Back in the 1950s, two psychologists, John Watson and B.F. Skinner, started working on a new theory, predicting consumer behavior. They rejected the idea that psychologists can figure things out through introspection. Given that a generation before, Sigmund Freud spent a very long time thinking about psychology and subsequently developed the Oedipus complex theory, it’s easy to see why.
💡 Read Consumer Behavior Analysis 101: How to Learn More About Your Customers
Instead, they believed psychologists should obtain data the same way other sciences do: through observation. In short, they said that if you want to predict how people will react, look at how they have behaved in the past.
Over the next few decades, this simple idea caused a revolution, giving rise to modern psychology, neuroscience, and, of course, marketing and advertising. Because if you know how people will react to things, you can try to make them behave how you want.
Fast-forward a generation or two, and the folks in Silicon Valley figured out how right Watson and Skinner were. With enough data, you can predict people’s behavior with startling accuracy. The 2000s became the age of big data. Companies like Facebook and Google made a trillion-dollar industry by analyzing the data they harvest.
Now, we’re on the verge of a new revolution: the AI revolution. The power to analyze and predict how customers will react is potentially available to everyone.
In this article, we will explore how you can leverage the power of AI to predict your customer’s behavior and make informed and data-driven decisions about your business, provide your customers with what they really want, and stay ahead of your competitors.
Why Should You Be Using AI Marketing?
AI will change the world as we know it, and marketing is no different. Unlike the old ways, AI can analyze vast amounts of data far more accurately than even the best statistician. And it does it in a fraction of the time.
Do you know why else you should use AI? Because your competitors are. From social media sites to retail and from policing to AI in insurance sector, companies and organizations are embracing AI. You may be happy with the methods you have been using so far, but when your competitors use AI, they have a massive advantage over you.
Imagine you send out your usual mailshot, while they send a personalized email to each customer, offering them the product they most likely want. Yours hits your customer’s inbox at 9 a.m. Monday morning sharp. Theirs is timed to arrive just as they sit down to relax for the day. Yours goes out once a week, without fail. Theirs is optimized to make sure customers are never annoyed by them. See the difference?
What’s Wrong With The Old Ways?
The old-school method of predicting customer behavior worked mainly by using this one trick: asking them. Surveys, focus groups, and reviews were the best ways to conduct market research.
When sales figures got a bit better, marketers started to be able to perform analyses of historical sales data. Perhaps you saw a bump in sales after your last ad campaign. Great stuff. More of that, please. No real difference? Better get back to the drawing board. Over time, you built up an impression of what your customers wanted and stuck with it.
There are a few problems with these methods, though. Firstly, they often lack depth or a fundamental understanding of why your customers react the way they do. You’re using data to get closer to a method that works, but in essence, you’re just playing Marco Polo with your strategy.
The second problem is that these methods are time-consuming. Plowing through the data by hand is both skill and time-intensive. What’s more, insights into your customer’s behavior are often delayed.
Finally, it is worth remembering that humans come preloaded with thoughts and feelings. You can follow rules to reduce the chances of skewing the data. Still, confirmation bias is real, and finding the result you want or expect to see is all too easy.
Read How to Use Social Listening For Market Research
How Can AI Help You Predict Your Customer’s Behavior?
Hopefully, you can begin to see why using AI will be so crucial for your business in the future. Now, let’s look at how AI can help you predict your customers’ behavior and leverage these insights.
Personalized Marketing
One of the significant advantages of AI is its ability to help you personalize your advertising to meet the demands of your customers.
Take the email example we looked at earlier. AI can take information from a mail client, such as Mailchimp, and dramatically improve email deliverability. For example, mail clients can provide metrics such as:
- Open rate
- Click-through rate
- The time at which customers open emails
- Total clicks per link
- Unsubscribe rates
Read Social Media Metrics: 5 KPIs That Matter for Your Bottom Line
AI can build up a detailed picture of each user from these metrics and tailor future emails accordingly. So, suppose a customer only clicks on links for power tools and brown leather sandals and usually opens emails at 5 a.m. In that case, AI can ensure it sends them an email entitled ‘new Makita drill’ at 4:59 in the morning. Oh, and a Father’s Day card in June.
This is the power of personalization—it significantly improves engagement and, by extension, drives sales. Of course, it doesn’t have to be emails, either; social media, text messages, and even the AI chatbot you use on your website can be tailored to your customer’s wants.
Read What You Need to Know Before Trying Personal Selling
Predictive Analytics For Inventory Management
While it may pain us to admit it, not everything companies do has to be centered around marketing—just most of it. One fantastic example of how AI can help your business is by providing intelligently managed stock inventory levels.
Traditionally, managing stock levels has been a bit of an art form. Look at predicted sales figures, add a bit on for buffer, and then perhaps look to see if there are any holidays or sunny/rainy days coming up that will affect stock levels.
However, AI can take out the guesswork by analyzing trends based on historical data while automatically accounting for seasonal changes or even weather patterns, which can be critical to industries such as brewing. Not only that, but once AI has figured out what you need, it can also ensure production has the raw materials in advance.
Predictive inventory management analysis means your production team will always have the stock ready for your sales team to sell, while simultaneously reducing waste due to spoilage.
Read AI in PR: 16 Ways AI Will Transform The Game for PR Pros
Dynamic Pricing
Speaking of spoilage, AI is also changing how companies price goods. By monitoring stock levels and supply and demand issues, AI can ensure you get the optimal pricing levels adjusted in real time. If demand goes up, your prices can reflect this. Suppose a stock is approaching its best before the date. In that case, AI can automatically adjust prices to sell inventory.
One great example of this are airlines, who regularly adjust the prices of their flights based on the location of the buyer’s IP address, so customers in more affluent areas often pay more for the same flight.
Sentiment Analysis
Another amazing example of how businesses are using AI to react dynamically to situations is sentiment analysis. Many companies now use call center AI systems to monitor how customers feel about calls in real time.
Sentiment analysis can be instrumental for managers to see how their team is doing and as a training tool for new employees.
How To Implement AI Customer Predictions Into Your Business
The applications of AI are vast; in this article, we have only scratched the surface of what AI predictions can do.
Conservationists use AI to predict where poachers will strike, fashion houses predict the next big trend, and companies with FedRAMP compliance requirements use AI to work on sensitive data. The police are even using AI to predict when criminals will commit crimes. Although, that does sound a little too close to Minority Report for comfort.
These applications are all exciting ways to use AI—but getting started can be a bit daunting, though for entrepreneurs and those starting a business, integrating AI can be a game-changer. Will you need a computer science degree to manage your sales team? Well, no. The good news is that there are experts who know AI, so you don’t have to. In fact, the chances are you’re already using AI without even realizing it.
Speak to your CRM provider—ask them about AI integrations with their software. If you have a specific task, you can find a company that will cover it. Those wildlife conservationists don’t know about AI; they know elephants. When they needed help, they asked the smarty-pants at Harvard University. In case you missed it, there are even companies that offer AI-powered media monitoring solutions.
Read New in Determ: AI Assistant Synthia
AI In A Nutshell
AI is already changing how we predict customer behavior. From personalizing marketing to providing real-time analysis for sales teams, companies are embracing the AI revolution.
The question isn’t if you implement AI’s predictive analysis but how and how soon. The great news is that tools are already out there to help your company grow so that you can offer your customers what they want when they want it.
If you’d like to learn more about how to track your sentiment score with Determ and learn how AI can helo you, book a demo, we’d be happy to assist you.
