What role will the new technologies play in retail processes? What innovations are already being deployed by leading companies that will be retail game-changers over the next years?
We’ll dive into the latest retail innovations in the 4 main aspects that concern a retail company:
- Sales and CRM Applications
- Customized experiences
- Manufacturing
- Logistics and Delivery
Sales and CRM Applications
THE FUTURE BRAND will have human-like robots at your service in every channel you can think off
Trend: AI robots that replace humans in customer service (ex. Domino’s chatbot for deliveries) or sales functions (ex. sales assistant).
Technology: AI powered robots or chatbots that use technology of voice recognition and visual recognition to interact, understand human emotions and imitate the natural language.
Results:
- Virtual assistant chatbots: automatization of tasks leading to cost savings and enhance operation processes.
- In-store robots: boost store interest, increase engagement, get better data in real time and increase sales.
Case: Pepper Robot, Japan’s SoftBank
Introducing Pepper: a humanoid robot that interacts with customers and is pretty popular among them.
The SoftBank robotics partnered with Aldebaran, a French robotic manufacturer, to develop Pepper. “He” can perceive human emotions and was used as a customer service greeter and representative in 140 SoftBank mobile stores in Japan, and then traveled all the way to California. According to Softbanks Robotics America, a pilot of the Pepper in California’s beta stores in both Palo Alto and Santa Monica yielded a 70% increase in foot traffic in Palo Alto, and 50% of Neo-pen sales in Santa Monica were attributed to Pepper.
Pepper robot has increasing popularity and his positive response has attracted companies like ATB Financial and Nestle to use Pepper as an in-store sales assistant.
Customized experiences
THE FUTURE BRAND will provide targeted experiences that highlight brands understanding of individual consumers
- Trend: Use of segmentation and recommendation models for tailored suggestions and personalized offers based on each consumer’s specific wants and needs.
- Technology: ML/AI powered pattern recognition for a) customer segmentation and recommendation models. Segment modeling technology is used to find patterns of customer segments with similar behaviors using CRM data, this allows for potentially useful “clustering” at scale.
- Results: improved commercial intelligence for better attribution on marketing spend, to increase conversion rates, sales, and average expenditure per client. To provide a better customer experience through personalization.
“It’s not something that retailers can let slip, especially as companies such as Netflix and Spotify continue to hone their skills when it comes to individualized recommendations and playlists. Once consumers taste what can be, they expect other businesses to deliver the same treatment.” — Susan Reda, Editor of STORES Media, the National Retail Federation’s magazine, explained this in her overview of “What’s in store for 2018”
Case: Stitchfix, a new whole new business model
Stitchfix is a personal styling concept that uses an algorithm to deliver personalized packages of pre-assorted, curated clothing deliveries for men and women, on a monthly basis. Their pitch? “The netflix of clothing”.
How does it works basically? You will provide personal information that relates to your size, fit, personal taste, price preference and demographic data, and in exchange, an algorithm uses this data to curate cloth for you better than any fashion assistant will. Once customers receive the package, they will choose the items they like and and send the rest back, paying only for the once they chose. This feedback is analyzed to improve the customer experience and make more accurate predictions.
Stitchfix has already over one billion USD revenue run rate, positive EBITDA, 2.2 million active customers and went public with and IPO raising $120 Million (nov 2017). But really, the KPI that’s more interesting for their business model is the repeat purchase, which they have a 86% rate. This means basically, they are getting it. Stitchfix is growing at a year-over-year 31% rate. It seems that this new business model has introduced a whole new concept that will soon be known as the Stitch Fix fashion experience.
Case: Northface’s conversational interface
North Face launched a landing page that uses IBM’s technology Watson to recommend customers the best options of jackets to purchase based on the place, season, and activity they are performing.
The conversational interface uses a minimum of variables that wouldn’t require necessarily machine learning powered system to give a recommendation. Nevertheless, the advantage of using ML is that through the customers interactions, North Face is gathering a huge volume of data that will then allow them to get insights and recognize patterns of purchase that will allow the company to make future decisions to increase their conversion rate.
Manufacturing
THE FUTURE BRAND will be able to manufacture at large scale on-demand personalized products with features that respond to each consumers specific needs
- Trend: Mass production of 3D printed personalized products
- Technology deployed: 3D printers
- Results: personalization and customization of on demand products
Case : Adidas 3D Printing sneakers
A technology company named Carbon partnered with Adidas and together they are revolutionizing the way the world makes 3D printed items. Why? Because they are mass producing the items and they’re the firsts to do it in the shoes industry.
The Futurecraft 4D sneaker — how they are calling it — allows the design and production of customized, high-performance shoes that meet the unique needs of each client.
Logistics and Delivery
THE FUTURE BRAND will have your order ready before you even place your purchase and will deliver your products or goods in no time
- Trend: Anticipatory logistics, autonomous delivery of goods and food rolled out at scale (within the next decade) and optimization of delivery routes.
- Regulations: There are still air regulations that need to adapt in each country for this solution to be deployed at scale but pilots are determining the safety and reliability of this technology to make it viable.
- Technology deployed: Robotics and drones for autonomous delivery, anticipatory logistics based on predictive algorithms running on big data to predict demand before a consumer places an order, and machine learning algorithms to find and navigate optimized travel routes.
- Results: cost reduction, time efficiency, enhanced customer experience.
Case: Domino’s Robotic Unit (DRU)
Domino’s is really embracing the power of AI to save costs and deliver better customer experiences. In this case, they have created a prototype delivery robot that relies on sensors to navigate the best path for delivery and in the meantime, keeps the food and drinks at the appropriate temperature. See it yourself:
Case: Amazon’s Anticipatory Shipping
What happens when you combine artificial intelligence, machine learning, big data, GPS, payments and voice? You get, indeed, anticipatory shipping. So basically, it works like this: Amazon will ship products to consumers before they even order them.
For now, Amazon is using the patent to send the items to a shipment hub to cut down fulfillment times of popular items. Though, they are testing a pilot with “Amazon prime wardrobe” where they use the predictive analysis technology to send clothes directly to customers without them asking. They leave a box at your doorstep. If you like it, you keep it. If you don’t, you send it back. Will it work? We’ll have to see about that, but we can at least agree that this cutting-edge patent will shake up regular logistics processes.
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Sources:
- https://www.techemergence.com/artificial-intelligence-retail/
- https://www.shopify.com/retail/retail-trends-2018
- https://hackernoon.com/five-interesting-points-from-stich-fix-ipo-prospectus-915d8008d10e
- Anticipatory Shipping — Why Amazon Will Disrupt Supply Chain. https://youtu.be/JhAlW_DCYxk
- https://www.smartdatacollective.com/amazon-wants-predictive-analytics-offer-anticipatory-shipping/
