There's a Lot More to AI Than Just Chatbots
Whenever artificial intelligence (AI) is mentioned in a business context, the conversation inevitably turns to the subject of chatbots. Chatbots are great business tools, from an ecommerce standpoint. Those developed by Fluid and North Face, for instance, can be used to replicate in-store interactions, improving the online shopping experience and increasing the number of consumers who spend on your products and services online.
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Chatbots can be used to deliver better customer service, operate call centers and improve your brand-building: The Walk with Yeshi chabot created by the well-building nonprofit CharityWater earlier this year was an outstanding example of how chatbots can be used to build brand perception, awareness and sentiment.
But, are chatbots the definitive example of how businesses can use AI? Not even close. In fact, not all chatbots will be driven by AI; the majority are scripted and follow a simple decision-tree process. So, while incorporating chatbots into your company strategy is commendable, it's really just dipping your toe into the multiple ways artificial intelligence can improve a business. Have you, for instance, considered data?
Good data management
AI's true power lies in analyzing data and making real-time decisions based on that information. How many data points can one business generate? Taking into account such factors as point of sale, social media, email, ecommerce, search, mobile and advertising, one business could easily generate trillions of data points -- far too many to be processed manually.
Many businesses recognize the importance of data, but making use of it to inform decisions is a separate challenge. The first and most vital step for any business is to keep its data in one place. Finding a good data-management platform (DMP) is essential for any business looking to incorporate AI into its strategy.
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An effective AI system draws data from a DMP: The more complete and high quality the data, the better the AI system will be able to function. Poor data will result in poor, ineffectual artificial intelligence.
A close relationship, then, between the DMP and AI system will also have an impact. Good artificial intelligence will create its own data, which should be automatically fed into the DMP at regular intervals (at a minimum, once each week, ideally in real time) to be truly self-learning.
Options, where the AI uses data to create a model, but does not integrate with the DMP, are okay and will deliver enhanced business results. But they will never be as powerful as a truly integrated system.
Artificial intelligence perceives its environment and makes decisions which will maximize its chance of success at any given goal. This could range from optimizing profit margin, to maximizing stock efficiencies. For example, a supermarket will want to ensure it always has enough salad in stock to supply its customers, while making sure there is minimal wastage and minimal unsold product.
A good AI system can take that supermarket's typical sales into account, but should also be linked to weather information, so if there is a freak heatwave in October, the weather, and not just October's average salad sales, will be considered.
What "gluten-free" can teach us
The AI system's assumption set should also reset frequently so it regularly takes new data into account. For example, think of the gluten-free food movement, initiated a few years ago.
Gluten-free products used to be advertised only to those with Celiac disease, and were sold in specific stores. But then a trend emerged where more and more people started to adopt gluten-free diets, and began searching for those products and where to buy them.
By using AI to analyze which consumers were purchasing those products and the locations where they were proving most popular, then comparing this data against previous trends (such as low-fat, low-sugar), a food retailer or manufacturer could have mapped future trends, so as to be able to adjust its product lines and placement strategies to align with consumer behavior.
Under older methods, vast amounts of data would have needed be analyzed to identify this trend; but without AI, it would have been impossible to detect these patterns.
Artificial intelligence means it is possible to base a decision on each and every piece of information available. And, within advertising campaigns, that information can help you make predictions about each and every impression; or, with ecommerce, make decisions on each and every sale, then use this information to make better decisions.
In sum, AI represents the difference between trying to sell someone shoes because they have feet (!), and trying to sell shoes to someone who actually wants to buy a pair of shoes. AI systems elevate the human thought process, eliminating our biases -- conscious and unconscious -- and following the path that the data shows.
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So, if you are using those chatbots as part of your strategy -- welcome to the world of AI! But don't stop there: Why not explore a little further?