How Retailers Can Leverage Big Data and AI During a Recession
From the current political climate to the looming economic recession that experts are expecting to draw close, there has never been a more vital time than now for retailers to future-proof their business.
How the economic recession affects retailers
During an economic recession, consumption for discretionary goods decrease, and these companies suffer because of the decline in profits. In an effort to improve the bottom line, companies cut back on unnecessary expenses like filing headcount and on creating new product line items entirely. With declining revenue, stock prices in publicly-traded companies falter, shareholders become upset, and the cycle continues with consumers tightly watching their pocketbook.
There is no doubt that an economic recession is bad for companies all across the world, from small to big. With retailers and brands already struggling to overcome the sluggish sales they’ve been seeing the past few years, analysts note that with this oncoming recession, the gap between industry winners and losers will only widen. As stated by Neil Saunders, a managing director of GlobalDataRetail,
The retailers that are doing well are seeing great returns, while the weaker ones are being left behind. The real concern is: What happens if the economy slows down? Polarization is going to become even more of an issue.
According to UBS analysts, the retail apocalypse has been showing no signs of slowing down, as 75,000 retail stores selling clothing, electronics, and furniture are expected to close by 2026. Based on their findings, about 16 percent of sales are made online, with 25 percent of retail sales made up of online shopping.
Chain of Demand and Fasta.AI – a conversation tool that helps pick up social trends – partnered for a night of conversation at R-One Space recently in Hong Kong to share how artificial intelligence can be used to mitigate risk during a recession.
For Chain of Demand, this means leveraging an in-season predictive model, a tool that helps forecast sales and allowing retailers to react more quickly with data-driven recommendations. CEO and Founder, AJ Mak shares,
The retail business is already tough enough as it is – it’s critical to not look solely at historical sales as a forecast. There’s a wealth of information out there that can minimize losses during a recession.
With the in-season model, Chain of Demand is able to recommend a reallocation strategy for inventory so that merchandise is cleared through at full-price in high-performing stores. During a recession, it’s imperative to be even more strategic with your inventory dollars.
Using AI-powered conversation analytics
Another interesting way for retailers to leverage artificial intelligence to stay ahead and cater to their consumer needs is diving into social conversation deeper. Fasta.AI was able to share how retailers can use to make sense of the trends within social data.
By analyzing various relevant social media conversations, the company’s proprietary machine learning models identify and predict emerging trends three months earlier. Categorizing millions of online conversations will allow retailers to discover insights about their customers that they would otherwise have to guess or assume.
The Case with Pepsico
A great example of this at work was with the company Pepsico, where they were able to leverage social data to design a drink that exceeded $100 million USD in sales within 12 months of launch, beating the competition by getting to the market first They did this by turning to Black Swan Data to analyze consumer conversations at large scale to better understand what their customers truly wanted. Their specific aim was to identify opportunities within the community of sparkling water lovers.
Digging through 157 million real-time beverage conversations from online sources, and cleaning though the rubbish content (spam, advertising, bots, etc.), they ended up applying AI and natural language processing.
For Fasta.AI, they were also able to analyze data from LIHK (連登), a Hong Kong-based Reddit-like forum and identified many F&B retailers within Hong Kong that were currently running $20 promotions to entice customers to spend on a combination of foods like fishballs and ice cream.
From their findings, Fasta.AI realized that $20 was the magical spot where consumers were willing to spend not too much of their money, while shop owners could still make a profit. Shops found that setting the price at $10 too low to draw a profit and $50 too much for the average consumer.
Through all these examples, Sam Ho, Founder of Fasta.AI sees the opportunities can be leveraged with social conversation,
Social conversation can be a powerful way to gain a first movers advantage. Analyzing what’s being said will allow you to forecast emerging trends and discover unknown topics for the masses.
In places like Hong Kong, retailers have been getting hit hard, with revenues declining, profits dropping, and opportunities falling by the wayside. Thus, learning how to pay closer attention to social trends, as well as receiving more accurate recommendations on what are your best and worst sellers can definitely help to not only survive, but thrive.
Whether it be looking at social prediction solutions like Fasta.AI, or machine learning-driven predictive analytics of Chain of Demand, the only way to do more in these tumultuous times is to make the most with the data you have. With an open mind to embrace the unknown, retailers can empower themselves to produce better results and come out of these economic downturns with their heads held high.