If you want your business to grow, you need to know who your customers are. Instead of taking them as a whole, it’s better to divide them into segments and describe key features of each group. This way, it is easier to prepare relevant marketing campaigns that target different audiences. One of the most commonly used models within the cinema industry, which facilitates the analysis of customer behavior, is the so-called RFM analysis model.
What is RFM analysis?
In short, RFM stands for Recency, Frequency, and Monetary value. It is a kind of model used to segment customers based on their transaction history. Recency refers to when they last visited your cinema, frequency refers to how often do they come to your place, and monetary value is how much they usually spend when using your services. Based on the combination of these three important parameters, you can easily draw conclusions concerning your audience and rank moviegoers by the value they bring to your company. Customers who spend more than others do, visit your cinema more often, or spend more than others should be ranked higher.
Types of cinema customers
Thanks to FRM analysis, you can group moviegoers according to their recency, frequency, and expenses, by establishing if they fall below or above the median value for each category. As a result, you should be able to divide them into at least eight groups:
- Loyal customers – these moviegoers have recently been to the cinema, they often visit it and spend a lot of money there.
Customers at risk – these moviegoers go to cinemas regularly and spend a lot, but haven’t been at your venue recently.
Potential loyal customers – these moviegoers have been to the cinema recently and spent a lot, but they are not frequent visitors.
Customers seeking attention – these moviegoers spend a lot each time they visit your cinema, but they rarely visit you and haven’t been at your venue for a long time.
Promising customers – these moviegoers have been at your cinema recently and watch films at your place frequently, but do not spend much when they come.
Recent customers – these moviegoers have been to the cinema recently, but do not do it regularly and do not spend much.
Customers which are about to be lost – these moviegoers haven’t been to the cinema recently, do not come frequently, and also do not spend much.
Dividing your customers into such groups based on RFM segments will allow you to focus more on valuable customers and tailor your massages to their needs.
How does it work?
Grouping customers into segments helps you understand your cinema business and its audience, as well as make plans for the future. By answering the questions like who are your best customers, which customers are likely to become loyal customers, which customers should be retained, or which customers are likely to respond to your marketing messages, you can plan your marketing strategy.
RFM analysis in practice
RFM analysis shows that there is no unique way in which you can market your products to all your customers. To put it simply, let’s now focus on how to encourage customers who fall behind the median value of each of the three main segments:
- Customers with low recency: targeted communication via marketing automation, e.g., through newsletters or online ads, as well as free vouchers can be helpful in reaching customers who love cinema, but haven’t been at your place for a long time.
- Customers with low frequency: in order to encourage moviegoers to visit your cinema more frequently, provide them with discounts or time-limited vouchers for additional services or products. Consider implementing a loyalty program. Targeted communication can also be a booster in attracting their attention.
- Customers with low monetary value: to increase the amount of money they spend at your cinema, it is recommended to implement various up-selling and cross-selling strategies.
As you can see, RFM segmentation can help you find your best moviegoers, understand their actions and prepare your marketing strategy accordingly. It is therefore one of the easiest techniques of sales and performance optimization.
