9 Innovative AI Use Cases in Retail

Nine innovative use cases of AI in retail to show you where the opportunities lie.

Nikole Wintermeier | Jun 19, 2019

Future of retail is AI blade runner

You’re running a retail store in an age of digital disruption and competing with innovative future technologies like Artificial Intelligence.

You are pitted against behemoth retail stores like Amazon who maximizes on customer intelligence. The 4th industrial revolution (or so they are calling it) is everywhere you look:

Artificial intelligence, cryptocurrency, the internet of things (IoT), the Black Mirror shoppers carry in their pockets wherever they go….

Your customers are growing digitally literate and more and more emancipated. They require immediacy, trust, and gratification from omnichannel shopping experiences.

The customer is always right’ has now shifted to the customer is both right and empowered.

So what’s the good news?

The digitized economy of experiences is growing at an exponential rate:

  • Accenture reports that investment in AI and Human-Machine collaboration could boost retail store revenues by 38% by 2022!

Moreover, 72% of retail stores said that intelligent technology will be critical to their organizations’ market differentiation. And it is predicted that AI will add 16 trillion dollars to worldwide GDP by 2030.

So, how do you gain a competitive advantage in the Future of Retail?

Answer: With AI and Customer Intelligence.

This article will chart how AI is already functioning within the retail landscape and posit that customer intelligence along with AI are key components to gaining a competitive advantage.


Leveraging AI in Retail Stores

Firstly, how is AI functioning in physical stores (or: brick and mortar)?

Frankly, it’s function is prolific.

Here are two extreme (but very cool) examples to understand the physical market that you’re dealing with.


1. Bring AI in-store: Amazon 

Amazon is Moving to Brick and Mortar, and They’re Bringing AI With Them

Amazon has just launched ‘Go,’ a supermarket without check-outs, cashiers, or lines.

The ‘just walk out technology’ uses AI to observe what product you choose before - nonchalantly and not feeling criminal at all - you just walk out of the store.

Amazon leveraging AI

Did you know? Amazon accounts for 44% of all US eCommerce sales.

No surprise since they are using AI to innovate and obsess over the customer by reducing the psychological stress of shopping.



2. Leveraging Psychology in Retail: eBay

During this eBay-Saatchi experiment, machines were used to analyze the subconscious of shoppers and determine what products they (or their neurons) responded to best. The items were then added to their virtual shopping carts, and voila!

The first subconscious shopping experience!

"Shopping has always been intensely personal [...] It's an expression of what makes you, you." (Julia Hutton-Potts, Director of Communications, eBay)


3. IKEA uses AR to improve shopping experience

IKEA’s augmented reality app ‘Place’ allows customers to visualize how IKEA furniture fits into their household spaces. IKEA boasts over 817 million customers per year, and is one of the "most loved companies worlwide". 

IKEA Place app AR


But you don’t have to budget for VR or new apps, you just have to close the gap between retailer and shopper and bring your products closer to home.

And this can be done by coupling consumer psychology with business strategy.


What about AI in Online Retail?

The same digital transformation that’s happening in-stores is, of course - and even more meaningfully - happening online. Let’s have a look at some examples...


4. House of Cards learns from Big Data

House of Cards using AI

Ever watched House of Cards?

If you did, you probably liked it.

That’s because Netflix used AI-powered pattern learning to analyze vast amounts of customer data to predict what show people would enjoy.

They then hired people to write what would become the award-winning political drama  that is House of Cards.

AI for predicting purchase patterns, AI assistants, chatbots, recommendation engines, warehouse automation, algorithms that drive internal and customer service operations - these are just part in parcel of a host of other use cases for AI in eCommerce.


5. Pinterest uses data to create product matches

Pinterest recently introduced an updated chrome extension which allows users to search for any product online through an image.

This means that if you stumble across a picture of a man wearing a cowboy hat and denims and you think, “cool jeans!”, you can now hover over the jeans and Pinterest’s “visual search” technology will let you browse similar products by the same retail store.

Same applies for the cowboy hat, if that’s your thing.

Pinterest AR for product recognition[Although it may not be perfect because I’m fairly sure that Professor McGonagall is wearing a witch’s hat... but we’ll get to her later.]


6. eBay's Shopbot provides recommendations and advice

eBay’s Shopbot is using technology to engage with their customers by giving recommendations and advice.

This simplifies online purchase decisions for mobile phone users, giving them that one-on-one time with AI (basically a chatbot that you can communicate with through text, voice, and pictures).

  • Ubisend reports that 40% of consumers use chatbots to look for offers and deals.


7. Mitingo synthesizes data for profiles

The future of retail will rely on customer intelligence using AI. Because it's only with C.I., that brands can really learn to understand their customers.

We've already seen the pivot in other industries as they start to recognize this untapped opportunity. eCommerce will follow suit before we know it. 

Take Mitingo, for example, an AI-powered platform that synthesizes billions of customer data points.

Mintigo AI platform

Their mission is to place the ‘power of AI in your hands’ and implement AI across the whole business funnel for their partners.

Mitingo’s predictive lead scoring and data enrichment application enabled Red Hat to increase customer acquisition and conversion rates by offering personalized experiences gleaned from the data.


8. Leveraging AI for campaign management

Similar to Mintigo, Beabloo, who call their AI project Minerva - making me nostalgic for my Harry Potter childhood and Professor Mcgonagall.

Except their use of AI and machine learning is no magic.

Minerva AI platform

For Fira Barcelona they implemented a CMS for unified campaign management and an audience analytics dashboard which delivered relevant metrics for campaign planning.

They have also piloted a virtual assistant for brick and mortar - this one called Halo - and set up digital interactive kiosks in NBA stores in China for improved shopping experiences,

“integrating the advantages of online shopping into the offline world”[Beabloo: FYI, the blending of physical and digital is a marketing trend called “Phygital”]

9. Using AI to Generate Actionable Insights

At Crobox, we have used our AI to help brands like Dyson and Under Armour profile their webshop visitors based on behavioral data to serve them personalized product promotions.

We create psychographic data profiles that explain the psychological tendencies of shoppers or, in other words, why they respond to one message versus another.

“When explaining Crobox we say derived from behavioral psychology, optimized by AI. Our machine learning algorithms learn from the behavioral data of shoppers on a specific client’s platform.” (Janelle de Weerd, Marketing Manager at Crobox [read the full interview here] )

Crobox shopper profile DNA

It all boils down to this:

As humans, we thrive on personalized experiences. We need to be understood.

Therefore, as we’ve seen, psychology and the subconscious are becoming increasingly important for customer-centric approaches in retail, both online and offline.

For online retail, AI science provides contextual understanding, predictive modeling, and machine learning abilities that eCommerce stores are using to get closer to their customers, one-on-one.


Recommendations on How to Compete in the Future of Retail  

1. Adopt an AI-culture company wide

AI will enhance your digital platforms and existing analytics, allowing you to structure and integrate your data to deliver personalized customer experiences.

We therefore recommend scaling up eCommerce, business technology & development roles, as well as providing tech skills-trainings for all departments.

Invest in an enterprise-grade analytics solution, making sure a company wide AI-ambition is echoed across all departments.


2. Place the customer at the forefront of all business goals

What could be more important?

Harness the power of AI to analyze big data and use this to improve customer experience across all touchpoints.

This 360 customer engagement should be a mandate from C-level down, ensuring that machine learning for customer intelligence is implemented across all segments rather than operating in a silo.

I know you can do it.  


3. Invest in technology for mature data analytics

A mature analytics solution (and not just, for example, aggregated data) that identifies high-value segments can drive campaign strategies, channel mix, ad budgets, etc.

The future of retail will depend on these continuous learning tools and, in order to adapt, we strongly recommend using AI to enrich your data analytics model.

Therefore, allocate enough budget to get ahead of the curve.


4. Democratize the data

Empower the data experts within your company!

“Leveraging customer data to deliver hyper-relevant experiences takes a new level of marketing intelligence”[Salesforce]

The more digestible and unified these insights are, the better the 360 customer engagement across all channels

We therefore recommend equipping all departments with the tools, data, and insights to make smarter, more customer-centric business decisions.big data comic

Having this universal decision making engine will increase conversion rates, customer loyalty and retention, reduce churn, driving revenue and growth.

We all know: customers that stay are customers that pay.


Pivot your company priorities towards customer intelligence.

I can’t hammer this point in enough:

The Future of Retail is AI and Customer Intelligence.

Hey, that’s the title of this article! I guess I’ve made my point then...


Key Takeaways

Your customers have high expectations for every touchpoint they interact with. Technology can help make shopping easier, relevant, and more enjoyable.

You can now create authentic shopping experiences - maybe not to the extent of eBay, but still to an extent where you can empathize with shoppers using the data synthesized by AI and machine learning.

Bottom line?

  1. Retail is reorienting itself to encapsulate the customer (a customer who is more demanding and more self-aware)
  2. Consumer psychology is at the forefront of this reorientation
  3. Customer intelligence is the tool for 360 customer engagement and consumer psychology
  4. AI facilitates customer intelligence  

bladerunner image smile

With all these insights, I hope you understand how the future is, in fact, exciting and full of promise.

Good luck!

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