Brave New World through Customer Portfolio
Posted: Wed Feb 12, 2025 8:30 am
The principle can be transferred to companies with thousands of customers using databases. From the data we collect, we can calculate customer value and at least estimate customer potential. To simplify things, I imagine a traffic light: we can sell more to green customers, so they are given preferential treatment. Yellow customers are attractive in themselves, but are at risk of switching, so there are customer retention measures for them. And red customers, who are not buying anything now or in the future, need to be rehabilitated - in other words, either gotten rid of or at least only provided with standard marketing measures so that they hardly cause any costs. The closed-loop strategy according to Peppers and Rogers finds different words. I'll simplify things again: first identify, then differentiate, interact and finally improve. First you have to invest in the customer relationship, then you can use it - possibly even sustainably.
Fortunately, the system is not used with mathematical precision. After all, estimating customer iraq telegram data potential can go wrong. Even a student who is on the verge of failure can still get cheap health insurance or a bank account for free. Depending on the method used to calculate customer value, you get more or less meaningful figures. Managers still have to decide for themselves at what customer lifetime value to continue investing in the relationship. And it's nice when people have some leeway when they decide to meet other people's needs.
Unpleasant Truths
We have to face up to a nasty fact: customers are not good per se! Recipients of services who pay less than they bring in can at least have future potential or contribute to the company's image of social responsibility. In this case, the costs incurred by these customers would be booked as marketing expenses. But there are also customers who, even with the best will in the world, are of no use to the business. Insurance companies assume that up to 50% of claims are not 100% correct. Mail order companies are also badly affected. Anyone who orders products without ever intending to pay for them is not a customer, but simply a fraudster. This is a case for anti-fraud management systems (AFMS) . They raise the alarm if the criminal wants to have goods sent to an unused mailbox under a false name, for example. Big data helps always and everywhere. The Italian "redditometro" has now become legendary; tax investigators used it to determine how many Ferrari owners live below the poverty line according to their tax returns. Analysis systems look for data sets that deviate from the mass.
Fortunately, the system is not used with mathematical precision. After all, estimating customer iraq telegram data potential can go wrong. Even a student who is on the verge of failure can still get cheap health insurance or a bank account for free. Depending on the method used to calculate customer value, you get more or less meaningful figures. Managers still have to decide for themselves at what customer lifetime value to continue investing in the relationship. And it's nice when people have some leeway when they decide to meet other people's needs.
Unpleasant Truths
We have to face up to a nasty fact: customers are not good per se! Recipients of services who pay less than they bring in can at least have future potential or contribute to the company's image of social responsibility. In this case, the costs incurred by these customers would be booked as marketing expenses. But there are also customers who, even with the best will in the world, are of no use to the business. Insurance companies assume that up to 50% of claims are not 100% correct. Mail order companies are also badly affected. Anyone who orders products without ever intending to pay for them is not a customer, but simply a fraudster. This is a case for anti-fraud management systems (AFMS) . They raise the alarm if the criminal wants to have goods sent to an unused mailbox under a false name, for example. Big data helps always and everywhere. The Italian "redditometro" has now become legendary; tax investigators used it to determine how many Ferrari owners live below the poverty line according to their tax returns. Analysis systems look for data sets that deviate from the mass.