How does data drive consumer value?Focusing on this topic, Liu Yang, General Manager of the Brand Retail Division of Sensors Data, shared a complete experience from three aspects: operational challenges, value propositions, and solutions.
1. Challenges faced by data-based operations
At present, many enterprises are faced with confusion about how to use data. In this regard, I believe that the data use of enterprises can cover the following four scenarios:
1. Data and global services are connected. The amount of brand data is huge, there are many types, and it exists independently, forming a data island, which is not really related to the stuck points of the business link, and needs to be connected with the business action.
2. Make business insights through data. Multi-dimensional data analysis, combined with business models, data modeling, analysis of the ins and outs and development trends of data in each business link, and evaluation of business health, i.e., sustainability.
3. Collect data in a targeted manner. Platform TA data quality analysis and evaluation, quantitative and qualitative data types, accurate data burying, selection of appropriate data tools, targeted collection, twice the result with half the effort.
4. Sift through valuable data. There are many channels for data, and it is necessary to remove the false and keep the true;Filter data from key business scenarios, core populations, important channels, optimal paths, and effective feedback.
So how to break through the data dilemma and achieve efficient use of data?There are four steps to start with:
First, user value stratification and portrait insight. Quantitatively analyze the user life cycle, value stratification and crowd portrait to find the target group.
Second, insight into the path of crowd transition. Through in-depth insight into the proportion of different segments of the population, we can find and formulate operational strategies suitable for this group.
Third, operational strategy coverage and factor insight. Based on the comparison of different groups of people and operation strategies, find out the key factors that affect their transition and conversion.
Fourth, the iteration and comprehensive precipitation of operational strategies. By building an operation strategy library and adopting various forms such as data-based operation accompaniment, the implementation of data in business scenarios is realized.
At the same time, we believe that the core of enterprise digital transformation should complete the construction of data system, party system, operation system, and marketing automation system.
The core purpose of the implementation of all the above strategies and systems is to turn massive data flows into business cash flow, and the three-engine product system proposed by Sensors Data based on Customer Journey Orchestration (CJO) brings value to this business goal of the enterprise.
2. The value proposition of Sensors data-based user operation
Different from traditional user operations, data-based user operationsWith "people" as the core, with the operation goal of "deep link stock management, reducing churn, promoting repurchase and cross-marketing".With consumer market penetration, target consumer wallet share, and loyal consumer marketing efficiency as the core operating KPIs, we achieve long-term growth of consumer value by improving LTV.
However, it should not be ignored that enterprises may also face pain points such as lack of policy system coverage of user journey, breakpoints in user journey, lack of effective policies, and lack of evaluation of policy effectiveness in the process of data-based user operation. How to deal with it?Enterprises can use marketing strategies to enhance users' positive perception of the brand through marketing strategies at key points in the customer journey. Therefore, enterprises need to look for key points at different stages of the customer journey to help users build their minds, so as to achieve long-term value improvement.
For this,Based on CJO, Sensors Data proposes the Mtaoo formula** to help enterprises locate the pain points of the journey and accelerate the implementation of digital operations.
Map:Detail every interaction between the enterprise and its customers, form a journey map by role and business, and accurately show how different customer groups experience the product and the process of stage migration.
Track:Identify the key touchpoints in the customer journey, and integrate data from various channels (such as apps, mini programs, WeChat Work and other scenarios) to establish a comprehensive customer touchpoint recording system for enterprises and complete the construction of an integrated multi-digit data infrastructure.
Analyze:Set key metrics based on different stages of the customer journey and conduct in-depth data analysis to diagnose journey continuity to identify pain points and potential opportunities for improvement.
Orchestrate:Based on data analytics, strategically orchestrate customer journeys based on the value of different customer segments to ensure the right content is delivered at the right time, through the right touchpoints, to further enhance customer experience and value.
Optimize:Continuously monitor changes in key metrics and dynamically adjust customer journey orchestration strategies to ensure that customer journeys are always optimally guided and optimized.
3. Digital operation solutions based on brand business understanding
Based on the CJO concept, Sensors Data helps enterprises break through the dilemma of the user journey, and achieve business growth and value creation by accurately targeting the people not covered by the strategy, expanding the audience with effective strategies, and optimizing the cost strategy.
Specifically, Sensors summarized the implementation path of the user operation strategy system, including six major links.
1. Stratification of user value
Fundamentally, through life cycle + RFM stratification, enterprises can cluster members with the same growth rules, summarize the growth stratification threshold, and achieve the goal of refined operation and full coverage of members.
Among them, the core thing to do is to optimize the overall efficiency of effective marketing expenses, and clarify which links to invest in marketing expenses have a higher ROI. Only by completing user stratification can enterprises make the strategy more grasping, and finally realize the refined operation of "thousands of people and thousands of faces".
2. Portrait and preference insight of segmented groups
Through algorithms and clustering, we can gain insight into consumer behavior and preferences, select groups with the same characteristics, mine effective marketing strategies for them, and study the influence of strategies on such groups.
3. Insight into the transition path of the segmented population
By gaining insight into the proportion of people who "increase frequency" and "increase amount" in different life cycles, we can find suitable marketing strategies.
4. Insight into the coverage effect of existing operation strategies
Through comprehensive insight into consumers' time preferences, channel preferences, and product preferences, we can understand the differences in the effectiveness of operational strategies for different consumer groups5. Further find the factors that affect the effect of the strategy
Through insight into the population coverage of existing strategies, the landing effect and feedback of different strategies, the implementation of strategies is compared and the effectiveness of the strategies is verified.
6. Strategy adjustment and effect review
Strategy effectiveness and crowd coverage are usually "seesaws", which require continuous effect review, and adjust and optimize the strategy through indicators such as strategy GMV, strategy crowd ARPU value, strategy ROI, strategy conversion rate, and number of strategy participants, so as to optimize the global ratio of limited resources.
Finally, through the above steps, enterprises can easily precipitate a user lifecycle operation policy library.
As a professional digital customer management software provider in China, Sensors Data has a highly open product architecture and flexible integration capabilities, a digital customer management solution, and a complete data security and compliance system.