In just a few years, it will be practically impossible to find a single industry left unaffected by the meteoric rise of Artificial Intelligence.
This disruptive blend of computer science, statistical models, and reasoning with big data is propelling the Fourth Industrial Revolution forward and changing core industries like agriculture, energy and healthcare while also hinting at solutions to a range of modern challenges.
But how is the world of retail using AI to transform the in-store environment to offer superior experiences and achieve higher revenues?
Three Key Challenges for Retail
Each day, millions of dollars are spent by customers around the world in brick-and-mortar retail locations. This dynamic is, of course, being challenged by the rise of e-commerce: in 2017 alone, 1.6 billion shoppers purchased goods online.
Retail locations have three key challenges that must be resolved to level the playing field.
Firstly, retail stores must successfully capitalize on the physical locations they own to give consumers new, fun and innovative experiences. The real-world location of retail stores is a big advantage, given the preference some consumers demonstrate for real-world experiences, where they can feel and fit products.
Secondly, retail stores have to improve at blending the digital and physical worlds to offer seamless, frictionless experiences to consumers. People expect to be able to shop within multiple channels, at anytime and anywhere.
Finally, retail stores have to compete when it comes to data. E-commerce stores can collect swathes of business-critical data about consumers and their habits, while many physical locations fail to glean the proper insights from in-person customers.
How AI Can Help
Will retail stores succeed in conquering those challenges? Their best chance is through the deployment of AI technologies. There are a range of intriguing and promising AI projects in the works, all the way from humanoid robots to no-checkout stores.
At the forefront of this surge in AI technologies, we take a closer look at tools that create new shopping experiences for retail stores to engage and inspire their customers, while boosting their sales.
Snap to Shop
This tool allows shoppers to upload an image of an item they wish to buy, for example an outfit they like the look of, or a piece of furniture. With computer vision algorithms, the image is parsed into shop-able items and a recommendation system serves up a range of similar products within the retail store. This is a powerful opportunity for retail stores to personalize the shopping experience and offer products that really resonate with customers.
Complete the Look
Using this tool, customers can upload an image of an item they want to complement, for example a person already has a nice blouse, but they are looking to create the full outfit. The system will then find products, e.g., matching pants, shoes and accessories in the store that go well with the initial item. This helps retailers to increase the basket size of consumers while also inspiring cross-selling.
A consumer insights tool is capable of conducting rich demographic analysis while also complying with GDPR and respecting the privacy of your visitors.
This anonymized information can be used by stores to create a range of useful insights that can drive informed business decisions. For example, you will be able to answer questions like: What are the age and gender distributions of the people that visit the store? How do these demographics compare between different stores? What is the sentiment of shoppers throughout the store? Where do people spend more time, and where are the dead zones? This helps stores to optimize the shopping experience.
Getting Started with AI
For some retail stores, getting started with AI can seem like an impossible task. This is not the case, though, and the longer those businesses wait the longer they miss out on exciting opportunities that could help their business to thrive in the digital age.
While each store is unique, there is a common path that stores can take to AI success.
Identify the Challenge
To get started, it’s important that stores begin by evaluating the specific needs that they have. This can be done by taking a detailed look at the business and how customers currently interact with the store.
If a store finds, for example, that it is failing to encourage shoppers to interact with stock, it can begin to strategize on how this can be resolved. Perhaps a new piece of in-store technology – alongside a marketing push – will be able to help the store to have shoppers explore inventory in more depth.
Decide on Sourcing
Once the need has been accurately identified, it is time for the store to begin thinking about how the AI technology will be sourced. There are two options here: choosing a provider or developing the technology in-house.
Many stores will, naturally, not have the capacities to produce in-house AI systems. If this is the case, however, this option means that stores can produce a tool that fits specifically to its direct needs. Control over the system also means that it can be tweaked and adjusted on the fly.
When it comes to choosing a provider, stores have more options available than ever before. Stores that choose this path will work with a professional partner and have a sophisticated system that can be installed to boost results. Many providers will provide analytics and interfaces that are easy to understand, boosting the value of the AI system.
Launch the Pilot
After identifying a provider, it is time for the store to launch a pilot. This short test period will help to smoothly implement the technology, verifying its efficacy and how the system itself functions. H&M, for example, is currently trialing a smart mirror that suggests outfits for customers… and the results are looking promising so far.
If the store chose to work with a provider, this pilot can act as a trial phase and the working relationship can be developed further. Based on the results of the pilot phase, a series of adjustments can be made.
An Exciting Future Awaits
As our common understanding of AI continues to improve and the various tools and technologies mature, transformative opportunities await sellers.
Retailers share this belief too: findings from Juniper Research suggest that in retail, global spending on AI will leap from $2 billion in 2018 to an estimated $7.3 billion a year by 2022.
The future looks bright and if current performance is any indication, that investment is a smart one.
About Susana Zoghbi
Susana Zoghbi, Co-Founder & CEO, Macty
Susana is a researcher and entrepreneur in a quest to help businesses grow with Artificial Intelligence. She received a PhD in Computer Science and her research focused on cross-modal processing of textual and visual Information. She designed deep neural network architectures and probabilistic graphical models to understand visual and textual content from e-commerce and social media.
Her work has been published in top conferences and journals in Artificial Intelligence. She has worked for NASA as a Deep Learning Researcher to automatically search for long-period comets that might impact Earth. She has also worked for Microsoft Research in Cambridge, where she focused on machine learning for optimizing environments for large scale software development. Before her PhD, she obtained two Masters degrees, one in Mechanical Engineering from the University of British Columbia, where her research focused on human-robot interaction technologies, and one in Mathematical Physics, where she focused on gravitational fluctuations in Domain Wall Spacetimes. In 2014, she was granted a Google Anita Borg award for her contributions in Computer Science and her community.
Follow Susana @susanazog
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