Predictive analytics have already proven its value in sales & marketing and have dramatically increased the ROI of those companies who use it. Cross-selling increases, closing-rate increases, customer churn decreases, and more importantly, profit increases. There’s no secret that machine learning and predictive analytics is taking sales & marketing by storm and changing the game as we know it. But for those who haven’t already adapted to a new reality, it’s not always straightforward how analytics is being used. Here are the four main reasons why companies are benefiting from using predictive analytics.
1: Predict which customers are most likely to buy from you and what
Whether you are in B2C or B2B you can dramatically increase the effectiveness of your sales efforts by utilizing predictive analytics. By using your sales data you can accurately predict what clients are most likely to buy again, and furthermore, you can predict what product/service they are most likely to want. With this information you can more effectively invest your marketing money by simply leaving out those who are unlikely to respond, based on the outcome of your predictive analytics scoring, and place all emphasis on those you know will likely respond. You’ll be able to send the right message to the right customers at the right time. Research shows companies are increasing their marketing ROI by more than 60% by adopting predictive analytics in their sales and marketing efforts.
A growing number of companies in B2B sales, for instance, are utilizing predictive analytics by generating lists of their current clients who are most likely to accept a new product or service. This increases the cross-sales significantly and improves the closing rate of the sales team as they are solely contacting those who are most likely to accept the offer.
2: Get new clients based on information about your current clients
When you have generated insight about those clients most likely to buy your product, as detailed here above, the algorithm can discover a hidden pattern/profile of those who are most likely to buy your product/service. That sort of information is a goldmine which can be utilised to attract new customers who fit that profile. Instead of spraying your marketing budget all over the place, predictive analytics will have generated a specific profile of those who are most likely to positively respond to your message and allowing you to target prospects with laser-focused campaigns.
3: Launch new products and get immediate sales
Even if companies do rigorous marketing research, launching a new product is always a challenge. The marketing focus groups and surveys might have indicated that a certain group of people are willing to buy the product, but when it comes to launching for the mass-market many seem to fail. According to Nielsen statistics, more than 85% of new FMCG fail! But where humans fail, machines might not. By using predictive analytics you can predict what group of people are more likely than others to buy your new product. This allows you to target them specifically both pre- and post launch which dramatically increases the likelihood of the success of your new product.
4: Prevent your clients from leaving you
It costs about 10 times more to get a new client than retain a current one, at least that’s what we’re told. But retaining a current client isn’t always straightforward. Your clients don’t send you messages telling you that they’re gonna buy from someone else next time, or they’re not going to continue buying your service and will go to your competitor. Customer retention is a tricky thing because most of the time you don’t know you’re about to lose a client until you’ve actually lost it.
With predictive analytics you can predict what clients are most likely to leave; i.e. you can literally have a list on your desk every Monday morning with the clients most likely to leave you. This gives you a golden opportunity to reach out to them beforehand and offer them some sort of discount or benefits in order to retain them. You can even engage in preventive marketing by communicating with a group of clients likely to leave with promotions which might create goodwill and eventually prevent them from leaving.
Think of a gym or fitness chain where clients pay a monthly fee. You might not know that a client is thinking about changing gyms and will be going to a competitor next month. However, it would be possible to predict that they were likely to leave, and therefore giving the manager an opportunity to reach out to them with an offer of brining a friend to the gym and both get free 2 month memberships, or that they get a nutrition plan and a personal trainer for 2 weeks, or any action aimed at preventing them from leaving.
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Predictive analytics have already proven its value and more and more companies in every industry are adopting machine learning practices to get an advantage over the competitors. The examples here above are just a small part of what is possible to do. The only thing that is certain is, that those who start using artificial intelligence and adopt analytics before others will certainly gain an advantage. Those who are late to adapt to this changing reality will soon be left behind.
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