You are PM of Medium and you notice some fluctuations in % of active users. After 3 weeks of monitoring, you notice one morning that the % of active users drop by 35%. What would you do to figure out the drop and how will you restore it?
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Clarify:
- What is the timeline frequency of the active user we are talking about here? Is it D, W, M Interviewer: D
- What do you mean by active users? Does it mean people who have logged in and opened a session irrespective of the time they spent on the platform Interviewer: Yes
- The fluctuations seen earlier in the active users were positive or negative or both? I believe the fluctuation was in +/- < 1% and that is why we did not look at it in till now. Interviewer: Yes
- Is the absolute number change is significant as well as sometimes the population is low and percentage change is thus huge Interviewer: Yes
- Was a drop seen on any specific channel - Mobile(IOS/Android)/Web? Interviewer: All
- Was the drop specific to a particular geography? Interviewer: USA
- Seasonality: Did we see the drop last year as well during this time? IVR: No
- Any recent change in the way we measure the metric? No
- Any recent retirement on promotions campaigns? No
- Do we see change in any other metrics other than #/% daily active users?
- Is it specific to a particular user group? Readers, Posters IVR: Both
- Do we see change in the number of posts as well or is the drop related to readers only and by how much ? IVR : we see a change in both but do not have specific numbers
- Are new users able to sign up and do we include the new users in the active category? Yes
- Any drop in new users sign up? No
- Any chnages in the content exposed to google search crawlers? If this is the case, it is possible that people who are conducting a google search do not see relevant content from medium and thus do not go there. The organic/inorganic search numbers should also be impacted if thats the case IVR: No
- Did we do any recent changes in the past three weeks related to UI that makes people unable to see sign in pages. We should be able to verify it with unique no. of ip address visiting medium should not have dropped. If thats the case, it depcits that users are visiting the platform but not able to sign in IVR: We do not make any recent UI changes
- Did we see any recent problems with AuthN/AuthO - No/# of errors in signing in must be up IVR: Yes, we do see a spike in AuthN errors
- Could it be due to mediums identity solution? Any changes there IVR: No
- It could be due to SSO platforms like google, facebook not allowing users to go in medium. I would like to see the numbers for users who use SSO and granularity with google and facebook sign on individually. IVR: Bingo. Google API key was not updated and we see the numbers match with the drop.
- So it means that all the users using google sign on in USA were not able to login using their G profile. IVR: Yes
- Any issues with third party servers? IVR:No
- Google page rank changes
- Any regularoty issues with gov putting sanctions or statements against medium in the US
- Bad PR - medium sued or bad advertising leading to a backlash
- Major event in US and people do not have time to post/read on medium
- Elections
- Protests
- Communication system/Internet Services Down
- New competitor launched or existing competitor luring users via promotions, advertising, influencers
- Some major influences on the medium platform left? As a result the followers of these do not go to medium as they have lost interest
Identification and segmentation of cause for user-churn:
1. Demography (IP locations having the most increased churn by comparing with past data)
2. Ethnography (age, likes, profession)
3. User Agent (Browser info, OS , Android App, Web-App)
4. A/B split testing (whether a new feature integration has led to UX problems)
5. Decline in Content-wise user interaction (any topic which is unsuitable or not creating a good user interaction)
6. HTTP errors displayed (technical, web-page unavailability)
Metrics:
1. Bounce rate
2. Pageviews
3. Reduction in Referer vs Organic vs Social search links
4. no. of sessions
5. average sessions duration
Part 2: Problem Analysis -
After analysis of Medium Web analytics it is found that the cause of regular churn is due to:
Demography - Users from Metropolitan cities are not visiting much now.
Ethnography - People who are relatively young having affection for Product management are the churn
User-Agent - No. of users who use Mozilla Firefox and Android OS is lowering.
A/B Testing : The new feature where you can form a group of people having same likes as yours is not working as per the intention. ~ 35% churn is due to this maybe.
HTTP 504 Gateway Error (Error of 5XX represents server side error)
Metrics - Reduced no. of sessions
Part 3: Solution-
Demography - Some other blog website is becoming popular as metro people are most aware about copetititors - Competitor Analysis is required
Ethnography - Source more interactive writers from Product community
User Agent - Android team needs to roll out a new bug-fix feature update which is correlated with Error 504 and sessions reduction problems.
A/B Testing : The new feature does not create instant notifications on phones of group members instantly. Now A/B test again with instant notifications insertion.
Clarify that there are 2 problems that we are solving - "some fluctuations in % of active users" & "sudden drop of 35% of active users"?
Let me start by focusing on the biggest problem today which is the sudden drop of 35% of active users. The timing of the sudden drop is very curious.
Medium is a blog where content is published and consumed. It is fair to rule out that there are big changes in the number of articles published by publishers.
I would also check if this has happened in the past to rule out seasonality. Perhaps 35% is too big of a drop because there is very less change of seasonality impacting content publishing businesses.
Was there any technology change or outage that might have causes this? Let us assume that there were no major features (or) outages.
Now, it might be best to discuss the metrics –
- Analysis of the sources of traffic – direct (browse & search in site), referral (from other sites), search (from google, bing, etc.), campaign (marketing ads), social networks
- Can we isolate the problem of drop in traffic to particular region?
- Is there drop in registered users (or) guests (or) users able to login.
Our goal is to analyze any change that might have impacted the page ranking (indicated by drop in search traffic), drop in traffic by direct search on medium, end of any marketing campaigns, drop in users being able to login to the site to read the articles etc.
Once we are able to identify the reason for 35% sudden drop. We can investigate if the fluctuations in recent time was caused by the same issue (or) the fluctuation is in the normal range.
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