Product Case Study | Improve Retention | Housing.com : Pay Rent
About Housing.com:
Housing.com is India’s most innovative real estate advertising platform for homeowners, landlords, developers, and real estate brokers. The company offers listings for new homes, resale homes, rentals, plots and co-living spaces in India. It also offers other services like Rent Agreement, Pay Rent, Home Loans, Property Management, Legal Services etc.
Pay Rent:
Pay Rent is an online rent payment product by Housing. Users can pay their
house/office rent every month using their Credit Card.
Problem Statement:
80% of the Pay Rent’s payments come via App. Remaining from website.
Given below is the retention cohort for Pay Rent:
What should we build this quarter to substantially improve our retention
cohort?
Data Interpretations:
(Assuming that M1, M2 and M3 users are from the same segment of users who made the payment in the first month)
→ On an average 36% users stop using pay rent after making the first payment
→ Out of remaining users, 66% stop using pay rent after using for two months i.e., 30% drop
→ 32% users stop after three months usage
→ Maximum churn is seen after two months of using pay rent
Hence, if we focus on solutions for retention of the users after the second month, it can make a huge impact on the overall retention cohort. Since 80% of payments happen through mobile app, we will focus on improving the app for the time being.
Possible Reasons:
Some of the possible reasons for customer churn (based on the app’s Google Play Store reviews) can be:
- Slow runtime : Most common reason given was that app was too slow or it hanged quite often. The transactions take a relatively longer time to complete.
According to an Apteligent survey, almost 50 percent of consumers say they would uninstall an app if it “regularly ran slowly”
- Lack of other payment options: UPI, Debit card, etc.
- Lack of customer support: One of the ways to improve customer retention is to swiftly resolve customer queries. In the app no instant customer support window or chat box is given. The users are required to write mail or contact directly via phone for that, which can be quite irritating and cumbersome.
- Other competitor products: like Cred or NoBroker
- Less lucrative offers: The rewards might not be lucrative or interesting enough to make customers come back again and again.
To prioritize which problems to solve, we can take help from the table below:
As we can see from the table, making the app run smoothly via backend improvements , improving the reward system and having a great customer support have the highest possibility of reducing churn.
But since backend improvements are a never ending process and require much effort, we will focus on solving the reward system and customer support.
Solutions
- Payment Streaks for improving the reward system
- AI Chatbot for improving the customer support
Payment Streaks
How it will work:
- When a user pays rent for a certain period of months consecutively, a streak is formed.
- After a certain period, they reach a milestone in which they unlock huge and exciting rewards.
- If the streak is broken, i.e., user fails to consecutively pay then they will have to start all over again.
In our case, we can set the period for the first milestone as 3 months i.e., if the user pays for 3 months consecutively, they reach their first milestone. Since the users have already paid for two months, they will pay for one more month so as to unlock their milestone. After that, milestones can be created every 3–4 months.
The rewards can be anything like huge cashback or heavy discount offers based on the profit margin.
This will add a sense of curiosity in the users and once they have paid for 3 months, a habit is formed and they are less likely to move to other platform or stop using our platform.
Wireframe:
Performance Metrics:
- Completion Rate: Number of users who complete the streak
- Retention: Users who do consecutive payments after the introduction of payment streaks
Chatbot
This is an in-app 24/7 AI chatbot for instant customer support.
- The small issues and FAQs which don/’t need calling or mailing the customer support can be resolved via this bot.
- If the user needs further assistance, the bot will connect user to an agent within a few minutes.
According to Hubspot, 90% of customers rate an “immediate response” as important factor when they have a customer service question.
Wireframe:
Performance Metrics:
- Activity Volume: frequency of usage of chatbot, number of users using the chatbot, etc. .
- Bounce Rate: Sessions that fail to get the intended use of the chatbot
- Retention Rate: Users who have used the bot repeatedly
- Goal Completion Rate: Number of total queries solved by the bot
Disclaimer: This case study was part of an assignment and the solutions are for educational purpose only.
Thankyou for reading!
