by better storage solutions and cheaper hardware.

“…stepping back to see a bigger picture, predictive analytics can do so much more than determine where a market is heading: it can detect fraud and other financial abnormalities, help reduce risks via credit score generation, optimize a company’s marketing campaigns to help it foresee consumer responses, and improve internal operations (think, hotels, high-end restaurants and the like).”

“If predictive analytics aren’t a part of your business plan, you may want to re-plan,” he adds.

A recent article published on Forbes also highlights several relevant examples of how artificial intelligence and real-time data analytics is making an impact when it comes to transforming the customer experience. 

In November 2017, for instance, Adidas released a mobile app which evolves as a customer interacts with it, tailoring to the preferences and behaviour of the user to create a highly personalized mobile experience. Embedded artificial intelligence learns about the user’s specific predilections to show him or her customised product recommendations, articles, blog posts, videos and real-time updates about the user’s favourite sports and athletes.

For businesses of all sizes, the ability to predict trends and preferences by honing in on existing data – such as customer behaviour - is becoming more and more essential. In the retail space, for instance, it’s no longer enough to determine how a customer interacts with a brand while on the website. To get a deep picture, retailers need to consider the full omni-channel experience. What does the same customer do when they walk in store? Do they complete most sales on their mobile device or a tablet? And what other things does this customer buy?   

This level of complex and cross-channel analysis is becoming more and more commonplace – enabled largely by artificial intelligence and machine learning.

PWC Global predicts that artificial intelligence will contribute $15.7 trillion to the global economy and by the same time, local economies will see an approximate 26% boost in GDP from AI activities.

In the same report, PWC also suggests that 45% of total economic gains by 2030 will come from product enhancements, which will stimulate consumer demand. This is because artificial intelligence will drive greater product variety, with increased personalisation, attractiveness and affordability over time.

By tapping into these advances in technology, and using data as a more reliable “crystal ball”, businesses can, for instance:

  • Fine-tune their future product and service offerings based on real-time customer needs and preferences
  • Make the customer experience far more personalised and relevant – only showing customers information that will be of relevance to them based on their behaviour in the past
  • Determine if a particular customer is lagging in terms of his or her brand loyalty and take active steps to prevent him or her from going to a competitor
  • Predict the failure or less-than-optimal operation of a particular asset (e.g. a fridge within a supermarket) and provide predictive maintenance to ensure the problem doesn’t escalate. 
  • And much more.

Want to learn more?

If you want to find out more about Empired’s Member Analytics solution and how we can help, download Customer and Member Analytics resources now, or get in touch with us.

Posted by: Ben Johnson, National Business Manager, Data Insights  | 26 March 2018

Tags: Data Analytics, Data Insights, Customer and Member Analytics, Business Insights

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