According to just-concluded research, it was discovered that customers who are more active when it comes to their general engagement with a particular brand tend to make 90% more frequent sales than others and spend 60% more when making transactions. Also, they are most likely to choose that same brand five times more when coming to make purchases in the nearest future.
When it comes to keeping a customer engaged, product recommendations works better than anything else. This helps make your customers receptive to certain types of products and make them more inclined to take their business elsewhere.
Product Recommendations
Product recommendations are often done by integrating the real-time purchase data in your business with your historic purchase. With the use of data science, you will be able to make specific types of recommendations that will help improve your loyalty program. For instance, as a business owner who specializes in developing software for companies you were opportune to sell payroll software to another company. There is a possibility that their team might be interested in getting a series of accounting webinars, but you can’t just go ahead to recommend this without a guarantee that they will be interested. Data science can make that easy by analyzing their historical purchase data RI know if they might be interested in your recommendations. With this, you will be able to make all kinds of recommendations to all your customers with a guarantee that they will buy immediately or come back to buy from you in the nearest future when they need it.
The data collected for this kind of analysis include lifestyle patterns of your customers, the product purchased over a specific period, and the demographics of your customers. The aggregation of all these gives you a clearer picture of what to recommend to your customers. All these data are collected to make a recommendation so that you won’t just base your conclusion on just a piece of data. Just because you have a customer who stays in Canada during the cold winter months doesn’t mean you should make recommendations that have to do with buying winter coats. Such a person might not even require it.
What this is trying to express in a simple sentence is that you need to gather multiple data before going to make recommendations to your customers.
To conclude, it is pretty simple, one size doesn’t fit all. Using data science, a business can make the right categories of customers and you can use these categories or clusters of customers to understand what product to recommend to them. Data Science makes it easier for you to make the right recommendations because it studies and analyses all the user data available. For instance, it takes into consideration the geographical location, age group, gender, and past purchases before recommending what might be the right product to recommend and which promotion this customer might go for.
It is important before making a product recommendation to doubly make sure that the customer is highly likely to go for the promotion. This you can make sure with Data Science. Data Science helps you not just make recommendations but will help you predict outcomes as well.
We can help you with all this and more and we are just a click away. Contact us at NextBee and we with our set of skilled and experienced professionals will help you make the right recommendations.
