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Billing sample for Product Management

in this video we're going to talk about a b testing my name is kevin way i'm a product manager and i'm here to help you ace your product management interview be sure to like subscribe and hit the notification bell for new tech interview prep videos every single week a b testing is a scientific way for tech companies to make decisions that impact user behavior product managers often heavily rely on this kind of experimentation to help validate their product decisions a b testing questions are often asked in the analytical rounds of pm interviews for example you might be asked what experiments would you run to incentivize users to post more on instagram here are 5 steps that make up a perfect a b test interview answer step one hypothesis for any a b test you propose tell your interviewer what your hypothesis is what are you trying to test your answer might have a framework like if we make change x then it will impact y for example if we remove likes from photos on instagram then maybe more people will post photos step 2 methodology now that you have a hypothesis you need to discuss how to run the experiment typically you'll want to run the experiment against two cohorts of similar users we'll call these users in the first cohort our control group these are users who will see exactly the same experience today with no changes we'll then call users in the second cohort the experiment or the test group these are the users who will see the change you're proposing in our example the test group will be users who don't see likes on photos on instagram a big component of a b testing is defining who the experiment is targeting are you targeting all users on the platform or is there a single segment of users to test it's important to be precise your interviewer needs to understand what exactly is being proposed and what the experiment setup will look like step number three metrics now that your experiment is set up you'll need to tell your interviewer which metrics you'll be measuring what metrics will actually convey useful insights to the team in our example you'll want to obviously track the number of photos being posted but there might be a few other metrics that are worth mentioning like the bounce rate of sharing a photo or click-through rates of other buttons on the app you might also have a guardrail metric like ensuring time spent on the feed doesn't decrease too much if users can't see likes step number four trade-offs every experiment has trade-offs what are some potential pitfalls to launching your proposed feature that might not immediately be evident with a purely data-based analysis perhaps by hiding likes people feel more lonely since they don't know how the community around them is engaging with the content qualities like loneliness or user delight are not easily captured via metrics and might be missed in an overly quantitative mindset so if it makes sense be sure to call these out step number five impact at the end of the day running an experiment just tells us information it's up to you to tell your interviewer how this information will actually be useful to the team perhaps the results of this experiment will drive some bigger vision you have for the product these are the insights that will separate a junior pm from a more experienced pm and there you have it five steps to give the perfect a b testing answer in your analytical interviews i hope this helped paint a picture of what an experiment looks like for more pm interview prep content exponent has the best resources to help you ace your interview including in-depth courses private coaching and a community of experts ready to help you prep for even the toughest questions hit that subscribe button for more tech interview prep videos every single week and go to tryexponent.com to become a member today thanks for watching [Music]