Author: Analysys senior digital marketing manager Zhao Yan
App After just on the line, a lot of room for improvement, the initial experience with the product function is to create, without user verification, we will, through multiple product iterations, to adjust details, helping App product optimization through analysis of user behavior, allowing users more willing to in our App orders.
Most products when updating, by the experience pm or a small number of survey questionnaire, the lack of data in support of such an iterative fashion, product optimization driven by user behavior analysis, the user can know more stop on what features, or know which functions are not user-friendly, this approach will be more optimized product basis, the effect is more obvious and easy to see.
I will introduce two parts based on data analysis of user behavior driven App product optimization, which are optimized ideas and practical operation case.
Optimization idea:
When the product is no basis for comparative data, we will be in a few aspects of the data analysis of the product obtained basic data, basic data set can then be based on growth targets, an App to give priority attention to what data?
1, understand the user's use of product features
Through intelligent understanding of the path from the user to trigger events to open the App on the App understand all user interactions, depicts every step of the behavior of users with intelligent route;
2. Focus on conversions core funnel
By conversion funnel analysis focuses on the core of the funnel, such as the user from the open app to the shopping cart to submit orders funnel wastage;
3, concerned about the use of the product of a single function
By event analysis, a single track on a new feature;
4, concerned about the user completes the core objective of total sex
5, the user physical differences in the updated version
6, a cross-dimension data analysis by subdividing, insights beneficial results, the iteration drive.
Next, we need growth plans based on current data to clarify the direction of product optimization, such as raising ADD TO CART conversion of orders to pay, you can complete the following steps.
1, through the funnel analysis to understand ADD TO CART conversion of payment orders
2, insight into the different versions, the conversion rate between the different provinces, different systems (Andrews, the IOS)
3, to develop conversion rate optimization test
4, App iteration
5, the data validation iterative effect, retention winner
Case:
App purchase coffee dismantling of some online user behavior analysis to target users buy coffee at the core
Home construction, divided into several functional areas, the most important thing is now single, followed by coffee wallet, you can see these two parts is the most important feature, so the top priority position, send out more direct show you can support the take-away service.
I was thinking to figure:
I am a user of this App, App through this understanding, I think there will be as follows, initiate want to give more App optimized to provide some ideas. The basic idea is to understand what the user experience on their App, how to provide users with a better product experience through user behavior analysis.
1, what I expect users to complete on my App?
Purchase orders and vouchers, under the SLR made for secondary actions, once the purchase coupons, order becomes a subsidiary of action in order to achieve a coupon carried out.
I need to know the user experience on the App situation through intelligent path to understand the user experience through product will be what path
From this we can know the path, the user will be the next one to buy coupons and frequent shuttle between, and frequency of use may (according to the total amount of events) above 80%
2, build the core funnel, understand user behavior
Selected from the several paths inside the funnel analysis
Funnel 1: Open the app, the next single, Add to Cart, pay.
Funnel 2: Open the app, purchase coupons Add to Cart pay.
Funnel 3: Open the app, the next single, Add to Cart, use coupon payment.
Funnel 4: Open the app, click on the ads, confirmed the landing, to share, to return. (This logical question was not clear how to get concessions, physical examination more confusion)
Through this funnel analysis, we know that user behavior on the App, to know usage and wastage of users, perhaps advertising a particular coupon, hindering the user to purchase a coupon or order, or one of our processes can be simplify greatly improve the conversion rate.
3, find the optimum point
The optimization campaign to improve the conversion rate of users buy coupons core objectives, priority user sort the data situation clear path and the current path, after starting from the distracting, the beginning of growth from product optimization test assumptions.
Conventional growth:
a, coffee wallet inside pages
Your coffee wallet a little lonely, increase direct purchase button
b, charged by discount
Replaced buy coffee coupons, test results CTA CTR
c, advertising fast switching
May cause click-through rate is not high
d, preferentially select button Delivery
Reduces operating procedures, provide conversion
Fission growth:
a, open screen advertising increased CTA
There is no CTA, CTR needs to be improved
b, free to Friends of coffee, have a cup each
Test functions, giving priority to the logical explanation, can increase the risk of sending them
……
Ten model Analysys Ark Argo, you can play a relevant role in the different stages of product optimization time, you can learn more about the Analysys Fangzhou Guan network.
to sum up:
Based on user behavior analysis, data analysis, drive product optimization, several steps away
First, understand their own situation data
Second, find the features users care about and do not function like
Then, find the core funnel
Finally, around data growth targets, hypothesis, on-line verification.
Welcome to the data analysis needs of small partners, free use of Analysys Ark Argo.