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Back in 2014, Amazon launched predictive stocking, a move that truly demonstrated the advantages of artificial intelligence in retail. It was ahead of its time, heralded as “pure genius”. These days, savvy retailers are turning to an arsenal of AI-powered tools to enhance the customer experience.
Algorithms already influence so much of the human experience, so it makes sense that the AI revolution is sweeping through retail.
There are new applications of big data and machine learning, and retailers will have to evolve quickly to keep up.
But it’s a push the industry’s been waiting for - 91 percent of retail executives told IBM that cognitive computing would disrupt their organization. It’s why 94 percent of those same executives intend to invest in the tech stack required to deliver better customer experiences.
Next-generation retailers must turn to big data processing and machine-learning models using cognitive computing for retail advises McKinsey, and there are already test cases across industries.
Powered by machine learning, McDonald’s will store data about the products customers select and predict how these choices will influence future purchases, according to VOX. The digital menu displays will dynamically serve relevant meal recommendations to drive-through customers. The fast food chain certainly has enough data to learn from - it serves 68 million customers every day.
By leaning into this type of technology, retailers can boost demand forecasts, too. Demand forecasting has had a patchy record in retail, and there’s at least a 32 percent error rate.
That’s because there is a range of factors to consider. Relying solely on single indicators like sales, for instance, can paint an inaccurate picture. What if the reason your sales took a nosedive is because your business ran out of stock?
One of the major advantages of artificial intelligence is that applications crunch a diverse data set, drawing on metrics like historical sales figures and real-time analytics to better forecast demand and optimize pricing.
Humans can’t match that kind of processing power, writes CalculAI’s Prannoiy Chandran. Machine learning allows retailers to “identify patterns that humans and traditional forecasting tools would have missed”.
Beyond purchase patterns, AI can improve product recommendations. Personalized product recommendations will fuel bespoke customer experiences, predicts Deloitte:
“An algorithm-driven user interface can provide product recommendations based on assessments of consumers’ buying patterns and product preferences, making the shopping experience more relevant, enjoyable, and satisfying.”
It’s why AI-powered product recommendations increase sales, according to ZDNET. Leading retailers like Etsy are ploughing major investments into AI-tools that can deepen customer engagement. The online marketplace bought Blackbird Technologies to improve the discovery experience to match shoppers with more relevant products.
“...Leveraging Blackbird’s technology, we believe we can enhance the buyer experience by making search quicker and easier and by surfacing even more relevant, tailored product recommendations,” said Chad Dickerson, Etsy, Inc. CEO.
There’s no denying that the advantages of artificial intelligence are also transforming customer support.
By 2020, 35 percent of customer service operations will involve virtual assistant technology, according to Gartner. While automated chat assistants can resolve routine queries, this type of technology also learns from new cases.
Harness the advantages of artificial intelligence to elevate the customer experience
Customers expect seamless shopping experiences across the physical and digital worlds. To survive - and thrive - in this shifting landscape, IT leaders must meet these expectations. Begin by identifying applications for AI in your organization. Our article on the advantages of artificial intelligence explores how AI-human partnerships can achieve business results in the modern economy.
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