When artificial intelligence and machine learning are mentioned, most people think of movie blockbusters, robots, and super-computers. However, these associations are no more science fiction then having a conversation with a chatbot on your favorite e-commerce website. Still, many businesses are doubting the power and the benefits of AI when it comes to sales. For those who are about to embrace it: we salute you! For others, keep reading.
What is machine learning?
Since the understanding of the term artificial intelligence is pretty intuitive, we decided to ask Google about machine learning. We got a results page full of academic and technical articles, experimental researches and various definitions. If you’re looking for the simplest explanation, here it is:
“Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in an autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.”
This means that we can employ a machine learning algorithm to learn about our customer’s habits and shopping affinities which ultimately saves salespeople time so they can focus on negotiating with the potential customer himself, instead of wasting time getting in touch with people not interested in our products.
Now that we established the basics, let’s go over the exact situations where AI and machine learning be beneficial to your company’s sales department.
Relevant content presentation
When customers browse your web-store or sales page, they might expect to find the desired item in an acceptable amount of time (of their own). Since affinities are different, you can’t feature content on the landing page that everyone will find appealing. That’s where machine learning comes into the picture. It lets you provide personalized search results based on preferences of the online customer. Search results powered by machine learning take into consideration customer’s purchase history, location and previous search preference to provide the most relevant content to show. This is like having a custom web-store which offers exactly what the customer is looking for.
Customer lifetime value improvement
Analyzing a diverse series of factors to see which customers are going to churn or leave versus those that will renew is among the most valuable insights AI and machine learning is delivering today. Being able to complete a Customer Lifetime Value Analysis for every customer a company has provides a prioritized roadmap of where the health of client relationships are excellent versus those that need attention.
Find the highest potential new prospects
But first, know your target customer. This is a little perk of machine learning: it can’t do anything for you unless you provide the algorithm with the data it can work with. We strongly encourage you to create your buyer persona, whether you decide to employ AI or not.
A persona is a semi-fictional representation of your real and potential customers, based on market research and data. A persona uncovers your customers’ goals, motivations, behaviors, values and pain points.
Fully understanding your personas helps you plan a marketing strategy that answers your real customers’ questions and leads them through the sales funnel.
Nearly all AI-enabled CRM applications are providing the ability to define a series of attributes, characteristics and specific values that pinpoint the highest potential prospects. Selecting and prioritizing new prospects using this approach saves sales teams thousands of hours a year.
When you use the data obtained from your competitors, and your audience, you’d know the unique price point at which you can sell your products. Being able to analyze pricing data, purchasing history, discounts are taken, promotional programs participated in and many other factors, AI and machine learning can calculate the price elasticity for a given customer, making an optimized price more achievable.
Accurate sales forecasting
AI and machine learning algorithms integrated into CRM, sales management and sales planning applications can explain variations in forecasts, provided they have the data available. Forecasting demand for new products and services is an area where AI and machine learning are reducing the risk of investing in entirely new selling strategies for new products.
The future is now, embrace it and benefit. And for those of you who still remember HAL 9000, remember that he was a fictional character, and start skyrocketing your sales, now!