Brazil's mobile market place is heating up with four large operators fighting for customers and prices in a downward spiral.
Earlier we looked at how cheap data is in Brazil as well as the relatively high churn that Brazilian mobile operators are experiencing. Generally speaking any market with strong competition, lower prices and a high churn rate would scare off potential new players such as MVNOs.
Data from TIM Brasil
When analyzing the Brazilian mobile landscape TIM Brasil provide the cleanest data source.
Their P&L clearly outlines the mobile-related revenues and the revenue related to handset sales, and telecom services other than mobile are less than 20% of their gross revenue.
Customer Acquisition Cost for TIM Brasil.
The graph below shows that TIM’s customer acquisition cost for mobile subscribers has been stable at around BRL 80 since the fourth quarter of 2010.
Important: In my calculation I have applied a method of calculating customer acquisition cost similar to how a technology startup would do. However TIM Brasil report a Subscriber Acquisition Cost around BRL 30 in their earning reports.
TIM Brasil reports gross revenue generated for each of the product lines in its P&L, however “marketing and sales cost” is not reported per product line.
My simplified assumption is that “marketing and sales cost” is in direct relation to gross revenue generated by each of TIM Brasil’s product lines. I therefore adjusted the marketing and sales cost accordingly and use the adjusted marketing and sales cost as a base for calculating customer acquisition cost.
CAC in Relation to Monthly ARPU for TIM Brasil
When analyzing the customer acquisition cost data it’s interesting to relate them to the average revenue per user data reported by TIM Brasil.
The graph below shows that a subscriber will have to stay with TIM Brasil for almost five months before it has covered the initial cost of acquiring that subscriber.
Continue the Discussion
This is a simplified model for calculating customer acquisition cost for TIM Brasil. The model does not take into account differences between the classes of mobile service types, such as post-paid and pre-paid. The model also misses a function for discounting marketing expenses towards increased brand value.
If you are interested in analyzing the data you can download the spreadsheet from my OneDrive account. It would be highly appreciated if you could share your reflections and analytics in the comments below.