Today’s retail industry is far more fragmented and competitive than ever. Multiple store formats and an arsenal of digital tools are making shoppers more educated about choices. Digital channels also continue growing. The landscape has become more diverse, too, with a variety of household types and lifestyles having very different needs than the parents-with-kids target that dominated generations past.
But the advent of distinct devices, sensors and machine-to-machine communications has made data sets so large that timely manipulation, management and analysis present significant logistical challenges for companies using on-hand data management tools or traditional data processing applications. Other entities have incorrect or outdated legacy data.
Turning to AI
Many successful high-volume retailers and consumer packaged goods organizations have turned to artificial intelligence to provide real-time, in-depth knowledge to attract diverse shoppers. At the simplest level, AI machines or systems imitate human behavior in intelligent ways that can augment productivity and optimize business performance.
AI allows retailers and manufacturers to gather customer insights in an automated fashion and predict next actions based on previous patterns or images. AI uses predictive patterns to help understand desires, motivations and actions across both physical and digital channels. This lets retailers and suppliers enhance many functions, such as executing more targeted and personalized marketing campaigns and improve trade promotion efforts. AI can also automate forecasting of inventory needs, more accurately predict out-of-stock incidences and ultimately help optimize supply chains.
But AI isn’t itself a unique capability; rather, AI is a field that includes three distinct methods of technical applications: robotics, machine learning and natural language processing.
Science-fiction writers have long predicted the day when tasks traditionally performed by humans are fully automated and completed by robots. While true in some sense—warehouse picking and packing, for example, can be performed by robots—the reality is that the replacement of people by robots in many retail cases doesn’t drive strong efficiency gains in the grand scheme of things.
Rather, it is the complexity of managing data with standard systems that is the real sticking ground for progress in the industry. This is compounded by the difficulties many companies face in recruiting the talent needed to implement complex technology tools, analyze the data and make effective recommendations. Because of this, retailers generally look to the two other kinds of AI—machine learning and natural language processing—to create value through better efficiency, service and experience.
Machine learning is really at the core of what we consider artificial intelligence and—as opposed to robotics—is leveraged almost entirely as a professional or personal augmentation, not replacement. Machine learning is the foundational technology that allows a retailer or CPG manufacturer to analyze large amounts of data and discover patterns and trends in real or near-real time. Evolving from root cause analytics, machine learning’s models change and learn every time feedback is received, allowing retailers to determine why something occurred.
Machine learning is already a widely applied technology across the retail landscape, not only to perform data analysis faster than humans but also to help experts within the organization make more informed and intelligent decisions that support business and customer needs. The next step in the hierarchy of AI is deep learning, which includes both machine learning and machine reasoning. With deep learning, a two-way machine reasoning capability allows retailers to evaluate past actions and prescriptive proactive recommendations.
Natural Language Processing
With consumer-facing technologies such as Amazon Alexa and Google Home joining mainstream consciousness, we’re all aware of the fact that machines can now understand, analyze and generate human speech, as opposed to a computer language such as Java or SQL. While not a brand-new field, it’s one that is growing very quickly and has significant potential to impact the way a company’s staff manage operations.
Natural language processing, or NLP, allows managers to request detailed information about a specific store, product, shipping method or other topic without touching a PC. By using AI solutions that respond to human speech, employees can easily find answers to key questions about their area of oversight. It allows, for example, category managers to find answers to questions they deem most critical for performance without having to master a computer system too.
A New Order of Intelligence
AI has been a pop culture phenomenon for decades, but today it is finally becoming reality in a much different way. The robots aren’t coming for our jobs, and artificial intelligence isn’t making human creativity or mobility a limitation. Rather, AI is making humans even better at what we do, and the retail industry is primed to be a major beneficiary.
Sy Fahimi is senior VP of product strategy for Symphony RetailAI