Customer lifetime value is one of the most important metrics to measure for any business. By measuring customer lifetime value, businesses can:
- Optimize advertising costs
- Calculate ROI accurately
- Identify high-value customer segments effectively.
However, currently on the market, there is no tool that can accurately measure, analyze and predict pLTV indicators. Understanding this, after a long period of research and testing, the Airbridge team has now launched the pLTV feature to equip more tools to help businesses optimize the effectiveness of each advertising dollar spent.
So, what is Predictive Lifetime Value (pLTV)?
pLTV is the estimated customer lifetime value, which is simply understood as how much money the customer plans to spend on the business during the entire process of using the business's services.
Airbridge's pLTV is calculated based on: average revenue per daily active user multiplied by the number of predicted hours.
- Formula for calculating pLTV: pLTV = Forecast Time * ARPDAU (Average revenue per daily active user)
Note: The more data you collect, the more accurate your model's predictions will be. Therefore, if you want to predict the value your users generate over a period of time, you need to collect more days of data. For example, to predict the value your customers generate over 10 days, you need about 20 days of data.
Why do businesses need pLTV?
IOS 14.5+ and the challenges of predicting pLTV and measuring campaigns
- In the context of Apple's restrictions from iOS 14.5+, with the introduction of App Tracking Transparency (ATT) and SKAdNetwork, the estimated customer lifetime value (pLTV) is affected by the limited access and use of user data. This affects the collection of important information to forecast the expected value that each user can bring from the advertising channel.
- ATT displays a notification asking users to click a consent button before allowing the enterprise mobile app to track their mobile app activity. This reduces the availability of data collected from sources outside the app, limiting the ability to track and collect information about user behavior.
- Along with that, SKAdNetwork – an Apple platform that allows advertisers to track the effectiveness of advertising campaigns without revealing personal information of users. However, it also reduces information and limits the ability to track users in detail, thereby affecting the ability to predict pLTV based on information about user behavior. .
As a result, Apple's restrictions have reduced the availability of data needed to predict pLTV, making it more difficult and less accurate to estimate expected user value. In addition, CAC costs are getting higher and higher. Calculating the effectiveness of each advertising dollar is a must-have for businesses.
Airbridge proudly introduces the pLTV feature using Machine learning & AI model with accuracy up to 90%.
When evaluating the effectiveness of an advertising campaign, one of the metrics that advertisers need to measure is the ratio between the lifetime value of a user and the cost to acquire that user (pLTV/CAC). In addition to the pLTV metric, Airbridge also provides the CAC (Customer Acquisition Cost) metric. This metric provides information about the cost of customer acquisition, helping businesses determine appropriate customer care strategies. This can include improving support services, incentive programs, or special marketing strategies.
- Example 1:
On Ad Channel 1: CAC = 50,000 VND. That means to get 1 user from Ad Channel 1, the advertiser has to spend an average of 50,000 VND per day.
- The ratio between pLTV and CAC allows businesses to compare the lifetime value of a user to the Customer Acquisition Cost (CAC). To calculate CAC, divide your total advertising spend by the number of customers you acquire. The ratio between pLTV and CAC is calculated as pLTV / CAC. This can be expressed as a ratio, for example 4:1.
- If the result is below 1, the advertising effectiveness is problematic: the advertiser may have difficulty recouping costs during the customer conversion period. On the other hand, a very high number shows that you are successful in attracting quality customers.
Therefore, the pLTV feature is extremely useful to get an overview of a business's advertising performance and see its overall direction. This information is necessary to set long-term advertising goals, which will contribute to changing the image of the business.
How can Predictive Lifetime Value (pLTV) help businesses?
- Ensuring the effectiveness of advertising campaigns: Businesses can use pLTV to estimate the expected value of each user across their advertising channels, helping them optimize their UA campaigns. If the expected value is high, they can afford to pay more to acquire each new user.
- Adjust CPA strategy: CPA is the cost to achieve a specific action such as: installs, purchases, registrations, etc. As pLTV increases, businesses can review and adjust their CPA strategy to maximize profits.
- Decide on advertising budget: If pLTV is high, businesses may consider increasing their advertising budget. This is because they know that the expected value from a new user is greater than the cost they pay to acquire them.
- Campaign performance prediction: By using pLTV, businesses can predict the effectiveness of their advertising campaigns and adjust their strategies before spending a large amount of their budget.
Sign up for consultation or product trial here
