Blog
Understanding & Improving the Customer Journey with Data Science
Learn how predictive marketing analytics can help engage your audience in all the different stages of a customer journey and maximize lead conversion.
Customer Lifetime Value
Predict the customers and prospects that are going to generate more sales and allocate marketing spend based on the financial lifetime value of each.
Distinguish between customers based on business value
It’s not practical to treat every customer or prospect exactly the same. Each can and should receive different marketing messages, different offers, even different levels of service. To maximize profit for your business, you need to predict customer lifetime value (CLV) to know which customers and prospects represent the most in terms of future revenues and profit.
Data science can do exactly this. With a better understanding of CLV, you can optimize your customer relationship management efforts in a way that ensures the best possible business outcome.
Quantify customers' potential value
Predict the lifetime value of each customer and prospect, based on everything you know about them. Understand just how important each is to your future success.
Differentiate marketing and service
Communicate and interact with each customer & prospect based on their long-term importance to your business, not just surface observations. Ensure each gets the experience they deserve.
Find valuable prospects
Use profiles of your most valuable long-term customers to identify and acquire prospects with similar characteristics. Target acquisition marketing to best effect.
Increase revenue and margins
Stop wasting service and retention efforts on customers that don’t merit it. With CLV, you can focus on the most profitable customers to grow your business and accelerate success.
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