How can you calculate customer lifetime value for online and offline shoppers?

I have mentioned (later on) that it is important to collect good-quality data. Segmentation is important as that will provide a perspective to identify different cohorts and their preferred shopping and marketing channels. Usage of RFM, behavioural and preference data analysis can help provide a deeper insight. Critical that all customers need to be treated as one.

Online: historical CLV, predictive CLV, cohort (segment) analysis Offline: revenue, customer surveys/feedback, RFM P.S. Don't forget to compare CLV with CAC to ensure that the cost of acquiring customers does not exceed their lifetime value. P.P.S. Keep in mind that these calculations provide estimates, and the accuracy depends on the quality and quantity of available data.

-Identifying customer segments is crucial for targeted marketing efforts. By leveraging data from various sources like CRM, loyalty programs, and surveys, businesses can categorize customers based on their shopping behavior, preferences, and demographics. This segmentation enables personalized marketing strategies tailored to specific customer groups, improving customer engagement and satisfaction while optimizing marketing resources. Moreover, understanding customer segments aids in crafting effective omnichannel experiences that cater to diverse customer needs and preferences.

ARPU or ARPC is fine and I would also like to add here that today customers have a choice to shop from any or multiple channels the brand has deployed.

- Estimating average revenue per customer (ARPC) is essential for understanding the value each customer segment contributes to your business. By dividing total revenue by the number of customers in each segment, you can gauge their purchasing behavior and potential profitability. This insight allows for targeted marketing efforts and resource allocation to segments with higher ARPC, maximizing revenue and improving overall business performance. Additionally, monitoring ARPC over time helps track changes in customer spending patterns and informs strategic decision-making to enhance customer lifetime value.

To calculate the customer lifetime value (CLV) for both online and offline shoppers, begin by estimating the average customer lifespan. For online shoppers, consider factors such as repeat purchase frequency, average transaction value, and retention rates over a specified period. For offline shoppers, analyze similar data obtained from in-store transactions. By identifying the average duration a customer remains engaged with your brand across both channels, you can then multiply this by the average revenue generated per customer during this period. The resulting value provides an estimate of the customer's lifetime value, serving as a valuable metric for strategic decision-making in marketing, customer acquisition, and retention.

Some metrics that can be looked at: - Average Purchase Value - Purchase frequency & recency - Customer lifespan and importantly - the customer retention rate (retention rates can be different for customers shopping from offline & online shopping channels)

Segmentation: Consider segmenting customers based on behavior, demographics, or other factors. CLV can vary among different customer segments. Discount Rates: Some calculations involve discounting future cash flows to present value. This requires determining an appropriate discount rate. Continuous Monitoring: CLV is not a one-time calculation. Regularly update and monitor your metrics to adapt to changes in customer behavior or market conditions.

Before getting into anything specific, the first step will be to ensure 1) the collection of data 2) more importantly - how good is the quality of data. Secondly - is the customer data collected houses in a central location. Since this is marketing-related a CDP (Customer Data Platform) can play a vital role. Focus on the power of one. With channels blurring (omnichannel) - one cannot and should not differentiate between online and offline.

Customer lifetime value (CLV, or LTV for “lifetime value”) helps you predict future revenue and measure long-term business success. CLV tells you how much profit your company can expect from a typical client over the course of the relationship. More to the point, CLV helps you estimate how much you should invest in order to retain a customer. There are many important metrics to take into account in order to optimize costs. Simply by calculating lifetime value, you can improve your business in all directions. You’ll get an idea from CLV investigations of how to build customer loyalty and increase sales. But easiest bifurcation is data sets that you specifically mine and segment based on segregated offline and online numbers. Regards,

A segment's Customer Lifetime Value (CLV) is often misused to make an investment decision that is not sound at first sight. Predicting a CLV on historic performance is a good start, but don' stop after approval. Monitor how segments are behaving and if CLV are met. Map all actions (and their associated costs) that have prevented a customer to churn and recalculate the CLV for each of your customer segments.