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Using Data to Transform Physical Retail with Eunice Wong, CEO and Co-Founder of Milky Way AI

Wong-Featured

Data can obviously be immensely powerful in eCommerce — but what about physical retail? As it turns out, having retail data analytics is proving to be a real competitive advantage for many brands: transforming their fortunes by giving them a glimpse of what their customers like, dislike, and how they go about their in-store shopping journeys. We spoke with Eunice Wong, Co-founder of the artificial intelligence startup, Milky Way AI, to get her perspective on the way data is changing the perspective of traditional retailers.

Eunice Wong | Interview

Eunice’s background is a mix of product, marketing, sales and operations. She started her career working in Microsoft marketing enterprise software, learning how marketing funnels are scientific. In 2014, Eunice became dunnhumby’s Global eCommerce Director — it was here that she learned about the power of customer data science (how Amazon and Netflix rely heavily on product recommenders for sales conversion) and why omnichannel experiences are so valuable. She noticed that while online retailers and brands have the tools to track and personalise in real-time and at scale, there are few solutions for the physical retail sector.

In August 2019, she founded Milky Way AI, an artificial intelligence Startup with a mission to transform physical retail, leveraging computer vision to digitize the store

Tell us about Milky Way AI

Our mission is to bring eCommerce-level insights into the physical world: tracking items on a shelf and using this information to determine customers’ browsing habits. We want to give retailers real-time data on what’s actually happening in their stores. Today, retailers and brands are spending hundreds of millions of dollars having their workforce manually eyeballing shelves to ensure that products are well merchandised on store shelves but with our technology, they’ll be able to automate the entire process.

I used to travel 100km a day to audit stores, that was time consuming and low value added. What takes humans hours can be done in seconds with computer vision.

What is your vision of the future of retail? 

Customers want you to meet them wherever they are, both online and offline. The whole experience should be seamless, connected, user-friendly, and personalised. Retailers can only do this at scale if they have the right tools to collect customer data and to surface personalized content.

I foresee more retailers digitizing the physical experience. Take Amazon Go for example: it’s branded as an “autonomous checkout” but it is actually so much more than just removing queues at checkout. They can now identify you as a shopper when you check-in and surface personalised content based on your historical purchases and preferences. 

And of course, not all data is equal. How do you use the data at your disposal and what should you actually be focusing on? For example, in fashion, your browsing history is generally more important than your purchase history — whereas your grocery shops are incredibly habitual. You often end up buying the same things week in, week out, so companies can quickly understand what type of shopper you are (and the things that you’re interested in) before personalising your entire consumer experience to suit these preferences. The key is to have frictionless, human, and genuinely meaningful communications with customers at scale.

What have you learned from starting your own company? 

It’s funny, everyone seems to have an opinion on what you should do: VCs, investors, customers, and even your Mum! I sometimes find it hard to drown out all the noise — you obviously don’t want to ignore great advice, but you also want (and need) to follow your own intuition and only take advice from people who have skin in the game. 

We’re in a great era where anyone can be an entrepreneur… You just have to get started. You need to have a growth mindset as you have to wear many hats and be comfortable with uncertainties. You have to be deeply connected to the problem that you are trying to solve, have empathy for the users, hustle ( an overused word but everything is stacked against you as a startup so you got to be incredibly creative and resourceful) and of course fundraising. I am still learning and it is something most people do not have any experience in but is absolutely critical to success.

Massive Rocket Theory

Data in retail

A recent Jabil study found that 55% of retailers are planning on investing in data visualisation technology in the near future. But why is it so important? Well, among other things, physical retailers can use data analytics for the following purposes:

  1. Measuring traffic flow and identifying the store’s busiest areas (by installing in-store beacons).
  2. Using these insights to guide the store’s physical layout.
  3. Stock management — identifying which warehouses need more stock, when, and in what quantities.
  4. Analysing product sales: guiding procurement decisions going forward.

And that’s not all. For example, this Capgemini report discusses the potential utility of combining in-store data analytics with an app: allowing consumers to see whether or not their desired products are in stock, where they’re located, and more.

We’re not saying that data analytics will help physical retail defy the rise of eCommerce going forward (it’s expected that the amount of revenue brought in by eCommerce will overtake that of physical retail in just four years). However, it can certainly go a long way to providing a better customer experience. After all, shouldn’t that always be the end goal?

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