Apxor strongly believes that Product-led growth is one of the most sustainable growth models. Vision of Apxor is to help build products which can propel themselves up in the path of success through product-led growth.
In an effort to inch closer to our vision, we launched a series of open discussions for the product people, where in product experts will be sharing their experiences.
In our first open discussion we were joined by Doubtnut's Rohan Rajan, Head of Data Science, and Vamshi Velagapuri, Product Manager, for an interactive discussion on blitzscaling growth ladders through rapid product experiments. They shared insights on their unique product positioning and customer interface best practices. They outlined with examples and statistics, how rapid product experiments are performed to gauge customer response to newly introduced product features. They also elucidated various metrics used to track product growth and also talked about the tools used by Doubtnut.
The session started with a product introduction and then proceeded in a lively Q&A format, with varied questions posed by the audience, expertly answered by the panelists and ably co-ordinated by the Apxor mediators.
Here are some Questions & Answers from the session:
Q: What does Doubtnut do differently from other apps, that has helped it achieve success so quickly?
Gist of the answer: Among the multitude of online educational tools and apps available in the market, Doubtnut positions itself uniquely. The idea behind the product is to bridge the precise gap in the student’s understanding. Clear doubts as and when they occur, instead of offering general educational course content. So that they move from weakness to confidence in the subject.
To ensure that the product is successful, every person in the team is assigned a metric, and is supposed to move the needle for every change they make.
Q: What is the process to identify Power users for any app?
Gist of the answer: Doubtnut first needed to figure out their Aha! moment to understand their power users. They found out that those users who are asking 3-5 doubts a week are going to stick to the app and use it repeatedly.
Q: Can you give an example where data driven feature was created and what was the process, how we come up with that?
Gist of the answer: One data driven feature developed by Doubtnut was the camera feature. They optimized the number of times the camera screen should open immediately on app open, by running repeated experiments and analyzing the inputs.
Q: What is the difference between user retention of an e-commerce app and an edtech app?
Gist of the answer: A regular e-commerce portal like Snapdeal or Flipkart might be happy if the customers return to the website, say 4 times a year. However, for an educational tool like Doubtnut, user engagement must be at least once a week. Otherwise, it implies the user is not deriving enough value, and will simply fade away.
Q: What are the important metrics for edtech?
Gist of the answer: Metrics to define goals of successful product deployment need to be defined clearly and unambiguously. For instance, an online training course could measure attendance levels as a key metric. Whereas for Doubtnut, number of questions answered per student would be the critical metric. All product experiments must be tuned towards achieving this.
Q: What is the core habit loop for Doubtnut?
Gist of the answer: For Doubtnut, its core use case is asking doubts. If a person comes to the app with a doubt, it clearly indicates that the person has a weakness in that area. Hence, more videos and explanatory material are shown to the person, until it is ensured that the person's doubt is cleared.
Q: Can you please share some of the interesting insights from the User Surveys that you have conducted?
Gist of the answer: User feedback collection is the most challenging aspect of product experimentation. Which user to ask, what method to use and how often to collect feedback – are the important considerations. Doubtnut panelists said that most effective way to reach out to customers and take their opinion without emotional baggage, was through in-app surveys. Using in-app surveys they could reach millions of users instantly and gather their opinions.
Apxor team would like to thank the panellists and participants for making the first open discussion hosted by us lively and fruitful. We promise to keep up the tradition and invite several other thought leaders and product specialists to share their valuable insights. We hope our humble attempt helps in enhancing product intelligence and building successful products.
Contact us to know more about using Apxor to perform Rapid Product Experiments. If you have any product related queries do drop a mail to firstname.lastname@example.org or use #askapxor in LinkedIn or Twitter. We will address your queries.
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