Artificial Intelligence Seeks to Disrupt the Retail Industry

Gyana is Betting Huge on AI's "Trillion Dollar" Potential Future

04.06.2018 | contributed by Joyeeta Das
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In McKinsey’s April 2018 report, it was unveiled that there are up to two trillion dollars to be unlocked in retail marketing and sales through the application of AI. Other sectors set to break new ground with AI in the coming years are manufacturing and supply chain, travel and logistics.

The total spending on AI-based technologies in these sectors is expected to reach into thousands of billions of dollars. Most solutions currently in development are either execution- or strategy-focused.

So, what do we mean by execution?

Airlines, for example, continually bombard us with images of exotic locations on billboards and big screens. However, how many of us have actually made a buying decision based on a single advertising image? If, on the other hand, you were kind of already thinking about it, then the nudge theory suggests a small push is all you need to pull out your wallet.

Another working example of AI being put into action – a well-known airline was recently able to hyper-personalise your “where to fly next” marketing, depending upon the propensity modelling of their customers. The result was six times more effective than they expected!

Nike has been able to increase their top line by 30% by enabling customers to engage in their windows through digital visualisation tools. Many new technologies now allow you to see 3D versions of yourself with the outfit you picked before you buy it. Stores, bookstores, and restaurants will allow you to scan and browse their entire inventories to choose what you like. Loreal now uses AR to help you experience what you look like “before” and “after” makeup. With the emergence of holograms, VR and interactive digital solutions, this is only the beginning.

However, this is expensive. For the retailers, the switching costs are significant, and the stakes are huge!

As a retailer today, you probably already know that you need an amazing tech solution, but who is your target audience? Do you know if they are the right people — the right segment? How do you know if you cam influence their behaviour? What is the proof?

The challenge is that a lot of these new solutions need to demonstrate a return on investment…meanwhile, should you continue pumping capital into new ideas? To deploy such a turning capital, the decisions need to be surgically precise.

This is why organisations are moving from data-interested to data-driven and now data-powered strategy. If data are not helping you to pick the right people and see if you have influenced them as you intended, the “execution” aspect can be wasted. What is the point of figuring out how to perfectly “go from A to B” if you aren’t certain of what A looks like and where B really is? This is why it is essential to utilise powerful data analytics to get your strategy right before you move to execution.

Screenshot of How Gyana Works  Source: Gyana

Analytics is a scary word though – I mean – think about it. Close your eyes.

What do you see when I say analytics? Suits? Keyboards? Big offices?

Now, imagine I said “big data solution”. What do you see now? “Tee shirts”? “Sneakers”? “Coffee”?

Now, close your eyes and see the person who needs to make these decisions – the CMO, the CRO, the CDO, the product merchandiser, the store operator, the IT strategy head, the creative solutions head, the CFO – who are they?

They are in between the sneakers and the suits — and at Gyana, that’s our home, too.

We are doing what Excel did to manual registers, and what the PC did to the mainframe.

In the ”mainframe universe”, you waited 6 weeks for a bug to be fixed up before you blew it up again. And spent thousands on reprogramming a giant machine.

Then came the PC — now, anyone could write anything and see results in seconds.


So, don’t wait for 6 weeks. There are moving targets in sales and marketing, and you don’t have time. Don’t wait for a consultant’s long, half-baked, data science report — they rarely use much data science anyway. Don’t spend millions on hiring a good data scientist team. They are rare, expensive, and full of tantrums…trust me.

At Gyana, we are pioneering technology that gives you the ability to explore – to ask as many questions as you like and figure out the story yourself. Now, imagine if you had the ability to accurately identify your targets, execute with your kick-ass technology solution, and then check if it is working in real time. All in one place, all in your browser. It’s a pretty exciting step forward.

Gyana-GROW is an economical deep tech tool that is designed for simplicity of use and empowers the modern day retail, e-commerce strategy and consumer good decision makers. Now, you can do at your desk what you previously could barely achieve with six data scientists in six months — not to mention the cost of purchasing data sets and the legal hoops you’d have to jump through to obtain them. A super advanced tool at your fingertips.

We are now seeing some really powerful examples of how big data can be leveraged to help shape strategy and refine execution for global real estate, financial services and public sector planning groups who want to see human behaviour at scale to make informed citywide planning decisions. When you combine science and tech with sector expertise, the results are a big jump forward.

In this day and age, there is a huge opportunity cost to not use big data. The biggest players in the market are already using data to drive all their decisions. Can you afford not to?

Gyana CEO, Joyeeta Das
Source: Gyana

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