Ultimately, companies have a single source of revenue: their customers.
Meanwhile, some companies make good use of customer and transactional data and data analysis to understand how much revenue they’re generating on a customer-by-customer basis or between certain sets of customers.
Nonetheless, many companies often don’t apply the same rigor to determining how much it costs to serve each customer or to serve customers in certain segments. These are critical requirements for companies that expect to survive, much less succeed, notes Joe Brady in a blog post.
Some customers cost more than they’re worth. Other customers or customer groups are worth more than business leaders realize. Companies can use data discovery capabilities to help senior executives identify which customers they should cater to for certain marketing campaigns.
Customer insights, aided by data visualization tools, can also enable business leaders to identify high-value customers and ensure they’re receiving preferential treatment when they’re dialing into a call center for assistance.
Quarterly earnings pressure often leads sales and marketing executives to focus on new customer acquisitions, especially when it comes to meeting revenue targets. Far less attention is paid to the business ramifications of losing existing customers due to poor product or service experiences.
But there should be.
Data analysis indicates that it typically costs a company six times as much to replace an existing customer with a new one than it does to retain that customer. Because customer loyalty has such a strong bearing on revenue stabilization, considerably more attention should be paid to satisfying and retaining existing customers.
Still, business leaders should take care to ensure that they’re not being pound-wise but penny foolish when it comes to customer retention. Using data analysis and data discovery tools, decision makers can examine a customer’s current value to the company as well as his anticipated short-term and long-term value.
The use of data visualization tools can help make this type of information pop for senior executives, enabling them to quicky identify key trends and to take swift action. It certainly doesn’t make sense for companies to overspend to retain low-value customers or customers costing them money.
The fact is, there are no guarantees that a customer will purchase from a particular company again. But business leaders can use data analysis to determine a customer’s recent transaction history as well as his current lifecycle status and other vital signs to help predict his likelihood to purchase again in, say, six months or twelve months and how much he can be expected to spend.
For instance, a double-income family with a daughter who’s about to start college may be likely to buy her a laptop computer. However, depending on the family’s income, debt, and financial obligations, it may be less likely for the parents to purchase a new car for themselves with college expenses looming.
Another benefit to using data analysis in this regard is that it can help decision makers determine how much the company should be spending on promotions and other forms of marketing for different sets of customers.
Data discovery tools can help business leaders identify customer value by different customer groups (by geography, types of products purchased, etc.) and determine the level of marketing spend that’s appropriate for different customer segments based on their likelihood to convert.
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