4 Benefits of Artificial Intelligence (AI) in Retail for 2020


4 Benefits of Artificial Intelligence (AI) in Retail for 2020

It is estimated that there are about 2 million fashion brands in the world – and growing. The retail industry is growing at an incredible pace and customers are finding themselves increasingly spoiled for choice. The flip side – brand loyalty and recall is dropping fast.

Customers are increasingly paring down their shopping to brands that connect with them, brands that offer personalized experiences, and talk to them on the channels that they are using.

Why every retailer should adapt to AI?

The new generation of shoppers, the millennials, expect bespoke shopping experiences in real-time and at the lowest price. They expect the retailer to know them as well as their local grocer used to. They don’t want to be flooded with thousands of irrelevant products. Instead, they want shorter wait times, quicker order fulfilment, personalized product recommendations & frictionless checkout experiences. This new generation was brought up in a digital world where they can find multiple options with a click of a button. They are used to Amazon’s seamless shopping experience. This means retailers today have to adapt AI to survive.

Research shows that when shopping experience is highly personalized, customers indicated that they were 110% more likely to add additional items to their baskets & 40% more likely to spend more than they had planned.

It is also increasingly clear that while retail is not exactly dead, it is undergoing a metamorphosis. There is still value in the offline. In fact, Doug Stephens, The Retail Prophet points out that stores need to see themselves as an extension of their media platform.

Are you on the right channel, at the right time?

The use case for the store is now to deliver a high level of experience – sensory and emotional in a way that is memorable and trust-building. But online is where sales are moving.

Approximately $5T of the $28T retail market is now online.

Retailers are finding their biggest competitors online. Social media platforms like Netflix, Instagram, Snapchat, and the likes have achieved the level of individualization and experiential content needed for a platform to become habit-forming – something that retail has fallen behind on. Shopping too is moving to these platforms.

And a large amount of this shopping is being driven by millennials and Gen Z.

It is easy to spot an item of interest on a platform, get recommendations, and opinions from friends and family, purchase the item of choice all within the same app and have the entire experience be tailored to the individual.

The data challenge

A presence online is not going to solve retail’s problems completely. Retail’s bigger issue is the lack of accurate data. Even the data that is available ends up being used ineffectively or in a way that doesn’t provide a singular view into the customer across channels.

Consider this – bad data has cost US businesses $3.1T every year, & data workers waste 50% of their time finding and correcting errors.

The challenge for brands in this atmosphere is two-fold:page5image3906263520
1. Know the customer well.
2. Use the customer data and build operational efficiency into their systems.

Accurate data can bring optimization, automation, and competence. And the best way to use data to bring about this hyper-personalized experience is through Artificial Intelligence.

AI in Retail 2020

AI is retail’s superpower. Retail is, in fact, one of the few industries where adoption of Artificial Intelligence(AI) is being seen in a meaningful and actionable manner. Every step of the retail process has the ability to be automated in a way that would increase accuracy, efficiency, and scaling of operations. From customer acquisition using reliable data to catalog and inventory management to post-purchase experience – AI has the ability to impact retail in a holistic end-to-end manner.

AI in Retail 2020

Benefits of Artificial Intelligence (AI) in Retail for 2020

1. Automated Product Tagging

One critical area where the use of AI has a big impact – Automated product tagging. Vue.ai uses machine learning to understand the taxonomy of an outfit, train the machine using our neural networks which it then uses to generate tags.

Automated product tagging makes it easier for catalog managers to curate inventory, which helps in understanding merchandise better, and pushing it out faster. It gives more accurate attributes for products and helps in better search results.

Customers are far more likely to find exact matches and are less likely to abandon carts. Result?

Image recognition driven product digitization produces above 90% accuracy and a more than 20% conversion through better search, browse and SEO.

Frequently Faced Challenges with Product Tagging - AI in Retail

 2. Visual Merchandising

Size visualization is another sector where retailers can benefit by using AI.

Retailers across the globe spend approximately $100 – $1000 per product on photography and digitization.

The high cost of the visual merchandising manually also means the merchandise is more likely to be non-inclusive and fails to give an accurate picture of the product. The time-to-market is also prohibitively slow and expensive.

Vue.ai’s Human Model Generator helps retailers by enabling them to show the same product in a more inclusive manner. An image of a dress or bag can be shown on various sizes, ethnicities, and ways to ensure the customer gets a more comprehensive view of the outfit.

3. Dynamic Personalization of the Shopper Journey in Real-time

No two shoppers have the same journey. With dynamic personalization, understand shopper intent with each click and serve personalized product recommendations with the highest likelihood of engagement.

Enable visual style, brand, price, and category personalization with every click and keep your shoppers hooked across their journey.

Dynamic Personalization in Fashion Retail Ecommerce
Dynamic Personalization in Fashion Retail Ecommerce

4. Personalized Curation

Shoppers in 2020 don’t want page after page of irrelevant products. Instead, they are looking for unique collections curated specifically with their tastes in mind.

They expect stylists to personalize the whole look according to their own style profile. However, personalizing hundreds of looks for each shopper will need a whole army of stylists toiling away for days.

An AI styling assistant can curate looks, mood boards, outfits, and collections for each shopper based on their visual style preferences. Each shopper gets personalized styling recommendations for every product they browse, increasing the number of items in the cart while at the same time giving a great experience to the shopper.

Conclusion

AI and Automation can help retail teams across the globe improve efficiencies across their workflows. Automation processes help brands with accurate data creation and help provide context around shoppers’ needs and behaviours.

By getting access to this accurate data and using it across personalization, styling, and customized marketing, brands can leverage this information to curate experiences that are meaningful and valuable to the shopper.

Today, intelligent retail automation is about leveraging the power of data. The amount of data that needs to be processed from even a single shopper with several touchpoints across multiple channels makes automation a necessity, not a luxury. Failure to automate can even lead to retailers missing out on capturing data completely. And in a data-driven economy, this can have dire consequences.

There is a constant need to create, use, analyze and distribute data in a timely manner for instant contextual decision making and value creation. This can only be done with automated systems capturing data across different touchpoints and channels.

Retailers today not only need automation to capture data across touchpoints and channels but also need to unify this data to speak in a single voice to the shopper. A shopper should be able to transition seamlessly from online to offline and back online again. This means, the data captured on a website should be available to the sales assistants in-store and the products bought by a customer in-store should be used to improve the recommendations on the website. Data cannot be isolated in silos. It needs to flow both ways and help provide a complete story about each shopper.

With the power of data, intelligent retail automation can completely transform how retail teams function. Automation can completely take care of efficiency, giving retail teams time to think creatively and provide incredible experiences both online and in-store.

When retail truly becomes efficient and experiential, customers can enjoy the thrill and the magic of shopping anywhere, anytime.

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