Why artificial intelligence is crucial to better business software
Artificial intelligence (AI) has been a hot topic for food retailers for years — and for good reason. This technology has the power to track customer insights in real time, speed up decision-making and genuinely reshape how grocers approach countless scenarios, from personalized promotions to pricing optimization, assortment challenges and much more.
AI only yields value when it delivers on its core objectives — to drive better, faster decisions for the end user. Ease of use and intuitiveness are both critical to continued adoption, and while that focus is fairly common for consumer-facing AI applications (Google search, Apple’s Siri), it’s much less so in the world of business software.
For vendors interested in leveraging the power of AI to improve their business software solutions, there are a number of focus areas. Here are a few.
Natural language processing
As AI has grown in prominence, the technology’s ability to intuitively understand how humans talk (or type) has grown with it. This is referred to as natural language processing, and Google’s search feature is a great example. When a user conducts a search, Google’s AI isn’t just word matching; it’s inferring meaning. The more people search, the smarter the page rankings and recommendations become. And as more people click on a link, its relevance score goes up.
Software designed for retailers has yet to latch onto this trend. With most programs, the average category manager signs into their system and is greeted by a landing page that presents 20 different reports from any number of departments or categories. Then, they must scroll through to their specific category, manually and individually queue up each relevant report and download them one by one. There may be a favourites/bookmark feature, but that only slightly improves the experience.
AI could simplify this process in a major way, allowing that same category manager to use a single search bar to be directed wherever they need to go. Investing in a search bar that excels in natural language processing could take that a step further — providing access to the most relevant information by simply typing, “How are my categories doing today?” This saves time, money and effort on a day-to-day basis, while also eliminating the need to train every employee on a complicated system.
The level of detailed information most employees need to do their jobs is funneled, with front-line, managerial and operational staff needing deep insights into small areas and more senior executives requiring top-line information across an entire organization. AI can be used to create personas based on these different levels, which leads to software that designs and delivers different, highly relevant reports for everyone from category managers to a marketing director or the CEO.
Personalized software solutions, which have been around for a while, use pre-defined segments (personas) to better suit users’ needs. The future will take that a step further, providing a truly dynamic experience based on how each individual user interacts with it. Just like the Google search feature, the more people use it, the smarter it becomes with its delivery of personalized information. If a category manager typically pulls a weekly report on Monday morning, the software could automate the delivery based on that habit, sending a regular prompt at 8:55 a.m. each Monday. Precima is already experimenting with this sort of technology, testing different alerts and notifications that will automatically inform employees of certain tasks or newly available information.
Artificial intelligence, combined with machine learning, could help to not only improve end-user experiences, but could provide valuable trends or data that may not be noticeable for the average person. For example, software for a grocery chain could identify a real-time spike in flu vaccination sales at 2 p.m. on a Wednesday afternoon, automatically identify the insight without any input from a human user, and send an alert or notification along with a link to the relevant data to the appropriate category manager.
The manager, in turn, could discern that the spike was prompted by a local news story on the flu and request that the store’s social media team repost the story to drive sales even further. By leveraging AI to track this sort of real-time, day-to-day deviation in the store, employees across an organization would be provided with ammunition to make better decisions that could lead to growth in sales and profit.
The integration of AI into the world of food retailers is a foregone conclusion, but we’re still in the early process of understanding how it can be leveraged to improve software solutions.
Investing in the right analytics has the potential to drive better decisions that power growth. AI is making good on that promise, fundamentally transforming the retail industry and unlocking massive potential. To continue that progress, AI applications need to go beyond just delivering insights requested by users, and instead interact with them in an intuitive, seamless way and offer valuable insights without prompting. Making that step won’t be easy, but the benefits are there for the brands who commit to a strong focus on how AI can make employees’ jobs easier and provide them with the right data to make smarter decisions.