Artificial Intelligence in Retail: Does it Solve the Complexity?

IN Artificial Intelligence — 11 December, 2017

Once upon a time, retailing was relatively simple. Merchants selected an appropriate product range, bought them at the lowest possible price and at the right quantities, and sold them for a profit. Today, thanks to its global nature and disruptions to the market, retail is one of the most complex industries to trade in.

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Without AI in retail, big data gives little insight.

In response, there is endless commentary on the importance of retail big data, but this information alone holds marginal value. The true vehicle to agility is retail artificial intelligence.

So, why is today’s retail industry increasingly complex?

1. Stock expectations

There’s fierce competition in retail; businesses that fail to satisfy their customers will lose both reputation and market share. As customers’ shopping habits evolve, merchants must establish themselves as nimble and flexible organizations.

If your customers’ favorite items are regularly out of stock, gone are the days they will wait patiently for a later date. What’s more, a third of global consumers impulsively purchase clothing based on when they want something, in contrast with 12% of consumers who buy due to the latest season collections.

2. Personalization

Today, customers expect you to know what they want before they do, and sell it at a price that works for them. Consumers will only respond well to an advert or sales prompt if it’s targeted to their needs, presented at the appropriate moment, and in a location that is relevant.

3. Globalization

Ecommerce has made the world a more accessible marketplace. Consumers think little of shopping cross-border to find a quality product at a more affordable price, or to find an exotic brand. According to our research, nearly three quarters of online consumers researched for up to five hours a month.

4. Seasonal sales are less effective

With shoppers more strategic in their buying cycles, merchants must address their pricing models and stock levels accordingly.

Discounting, however, is not always the key to driving sales; the same research showed that almost 10% of global consumers mistrusted a brand’s quality if there were too many discounts available.

5. Too much data

Data is key to understanding consumers’ needs and expectations, but in isolation intricate information from each digital footprint is incredibly hard to manage. It is estimated that 80% of data stemming from the retail industry — from consumer, product, online and in-store sources — is not even considered for analysis.

Retailers face an enormous challenge managing the sheer volume, velocity and variability of retail big data without artificial intelligence.

What is the solution?

How can retailers understand their consumers’ needs better, when their volume of personal data is too complex to process?

Artificial intelligence turns big data into big insights. It looks at huge volumes of information and converts it into actionable decisions. It provides the ability to analyse granular data around stock color, size, and style, to determine product and pricing requirements.

“Fashion retailers need to optimize prices in a dynamic way to positively impact sales and ensure profitability at season’s end,” explains Matt Hopkins, vice-president of retail strategy development at Blue Yonder. Only intelligent technology can point retailers in the right direction, ensuring they make the right decisions to optimize their prices, locations, promotions, distribution, fulfilment and replenishment.

Price optimization solutions, like that offered by Blue Yonder, use AI in retail to measure the relationship between price changes and customer demand, while incorporating a retailer’s business strategy.

Download our white paper, Fashion's New Rules for Pricing for more trends and opinions in the global fashion market. The research will help you fine tune your retail pricing strategy, highlighting the value of retail artificial intelligence to differentiate your business.

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enables retailers to take a transformative approach to their core processes, automating complex decisions that deliver higher profits and customer value using artificial intelligence (AI).