Lift
represents an increase in sales in response to some form of advertising or promotion.
Lookback Window
Lookback Window Definition
A lookback window refers to the specified timeframe following an advertisement’s click or view, during which an app installation can be credited to that advertisement. This window is pivotal in determining the effectiveness of an ad in prompting a user to download an app.
Attribution Mechanics Explained
Advertisers and attribution providers utilize lookback windows to assess whether a particular ad click or view was instrumental in a user’s decision to install an app. This process is vital for understanding and optimizing ad performance.
Varieties of Lookback Windows
Standard 7-Day Window: By default, if a user engages with an ad from Network X and installs the corresponding app within seven days—without interacting with another ad in the interim—Network X is attributed with the installation. Advertisers can often adjust this period to align with their specific attribution requirements.
24-Hour Probabilistic Modeling: In scenarios lacking a device ID (e.g., Google Advertising ID or Apple’s IDFA), probabilistic modeling steps in. This approach, which estimates the likelihood of an ad leading to an install within a 24-hour frame, relies on statistical probabilities and, while not infallible, boasts high accuracy within its limited timeframe.
Attribution Windows of Major Platforms
- Platforms like Facebook and Google set their attribution windows at 28 and 30 days, respectively, while Twitter offers a default of 1 day for views and 14 days for clicks. Twitter further allows advertisers to select from predetermined windows ranging from 1 to 90 days. These platforms typically operate on a cost-per-click basis, billing advertisers for any engagement within these windows, regardless of the sequence of clicks.
Interaction Between Third-Party Attribution Providers and Self-Reporting Networks
Self-reporting networks differ from their counterparts by not directly reporting each interaction. Instead, they establish a data-sharing agreement with attribution partners. Upon detecting an install, the attribution provider syncs the device ID with the network using a specialized API. This process enables the network to report any ad clicks or views associated with that device ID within the established lookback window.
LTV (Life time value)
A metric that determines how valuable a customer will be to your app over the whole relationship with the app. It tells you how much a user is worth and determines how much you should pay for this user.
What is Lifetime Value (LTV)?
Lifetime Value (LTV) is a significant metric used to estimate the average revenue generated by a single app user or customer throughout their entire lifespan, whether as a free or paying user or customer. This metric is closely related to Customer Lifetime Value (CLTV), and it helps companies make informed decisions on how much they can spend to acquire a new user or customer.
LTV plays a crucial role in enabling companies to understand potential profitability, scale their marketing budgets, forecast revenue, and more. The calculation of LTV varies based on whether the app is a paid app, an ad-supported app, or a subscription business. Nevertheless, it is an essential tool for analyzing the ROI of marketing efforts.
Growth marketers can calculate the payback time for upfront advertising or marketing costs and the expected profit from each customer over their lifetime by knowing their user or customer lifetime value and their user or customer acquisition cost (CAC). However, as each user or customer will differ based on their level of engagement, retention rate, and ultimate value to the company, this metric is an estimate that fluctuates over time.
LTV vs CLV
When it comes to customer valuation metrics, two terms that are often used interchangeably are LTV and CLV. However, there are some subtle differences between the two.
Typically, CLV is used to measure the total value that an individual customer brings to a business over the course of their entire relationship with the company. On the other hand, LTV is a metric that provides an estimate of the average value of a business’s entire customer base, including both paying and non-paying users or customers. In other words, while CLV is focused on the value of a single customer, LTV looks at the bigger picture and considers the average value of all customers.
Why is LTV important?
The importance of LTV cannot be overstated, especially in the free-to-install app economy. When combined with the average revenue per user, LTV becomes a critical metric for determining the potential revenue or value of your users.
Here are some of the key reasons why measuring LTV is so important:
Improve your strategies: If you don’t measure LTV, you can’t improve it. Once you begin measuring LTV and breaking down its various components, you can employ more targeted strategies around pricing, advertising, and user retention. This helps you achieve your goals of improving your user experience and increasing profit.
Better user acquisition decisions: By knowing what to expect in terms of average earnings per user, you can increase or decrease your spending on user acquisition to maximize profitability and continue attracting the right audience.
Improve forecasting: LTV predictions can help you make forward-looking decisions around ad spend. LTV forecasting minimizes the risk of underspending and missing out on potential business, or overspending and wasting your money in the wrong places.
Boost customer loyalty and retention: When you consistently provide value to your customers, in the form of a great, intuitive app, outstanding customer support, or an excellent loyalty program, customer loyalty and retention tend to soar. Focusing your efforts on users with higher LTV will enable you to drive retention, resulting in lower churn rates, more referrals, and positive reviews.
Drive recurring purchases: LTV allows you to measure web visits or app usage per year or over your users’ lifetime. You can then use that data to implement strategies that increase repeat business.
Charge up profitability: Higher LTV leads to bigger profits. By keeping users for longer stretches of time and building a model that encourages them to spend more, you should see the benefit show up on your bottom line.
How to calculate LTV?
Calculating LTV requires a methodology for aggregating and calculating ad monetization for an app with ad revenue. For an app that monetizes largely based on in-app purchases, IAP revenue is generally much easier to obtain good information on immediately. In a subscription-based business, LTV can be calculated by dividing the average amount a customer spends each month or the average monthly recurring revenue (MRR) by the churn rate.
For non-subscription businesses such as eCommerce, LTV refers to the average total revenue from a typical customer, including all their repeat purchases and upsells over a given time period. This can be calculated as the Average Order Value multiplied by the Purchase Frequency multiplied by the estimated customer lifespan. Estimating the customer lifespan in eCommerce can be challenging as customers may end up making a repeat purchase two or more years in the future. In such cases, LTV can be estimated based on specific time frames, such as the monthly or annual LTV of a customer.
What are the use cases for LTV?
LTV is critical for several main use cases, including budgeting marketing expenses, estimating the time to recoup marketing investment, understanding customer acquisition costs and profitability, and forecasting revenue. It costs less to keep existing customers than it does to acquire new ones, so increasing the value of existing customers is an excellent way to drive growth. Each of these use cases is centered around resource allocation, profitability, and having an accurate view of the company’s ROI on a per-customer basis.