Growth with Artificial Intelligence
6 Ways Businesses are Profiting with Artificial Intelligence
Predictive Targeted Marketing
By crunching the customer data that almost all businesses now collect, enterprises are using AI to predict how customers will react to products and promotions. That makes marketing much more cost effective and targeted. Some companies are using like-customer models that use machine learning to analyze who their current customers are and how they act. That allows for better targeting during marketing campaigns and can also be done on a micro-scale, examining who reacted best to specific test promotions and then using that information to target similar customers at a larger scale. But there is a limit to small-scale tests. Machine learning relies on having a lot of data to find general patterns. Businesses are also using AI to build full psychographic personality profiles on their customers, which lets them categorize customers based on what they’re really like under the surface instead of relying on demographics and geography.
Some companies are using AI to help define their entire brand. Instead of relying on subjective judgment to figure out where to place their brand in the market, machine learning algorithms can help find untapped niches by seeing patterns in data that no human could’ve analyzed in a lifetime
Refined Product Design
It’s always been hard to know what people want. Most people don’t even know, until they’ve seen it, and many still buy products that they later realize weren’t what they wanted at all. But by using AI, companies are starting to nail down what people want.
Early on, Netflix started using its data to decide on certain requirements for movies and shows. They found specific combinations of plots, characters and actors that seemed to consistently draw viewers, and then they made more shows designed around those combinations. More recently, some filmmakers let an AI write an entire short film, but as the creators explained to Ars Technica, the AI can only write “based on what other people have written,” meaning anything it writes “is just a pure reflection of what other people have said.” (arstechnica.com/gaming/2016/06/an-ai-wrote-this-movie-and-its-strangely-moving/)
Machine learning is useful for understanding customers, but it’s not going to replace marketers and product designers just yet. Instead, as businesses gather more data on how their customers use their products and services, they will finally be able to narrow down what customers really want so that marketers and product designers can give it to them. For example, a company might be able to understand why customers don’t like or understand specific features by tracking how customers use their products.
Beyond increasing profits by increasing returns with targeted marketing and desirable products, many businesses are also using AI to increase profits by cutting costs within the organization. AI also has the potential to help organize entire projects, streamlining project management headaches. Some companies are even using AI to automate fairly routine but complicated problems that used to take humans years of learning to do efficiently, such as financial services and supply-chain management. Anything that follows strict rules and routines is a prime target for automation with AI.
Many businesses in the financial sector are using AI-based algorithms to track and detect fraud. Not only can these machine-learning algorithms catch patterns that humans might miss, the extreme volume of transactions today means that no team would be able to keep up with online fraud by themselves. However, humans still have to be there at the end of the line to judge for themselves what action they need to take.
Automated Customer Service
At the far end of AI’s capabilities, some companies are also experimenting with AI in customer service. Automated switchboard systems for phone-based customer service have existed for years, but AI offers the potential to deal with entire routine customer service issues through chatbot-based systems. Computerized voice technology can already vocalize words into intelligible and personable speech, and machine-learning AIs are gradually getting better at putting together understandable conversations. However because human language is so messy, humans will still have to be at the end of the line for more complicated problems. MIT Technology Review described how one researcher’s talking AI can come up with comprehensible sentences and that it, “understands that certain combinations of symbols go together, but it has no appreciation of the real world.” (technologyreview.com/s/602094/ais-language-problem/).
Even though artificial intelligence is still a long way from what humans recognize as intelligent, the potential of AI to streamline businesses with better customer interactions, branding, and internal organization is only just beginning to get tapped. Every company that is looking to the future needs to explore the potential of AI if they don’t want to be left behind.