Well, that’s where the disruptions are happening thanks to artificial intelligence (AI).
It has completely transformed the way we handle our retail experience – both from a customer’s perspective as well from a business standpoint.
Artificial Intelligence creates an opportunity for retailers to bridge the gap between virtual and physical sales channels.
Brands are progressively using Artificial Intelligence to reduce cost, improve efficiency, achieve operational agility and increase the speed of decision making in the retail world.
According to IBM’s recent study, AI-driven intelligent automation in the retail and consumer products industries is projected to leap from 40 percent of companies today to more than 80 percent in the next three years.
That’s a significant leap and a major reason why retail businesses are jumping to create AI-driven strategies.
It’s a great time to be a data scientist in retail – and in this article, we’ll see 10 exciting real-world applications of how AI is transforming the retail sector around the world.
If you’re new to AI and want to understand how it works, how it’s disrupting multiple industries and how it might impact your role, you should check out the below certified program: Introductory Data Science for Business Managers Here are 10 Exciting Applications of AI in Retail: McDonald’s Drive Through Smart Voice Assistant H&M’s Assortment Planning using Artificial Intelligence Pepper Robots, The New Choice of Nestlé to Sell Coffee Machines Boch Automotive’s Artificial Intelligence Powered Sales Assistant Mango and Vodafone’s Smart Digital Dressing Room 53 Degrees North Applying Automated AI to the Process of Customer Segmentation Domino’s Pizza-Lovers Now Get Hot Piping Pizza Delivered By a Pizza Robot Nestlé’s AI Skill That Provides Voice Cooking Instructions As You Cook Walmart Deploys Robots To Scan Shelves Olay To Use AI To Personalize Skincare Note: The numbers mentioned in this article were taken until November 2019.
Given the rapid advancement in technology and businesses expanding accordingly, this will keep changing.
McDonald’s Drive-Through Smart Voice Assistant One of the world’s favorite restaurants moved quickly to transition into the AI era.
The top folks at McDonald’s have done impressively well to stay on top of the latest trends over the last few decades and their recent move indicates they are not relenting any time soon.
One of the things I’ve found a bit tedious is the drive-through line, especially in the evening.
I’m sure most of you have gone through this and sketched out your own plan to improve the waiting time.
Well, artificial intelligence has solved that for us!.Our favorite burger chain has installed a voice-based platform for complex, multilingual, multi-accent and multi-item conversational ordering.
It recently acquired an artificial intelligence company called Apprente, which has built this platform for them.
Don’t you love the power of Natural Language Processing (NLP)?.Think about it – the need for a smart voice assistant in this drive-through was quite obvious considering the time each customer typically takes to place a single order.
This makes the process of ordering faster and is cost-efficient as well – a win-win.
This technology is “sound-to-meaning,” in contrast to “speech-to-text.
” Basically, the system does not transcribe what the customer says and then infer its meaning from that transcript.
It goes directly from speech signals to result.
The company believes this provides a better approach for customer-experience related use cases, particularly in noisy environments such as restaurants and public areas or in cases where customers tend to use colloquial, poorly structured language, resulting in low-accuracy speech recognition.
Now we will be talking to a robot about McFlurries – how exciting!.How about building a speech-to-text-model in Python on your own machine?.Then here is an exciting tutorial to get you started: Build your Own Speech-to-Text Model using Python 2.
H&M’s Assortment Planning using Artificial Intelligence The role of an apparel store owner is quite intensive.
They have to plan for a new season and cautiously decide on what trends would the brand like to showcase to their customers.
How in the world do you forecast fashion trends?.One approach is to track the past trends per season and then factor in the new styles (or fads).
The brand can then make a decision based on these aspects.
That is proving to be a problem in today’s world as customers have a variety of tastes.
Social media has changed the meaning of fashion – and apparel outlets, even the biggest brands in the world, are struggling to keep up.
So taking into account historical data to make a decision on the current scenario may be an obsolete approach.
This, as you might have guessed already, is where AI comes in.
AI algorithms can predict the most relevant items to add to a retailer’s inventory by analyzing the product assortments of competing brands and comparing those products to the demographics and shopping history of that customer.
Big brands like H&M have realized the importance of using AI in their assortment planning.
H&M aims to forecast trends months in advance.
The retail giant is employing over 200 data scientists, analysts and engineers to use AI to review purchasing patterns of every item in each store.
The data incorporates all the information from five billion footfalls from last year to its stores and traction on its websites.
It also considers data from external sources.
H&M is breaking the stereotype with a one-size-fits-all merchandising approach to its 4,958 stores all over the world.
Here are its benefits: The localization of inventory will suit the needs of its clients in every geographic area Sharp data insights will help the brand eliminate bad product cycles With RFID tech to its stores, there will be an improvement in its supply chain process We know the industry is undergoing a huge shift – the catalyst for this transformation is technology.
It’s not just one technology, but a set that includes artificial intelligence (AI), augmented reality (AR), robotics and more.
” – CEO Karl-Johan Persson, H&M Soon, you and I will have the latest-in collection with the convenience of fast delivery by our most favorite apparel brand!.I am sure this will multiply your visits to the store and tempt you to shop more and more.
A similar concept called Market Basket Analysis is a must-know if you’re a data scientist in the retail world.
Check out how it works in Excel: Effective Cross-Selling using Market Basket Analysis 3.
Pepper Robot – Nestlé’s Solution for Selling to sell coffee Machines.
I was raised in the southern part of India and coffee is literally my ‘hot’ favorite.
I get spoilt for choice when I visit specialty coffee stores but often get disappointed when I find no one around to assist me in buying the best machine to brew my coffee.
Don’t you wish you had a robot coffee buddy who could guide you to buy the best coffee machine by understanding your needs?.Here’s the good news – this is now happening thanks to AI!.Take a look at the concept in the below video: Nestlé Japan is using a humanoid robot to sell its coffee machines built by SoftBank Robotics.
It’s one of the first robots in the world that can sense and respond by feeling human emotions.
Its equipped with the latest voice and emotion recognition technology.
And the best part is it can respond by understanding human facial expressions!.Pepper will be able to explain Nescafé products and services and engage in conversation with consumers.
” – Kohzoh Takaoka, President, and CEO of Nestlé Japan Starting your day with the perfect aromatic blend of your favorite coffee brewed just right is the most heavenly feeling in the world.
I am looking forward to talking with a humanoid coffee robot soon!.As mentioned above, this robot can read facial expressions and as a data science professional if you want to learn Facial Expression Recognition hands-on then here is an article for it.
Boch Automotive’s Artificial Intelligence-Powered Sales Assistant Every car dealership enhances its bottom-line via after-sales service.
Given the current dire state, the automotive industry finds itself in right now, a dealership’s very existence might depend on this.
So how do they make sure that customers are engaged successfully to drive this revenue?.Not only is the service revenue important, but this engagement will also increase the chances that their customers will make the next car purchase with the same dealership (or recommend it to others).
But anyone who has worked in the sales field knows that engaging customers is a tricky challenge task.
It takes time, effort and close monitoring and that’s a massive task with a service team when there are thousands of customers to work on.
Boch Automotive, an England based car dealership company, has adopted a unique AI software that streamlines its sales funnel and establishes an automated sales assistant to increase service revenue via engagements.
Conversica “sales assistant” software is designed to automate and enhance sales processes by identifying and conversing with internet leads.
The sales lead and management company claims that authentic-sounding messages result in an average engagement rate of 35%.
That is quite a big number!. More details