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The Net Promoter Score is a customer satisfaction survey where you don't 'just' calculate the average satisfaction score, but distinguish between negative, neutral, and positive customers. The idea behind this is customers who are very positive about your business and product are more likely to promote you to other potential customers, whereas negative customers will do the opposite. 

However, you will need a few more questions than only one about the likelihood of recommending your company and product if you are to find out what drives your customers' satisfaction.

I can help you to develop a useful questionnaire, set up a survey, and analyze the results. This analysis will give you not only your NPS score but will also show you which aspects of your product and service can be improved to increase your customers' satisfaction. Based on the results you will be able to identify distinctive customer needs and optimize your offerings.



In order to obtain and keep your ISO 9001 certificate, you will want to have an idea about how your customers perceive your organization and its performance. Of course, this can be done by asking your customers this question directly through an NPS or other customer satisfaction survey. 

However, there are other ways to capture the perception of your customers indirectly. By measuring the number of customers won and lost over time together with the average period of being a customer and their average spending, you will have a quantified idea about your customers' loyalty. This data is already available within your company.

If you would combine this with some qualitative input, you greatly increase your insight about your customers. Find out how you can increase your customer base and their profitability.

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Lifecycle based customer segmentation

Most marketeers would agree that it is wise to focus more on existing customers rather than new customers. A very effective and also relatively simple way of segmenting existing customers is by using the so-called RFM-analysis.

This analysis has proved to be very effective in e-commerce and customer marketing. The central idea is to segment existing customers based on their buying behavior: when was their last purchase [Recency], how many times have they placed an order [Frequency], and how much have they spent in total [Monetary value] during the last two years.

The RFM-analysis has proved to be very effective at predicting a customer's willingness to engage in a company’s marketing messages and offerings. Thus customers can be categorized as e.g. "promising" or "at risk of losing".

All you need is your transaction data of a period of two years, including a unique customer id, the transaction date, and the transaction amount, then this analysis can be done and you can determine which customers of yours need which kind of attention. 


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