When adjusting business strategies and upgrading APP value, it is necessary to formulate clear APP North Star indicators, describe clear products to guide product direction, and calculate the benefits of each functional version. In this regard, this article analyzes the DAU goal from five aspects including the definition of DAU and the derivation of the DAU formula. Let’s take a look.

Project goal: Based on the adjustment of business strategy and the strategy of APP value upgrade, it is necessary to formulate a clear APP North Star indicator. In this way, a clear product roadmap is drawn to guide the product direction and calculate the benefits of each functional version.

North Star Index: DAU target ×××w (eg 100w, etc.)

Article framework: Around the DAU goal, discuss the data formula, disassemble the data index, find the minimum parameter value, and find out the path and plan for how to increase the value of each minimum parameter through product strategy planning.

1. Definition of DAU

Definition of DAU: count the number of users who logged in or used the APP within one day (statistical day) (deduplication statistics)

2. DAU formula derivation

1. Formula logic deduction

• DAU —— active users: Users who visited the APP on the same day
• User type: active old users + active new users, that is, [stock + increment]
• stock - old users: registered, logged in , Users who have used functions such as learning, mall, mine, etc., visit again within the statistical day, that is, revisit users.
• Increment——New users: Users who have never registered, logged in, or used the APP, if they download and log in to use the APP due to channel diversion, word-of-mouth recommendation, etc., within the statistical day, they will contribute DAU means new users.
• Inventory - old users - revisit module - retention side

eg: Product strategy: increase healthy learning depth, continue to expand beneficial learning breadth, and appropriately supplement value-added services.

2. Learning depth - active main logic

• Increase the learning time and increase the number of learning days. As a result, users are dependent on learning ability. Furthermore, a large number of visits contributes to DAU
• The depth of learning has a certain relationship with the acquisition of knowledge. Therefore, the cost of users giving up or switching platforms is high, and vice versa, retention increases.

3. Increment - new users - new modules - channel side

eg: product strategy: leverage more users to register-login-use the app, and complete the first learning behavior.

1. Increase book sales, increase book users, and increase the number of users entering APP
2. Conversion of book private domain traffic
3. Publication in public seas, increase exposure, increase user conversion
4. li>
5. Word-of-mouth referrals bring more new traffic

Therefore, the derived formula is as follows:

DAU = the number of revisiters on the day + the number of new visitors on the day

New people added on the day = number of channels × conversion rate

Number of repeat visitors on the day = user pool × retention rate

PS: Lost users have been removed from revisit retention

3. Dismantling of data indicators

1. The number of revisiting users on the same day

(1) Impact association

The DAU increase of the [Retention] module of the day ↑:

• All data are increased;
• When any 1 or 2 data remain unchanged, the remaining 2 or 1 increase;
• Any 1 or The data of 2 items increased, and the other 2 or 1 item decreased, and the increase was greater than the decrease.

The DAU of the [Retain] module decreased on that day↓:

• All data are reduced;
• When any 1 or 2 data remain unchanged, the remaining 2 or 1 data are reduced;
• Any 1 or The data of 2 items decreased, and the remaining 2 items or 1 item increased, and the decrease was greater than the increase.

(2) Growth strategy

• Expand more learning tools, learning incentives, learning depth and learning interaction product capabilities around the user's learning scenarios;
• Provide more valuable additional capabilities around user portraits;
• Attract more users to use new functions as much as possible and try more functions;
• The click-through rate and retention rate of each functional module should be gradually improved as much as possible.

2. Number of new users on the day

(1) Impact association

The DAU increase of the newly added modules on the day ↑:

The DAU of the newly added modules on the day decreased↓:

• Expand channels that can attract traffic, including public domain placement, private domain conversion, word-of-mouth referral, etc.;
• The user pool of each channel has become larger, and the operation strategy has been blessed;
• Increase the conversion rate of each channel, increase the number of users who download, register, and use APPs in each channel, smooth channel access, lower user thresholds, and increase user benefit value, etc.

Fourth, find the minimum parameter value

1. Inventory - revisit DAU - retention side

(1) Learning class

Taking video learning as an example, disassemble the minimum parameter value

① Data indicators

• Result indicators: retention rate of video learning, number of users of video learning
• Process indicators: number of APP start users—number of users exposed to the learning page—number of users who click on the scan—video Number of viewing users
• Detailed review of historical data:
  • Number of APP startup users: Sensitive data×××××Replace
  • Number of exposed users on the learning page: Sensitive data× ××××Replace
  • Scan and click the number of users: Sensitive data ×××××Replace
  • The number of users who watch the video result page: Sensitive data ×××××Replace< /li>
  • Number of video viewers: Sensitive data ××××× instead

② Data insight

• About every 10 users who start the APP, there will be about eight or nine people to use the scan function;
• About every 10 users who use the scan function, there will be 8 users enter the video result page;
• About every 10 users enter the result page, there will be 7 users enter the playback page;
• means that every 10 Among the starting users, about 4 users will use the function of watching videos.

③ Minimum parameter value

Number of users who watch videos per day = number of APP start users × conversion rate of learning page browsing users × conversion rate of scanning clicks × conversion rate of video scanning result pages

④ Minimum parameter value - growth strategy

• APP start-up users: rely on the learning plan to increase the number of start-up users
• Video scan code result page users: optimize scanning activation path
• Video playback Number of viewing users: video interactive system construction
• Number of users who like videos: the video playback page supports dynamic likes

(2) Check-in

① Daily check-in in the APP

• Result indicators: APP retention rate, APP-DAU
• Process indicators: Number of users participating in check-in, new number of check-in ( day/week/month), punch-in user retention rate, visit ≥ punch-in conversion rate

② Minimum parameter value

• Number of users participating in punching cards
• Added number of punching cards (day/week/month)
• Retention rate of punching users
• Access-> Punch conversion rate

③ Minimum parameter value - growth strategy

(3) Mall transactions

① Data indicators

• Result indicators: the number of users using the mall, the retention rate of using the mall (not yet)
• Process indicators: the number of APP startup users -- "the number of users browsing the mall homepage -- " the product details page Number of browsing users
• Detailed data of last week (2022/9/11)
  • Number of active users: 31561
  • Number of browsing users on the homepage of the mall: 5904
  • Number of users viewing the product details page: 1248

② Data insight

• One out of every five active users browses the mall, and one out of every five users browses the product details, indicating that users are still very interested in the content of the mall.
• If you can regularly continue to launch new products that users are interested in, and develop the habit of users browsing the mall, you can contribute to the increase in DAU.

• Number of users who browse the homepage of the mall: new products are launched on a regular basis, small red dots on the mall tab + dynamic effects (when new products are on the shelves)
• Number of users who browse the product details : Putting high-quality products on the shelves, putting on the shelves of cost-effective products, marketing activities, pop-up windows, banner touch

(4) Reach class

① path

Reach users through different methods → guide users to start APP (SMS, outbound call, PUSH, subscription message, applet message notification)

② Data indicators

Reaching success rate = (number of successfully reached users / number of reachable users) × 100%

User click rate = (number of user clicks / number of users successfully reached) × 100%

③ Minimum parameter value

• Number of users notified by APP authorization message
• Number of users who view messages
• Number of users who bind WeChat accounts and follow WeChat official accounts
• Mini Programs Number of message authorized users

④ Minimum parameter value - growth strategy

• Increase the number of APP authorization message notification users: message notification authorization function construction
• Increase the number of message viewing users: user group touch, custom touch message, A/B test, touch reach Data analysis
• Increase the number of users who are bound to WeChat accounts and pay attention to WeChat official accounts: APPs are bound to WeChat accounts, and APP user learning/behavior records are regularly pushed to WeChat official accounts
• Improve mini programs Notify the number of authorized users: the APP and the applet call each other

(5) Member class

① Path: Complete membership tasks → upgrade membership level → consume membership benefits

② Data indicators:

Member task completion rate = (the number of users who complete the task of each level of members / the number of users covered by members of this level) × 100%

Average membership level growth cycle = total number of membership cycles of this level/total number of users who have completed this level of membership

Average membership level = sum of user membership levels / total number of member users

Member rights consumption rate = (total consumption of member rights/total distribution of member rights)×100%

2. Increment - Add DAU - channel side

• Book sales channel - users who have purchased books - download APP on the same day - and Register and log in to use
• External traffic users - experience APP learning tools - sub-channels (private domain: small program, enterprise micro, individual micro, community; public domain: launch, application market joint operation, industry Cooperation)
• Number of referred users——Download APP——Register and log in

(1) Channels: Existing channels to reach users - enter the APP

At present, the main source of traffic is "reaching users through existing channels - entering the APP". Based on the purpose of using the purchased product, users will most likely download and register to use the APP.

① Data indicators:

② Data insights:

• Every sale of ×× items can obtain ×× natural users, which can convert ×× APP users, and the DUA of the day will increase by ××;
• The data indicators that affect DAU are: Items Changes in the sales volume, the number of users who placed orders, and the conversion rate from purchasing to registering and using the APP, these three indicators will have dynamic changes in DAU.

③ Minimum parameter value:

④ Minimum parameter value - growth strategy:

• Item sales: increase product categories, expand sales channels, increase Douyin live broadcast duration, price strategy, user reputation
• Ordering user volume: distribution, old and new, group buying, community shopping , School-enterprise cooperation
• Conversion rate from purchase to registration and use of APP: try logic optimization, material guidance optimization, shorten download path, increase tourist mode, lower the threshold for users to enter APP (tourist visit is also DAU), increase The first user low-cost task, activate the user feel

(2) Channel: private domain traffic drainage—small program

① Link: mini program guide registration-> participate in marketing activities-> conversion (purchase/receive incentives)-> APP verification (activation/exchange)

② Results indicator: APP DAU contribution

③ Process indicators: new registrations-> activity participation users-> activity conversion rate-> write-off rate

④ Minimum parameter value:

⑤ Minimum parameter value - growth strategy:

Wechat circulation drainage in the field, the mini program undertakes the conversion of user registration, obtains the complete information of the user, and then guides the user to retain it on the APP through activities.

• Increase the investment and increase the exposure of the mini program
• The design is more attractive and the promotion of new user conversion activities

(3) Channel: Public Domain Traffic Drainage —— Delivery

① Data indicators:

• Amount of users reached
• Amount of browsing users
• Amount of downloading users
• Amount of registered users
• Amount of purchased users
• Activate user volume
• Use APP function user volume

② Data insight

• For every increase of ×× number of users reaching the public domain, the actual number of app browsing increases by ×× number of times, and finally the number of users who download the app is ×× number of times;
• Users who come through the public domain For every increase of ×× person-times, it is estimated that ×× purchase conversion will occur on the APP side, and the number of users activated on the APP after purchase will be ××, and the daily learning user conversion will be approximately ××;
• Impact DAU's data indicators: the number of reached users, browsed users, downloaded users, registered users, purchased users, and activated users.

③ Minimum parameter value:

Number of APP users = reached users × browsing conversion rate × download conversion rate × registration conversion rate × purchase conversion rate × activation conversion rate × conversion rate of using APP functions

④ Minimum parameter value - growth strategy:

(4) Channel: word-of-mouth traffic - referral

① Data indicators:

• Number of active APP users: sensitive data ××××× instead
• Number of users successfully reached by the sharing activity: sensitive data ××××× instead
• Click Number of Active Users: Sensitive Data ×××××Replace
• Number of Shared Users: Sensitive Data ×××××Replace
• Number of Reached Users: Sensitive Data ××××× Replace
• Number of new users: sensitive data ××××× replace

② Data insights:

• Every ×× user will be referred once, and every ×× referral can convert 1 new user
• Data indicators affecting DAU: activity reach rate, activity click rate , Activity sharing rate, conversion rate, download registration rate

③ Minimum parameter value:

Number of referrals = number of active users × activity reach rate × activity sharing rate × conversion rate × download registration rate

④ Minimum parameter value - growth strategy:

• Number of active users
• Event reach rate: event entrance exposed, pop-up window, banner reach
• Event sharing rate: improve user satisfaction and increase sharing incentives , Share poster content to realize user value
• Conversion rate: share the attractiveness of poster content
• Download registration rate: new user incentive

5. Strategy implementation

1. Analyze the active ratio of new and old users and find the breakthrough point for DAU growth

Data analysis of the current APP is required here, and it must be proved by the data (picture omitted).

The data is simulated data:

• Current DAU distribution: active new users account for 10%~16%, active old users account for 84%~90%;
• active old users account for far Much higher than that of new users, in terms of rapidly increasing DAU, priority can be given to expanding the active data of new users;
  • Shorten the activation cycle of users who purchase items, so that users who buy goods can download the App and activate the content as soon as possible;
  • After activation, the first operation behavior and task should be simple and easy to ensure the user's dedication;
  • Let the newly activated user quickly pass the novice period and enter the exercise period.

2. Stability strategy for highly sticky and highly active users

Here it is necessary to conduct data analysis of the current APP and prove it through data (picture omitted)

The data is simulated data:

• The overall number of users in the past 30 days [time stay] is 44.98%, and the historical data shows that the time stay is stable between 45% and 48%;
• The total number of users in the past 30 days [7] Retention] 30.16%, according to historical data, the second retention is stable between 30% and 36%;
• User stickiness is good, for highly active and high stickiness users, it is necessary to adopt a stable strategy to provide more depth, The ability to interact and value points keeps users highly active.

3. Avoid the retention trap during the rapid promotion period and reduce the loss of new users

• In the process of rapidly increasing DAU, a large number of non-rigid needs will inevitably increase New users, whose retention is relatively low, need to be vigilant;
• It is necessary to add more APP capabilities that are just needed and not necessary, so that users can explore corresponding capabilities in the APP self-closed loop. While maintaining the overall DAU growth, the loss of new and old users has gradually decreased.

Ms. Echo, official account: the logic and aesthetics of a product manager; good at e-commerce front-end and back-end, knowledge payment, marketing platform, understands users and operations, has good product sense and empathy, has rich product experience in B-end and C-end, An original 80,000-word text atlas of the work "Logic and Aesthetics of a Product Man".

This article was originally published on Everyone is a Product Manager by @Echo Miss's Product Theory. Reprinting is prohibited without permission

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