In the previous article, we saw that Sensors Analytics can support the problem analysis process for different business roles.
Here, we take the e-commerce industry as an example to introduce how Sensors Analytics helps business personnel in product, operations, and channel placement to quickly conduct data analysis.
Standard e-commerce core processes
E-commerce users typically go through the following core behavioral processes:
- Launch App
- Start browsing the homepage
- Click and browse the product details page
- Once you see a suitable item, add it to your shopping cart.
- If you intend to purchase, submit an order.
- Decide to make payment, pay for the order.
The core product process can be described as follows:
Launch the App - Browse the homepage - Browse the product details page - Add to cart - Submit order - Pay for order
Common Data Analysis Problems in the E-commerce Industry
In the specific work of the e-commerce industry, channel placement personnel focus on the quantity and quality of customers acquired through each channel, operations personnel focus on how to segment users and conduct targeted operations, and product personnel focus on the conversion of each core process and the user experience of each function.
We will list the main analytical requirements as follows:
- How many new customers are acquired through each promotional channel? Which channel has the strongest customer acquisition capability?
- Are there differences in the behavior of users from different channels from app activation to order payment?
- What could be the reasons for user churn during the payment process?
- What can I do about losing users through payment services?
- How can we comprehensively monitor the quantity and quality of new user acquisition across all channels?
Let's now learn how to find the answers to the questions above one by one.
Sensors Analytics Solution
View the number and proportion of new customers from each channel.
First, we want to understand the customer acquisition capabilities of each channel, and then calculate the ROI based on the advertising costs.
In Sensors Analytics, we can do the following:
View the total number of new customers, and then drill down by dimensions such as date and channel.
View the proportion of new customers acquired through each channel to the total number of new customers acquired.
View the core process conversion rate of users across different channels
Examine the overall conversion rate of the core customer acquisition process across various channels, as well as the conversion rates between each step, to identify areas for improvement in the overall conversion rate.
Multi-dimensional analysis of user payment behavior from various channels
In the previous question, we saw the conversion rates of users from various channels towards the product's intended target behavior. At the same time, we also hope to obtain more data to evaluate the quality of customer acquisition across channels.
View the conversion time from app activation to order payment for users from various channels.
Examine the distribution of average payment order amount and total payment order amount among users from different channels to determine the impact of channels on users' spending power.
Analyze the reasons for user churn during the payment process
Payment is typically a targeted user behavior for e-commerce products, but a significant number of users inevitably churn at this stage. We want to understand the subsequent behaviors of users who churn during the payment process. Is their payment behavior affected by interference from other stages?
Sensors Analytics allows users to view the historical behavior sequences of specific user groups, identify order submissions, and manually annotate subsequent behaviors to infer why payments were not made.
Analyze user activity from various channels
We want to understand the activity level of users from various channels, as well as the frequency of the target behavior—payment order behavior.
View user activity across different channels
Observe the frequency of payment order behavior of users across different channels
Obtain the list of churned users
We want to obtain a list of churned users to implement targeted marketing to specific groups. Sensors Analytics supports syncing a list of specific user devices to JPush/Xiaomi, enabling precise in-app push notifications to churned users in order to reactivate them and win them back.
Comprehensive monitoring of the quantity and quality of customer acquisition through various channels
If channel business personnel want to comprehensively monitor the channel's performance but don't want to reconfigure the metrics one by one each time, Sensors Analytics supports adding the analysis results to the overview, allowing business analysts to quickly obtain the status of the metrics they are interested in without having to configure them.
This allows you to build an overview of channel analysis, helping you quickly understand the current state of channel performance.
This case study helps you quickly understand a simple analytics scenario, involving Sensors Analytics models such as event analysis, funnel analysis, retention analysis, distribution analysis, and interval analysis. You can further explore more features. For more advanced scenarios, please refer to industry practice examples to learn more about use cases and advanced usage techniques.
The above data are all simulated data; please refer to the e-commerce demo. Experience. The next article will answer the question, "Where does Sensors Analytics' data come from?"