LTV is usually applied in the field of marketing. By analyzing and identifying the contribution capabilities of different life cycles and different users, LTV can make targeted cost input and operation decisions, so as to help enterprises gain strategic competitive advantages.
With the popularity of the concept of data analysis, the value of LTV has become increasingly prominent. It has gradually become an important data reference for enterprises to drive product progress and operation strategy optimization.
Overview of LTV analysis
LTV analysis is an analysis of the per capita value contributed by a group of users visiting on a specific date over a certain period of time.
Recently, the LTV analysis model of shence cloud was officially launched, aiming to help enterprises gain a comprehensive insight from the customer to the loss of the process, the sum of the business value brought by users for enterprises, and as an indicator of whether enterprises can obtain higher profits.
Shence data extracts the four application scenarios of LTV from the cooperation experience of 1500+ paying customers to help enterprises feel the value of LTV more intuitively.
(Data in this article are simulation, LTV analysis can be experienced at the end of this article ~)
I. Optimization of delivery strategy: cross-comparison of delivery quality through multiple channels
Enterprises can calculate LTV according to the behavior data of different channels, such as user order or purchase, usually select 7 days or 30 days as the analysis time, estimate the future transformation quality of the channel through the commercial value contributed by users, and decide whether to adjust the channel delivery strategy.
In channel delivery, marketers need to ensure that CAC (cost of user acquisition) is less than LTV in order to maximize ROI and achieve profitability.
The calculation formula is: ROI = LTV/CAC
CAC is a fixed value, which usually includes the total investment of enterprise operation and marketing, as well as personnel costs. When LTV > CAC, it can realize effective revenue increase.
When LTV < CAC, that is, the revenue is less than the cost, which means that the effect of the enterprise in the channel is not as expected. Marketers can optimize the content of the channel or choose a better channel according to the business needs.
LTV analysis can be performed not only by channel, but also by city and country according to specific business scenarios of the company.
2. Business empowerment decision: Analysis of the percentage of revenue contribution of multiple projects
For businesses with multiple revenue items at the same time, it is often necessary to compare the value of multiple items. Based on LTV, the business value of the project is judged according to the contribution of users in different projects.
For example, an enterprise has multiple revenue sources, mainly including user recharge, user renewal, etc. By comparing the two types of revenue as a percentage of total revenue, companies are expected to advance the assessment of business health.
When analyzing the configuration of cloud LTV analysis indicators, enterprises can select “user registration time” as the user attribute indicator, and select “App recharge behavior” and “App renewal behavior” respectively for revenue events. The profit ratio of each revenue event can also be set according to the analysis requirements. The diagram below:
FIG. 1 LTV analysis model of The Cloud
We find that most enterprises can only achieve a single dimension analysis of “event” when conducting LTV analysis, which is difficult to meet the overall requirements of enterprises in actual analysis scenarios. Therefore, Shence LTV Analysis has designed two index configuration schemes of “event attribute” and “user attribute” in the index configuration process, hoping to help enterprises achieve comprehensive insight into user value through a more scientific and reasonable analysis model and further improve the refinement of user behavior analysis.
Figure 2 trend view: View the LTV growth trend with retention duration
Figure 3 comparison view: Compare LTV with the initial date
At the same time, as shown above, the LTV analysis model of Shence Analytics cloud supports trend view and comparison view. When there is no grouping, you can directly view the revenue item indicators, total revenue situation and trend. In multiple groups, you can view the change and trend of the total revenue of each group.
Third, return to the cycle forecast: intelligent algorithm to achieve revenue outlook
How can you predict the LTV trend in the future if you know the LTV situation 7 or 15 days after the channel launch? Generally speaking, enterprises will use the existing channels LTV7 and LTV15 as reference indicators, predict the future revenue of the project based on LTV, and judge the project return cycle.
It is worth mentioning that the algorithm logic behind Shence data LTV analysis is not simple linear prediction, regression analysis, etc., relying on the real business scenarios of 30+ subdivision industries and the past five years of data analysis experience, the algorithm was optimized to create a new data model. Further help enterprises measure the real value of users over the full life cycle.
As shown in Figure 2, assuming that the CAC of the enterprise in this channel is 82, the future revenue of this channel can be predicted based on LTV7, and the return cycle = 15 days.
It is a common decision-making method for enterprises to forecast the current cycle through LTV. If the dust settles after 30 or 90 days, the value and income will be passively accepted even if it fails to bring effective growth. Therefore, based on LTV prediction, it can “predict the future” in the process of project. If the recovery cycle is too long or the recovery cycle cannot be predicted, enterprises can timely adjust their business models or product functions and optimize their business strategies.
Iv. User transformation and improvement: The corresponding time point of operation effect is clear
The LTV curve usually changes significantly before and after the start of an operation. When the campaign is on, the LTV curve increases dramatically, proving that the campaign is bringing effective user conversion. That is to say, after LTV analysis, enterprises can easily view the key time points in the operation process by comparing the horizontal and vertical coordinates of THE LTV curve, and evaluate the effect of operation activities for different label users: The actions that can bring visible profits to the enterprise should be carried out continuously, and the actions with normal or no obvious transformation effect should be adjusted in time to reduce the promotion cost and optimize the operation strategy.
We chose two different industries, gaming and e-commerce, to do a detailed breakdown, as follows:
Games companies often perform LTV analysis on multiple operations, such as advertising display, bundle purchase, skin purchase, etc., to find the best time for advertising display and the appeal of new bundle/skin to users, optimizing decisions to improve user retention and generate higher revenue for the enterprise. E-commerce enterprises can effectively judge the commercial value of users by comparing the LTV of users of different commodity categories, and adjust the pit position to improve the overall revenue.
In addition to the above common application scenario, the enterprise can also be based on the analysis of LTV positioning high value users, has connected people into god policy enterprise can a picture of the user through the similar diffusion function, get more users with high quality, but still has the potential to users and erosion marketing again, achieve user growth, drive precision touch of marketing activities and transformation with cash.
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At present, Shence analysis cloud Demo has been fully updated. Enterprises can fully understand the user value through the LTV analysis model of Shence analysis cloud, providing important reference data for advertising, sales and other business operations, accurately reaching high-quality seed users, maximizing the commercial value of users; At the same time, in the process of carrying out business based on SDAF operation framework, enterprises can effectively perceive business data and user data based on the divine policy analysis cloud, and form scientific decisions to drive the integration of knowledge and action in the operation link, so that all the roles of the enterprise can play a role in the closed loop, and realize the dual growth of efficiency and revenue. Click to experience it now