tell me about a time that you solved a pain point for customers [Music] hey everyone we're here today with amit to do a product management mock interview uh before we get into the mock interview um could you just tell us a little bit about yourself sure thank you stephen for having me here um i'm a second year student mba student at mit sloan right now prior to sloan i work my most of my experience has been working with early stage and tech startups in india where i transitioned to product management and after my mba i'm
heading to amazon as a technical product manager awesome thanks and today in this market review question we'll be doing a interview question that's sort of similar to the amazon uh more behavioral focus type interview questions um so in today's question what i'd like to ask you ahmed is tell me about a time that you solved a pain point for customers so the just to give you some context my first job was with a startup called trypoint in india this was a chain of tea retail stores similar to kind of what starbucks is here we were
trying to do it with chai in india and i was leading marketing there and as part of marketing one of the goals that i had for that quarter or one of my important goals was to launch a mobile based loyalty program and in order to do that i was i wanted to understand what are the kind of features we would build so i was doing some user research in order to do some user research i was visiting stores i was talking to customers in stores and one of the things that i identified was that while
a lot of customers felt that a loyalty program would be good i realized that there were some much deeper and bigger pain points they were having with the core experience their experience in the store itself and that was that the queues at the store were just huge especially during rush hours and so that's the problem i identified and here's what i did about did about it uh the first thing that i did was really try to understand what was happening was it an operational issue was it like a training issue so observing what was happening
talking to a few customers and just being at the store i realized um the big pain point was payments uh there was a lot like payments were taking a lot of time at like just to give you a sense the average ticket size was like 50 cents uh in u.s terms so credit you so we didn't have credit card or debit cards at that time and most of the people were paying using currency and at that time digital payments were not popular so and there was a big problem of tendering change at that time so
that was creating a lot of chaos at the counter uh and really like we were aware that something was like this was happening i didn't know how bad how uh how bad experience this was leading to with that insight i kind of went back to my team and i discussed that you see this is the problem uh this i feel is like a much bigger pain point and is there something we can do with the loyalty program can we try to address it and one of the team members at that time proposed how about launching
a digital wallet how about where customers can come and pay using qr codes and at that time like just to give you a current idea like this right now it's pretty popular common uh pain and using qr codes at that time it was a completely novel concept no one in india at that time was doing it but as but i did more research around it and uh talking to my team and like doing some understanding from the engineers like how feasible it is i realized like we can develop something like this something of in a
basic format and it would have been very hard to develop a few years before but now it's like it's more easy to develop so uh got an understanding that this is something that could be done and next i went to some more senior stakeholders in the company i was reporting to the ceo and they were like the ceo uh everyone involved and i propose to them like look this is a much more serious pain point and after talking to my team i realized that we can actually rather than launching a loyalty program we can actually
build a payments app where customers can load money onto their wallets digital wallet and pay much more quickly and efficiently so yes so there was some reluctance on their part uh it was not easy to persuade any everyone at that time but i aligned slowly i worked through their uh whatever their concerns were and i was able to align them and the result was that i was able to convince them to launch a pilot uh in one single store so for two months we built a very basic mvp if you can say and launched it
in just one store we were tracking a couple of metrics like how many people downloaded the app and how many how much it reduced the average transaction time uh the result of the pilot was after about six weeks that uh we got about thousand downloads at that store for the pilot it was for it exceeded what we were expecting and the wait time came from 40 seconds to 20 seconds yeah on average and then we rolled this app across all the stores over the next six months uh and within a year 25 of all the
companies revenues were coming through this program so uh not only this helped solve a big customer pain point uh it helped shape the whole direction and digital strategy for the company for the many years to come so this is a story that i wanted to share and happy to go into any of the elements that you want to discuss about totally well thanks for sharing that story really fascinating different take on a type of story in general and it sounds like it had a really big impact on the team which is awesome thanks um yeah
so i i guess like i i you mentioned um convincing stakeholders i'd love to dig a little bit deeper into that like how did you go about persuading people that the idea that you had was the right one for the product and for the team sure um so there was there's definitely a lot of uncertainty even i was not sure that this was the right idea and it would some it was something that would work uh i would say like at that time the stakeholders like everyone was aligned that this was an important problem they
also to their credit felt very excited that you know this is something that's new and they wanted to test out something new the genuine concern was at that time there were two concerns one was like will people actually use it there was no precedent like no one was using qr codes at that time for payment and like we were not a big chain you know we were like a small startup doing something so will people really use it that was their concern and the other big concern which was i think a much bigger and real
concern was that all these solutions had to be integrated with pos the point of system the billing machines and on in the stores and these are really bulky heavy software like they i remembered you know their downtime was 30 30 of the time the machines would never be talking to back talking back to us it was down like so uh the concern was like you know the if this doesn't work this might actually end up creating even even worse experience for customers so these were all really important points and the way i thought about like
the way i resolve those concerns was first like in terms of thinking like how do we get people to use it i propose like i don't know the answer to that but what we can do is actually launch a small pilot will not know until we do that so we can do a very very low cost pilot i've talked to my team and like the app should not take more than about six to eight weeks to build out the simpler version and rather and we can make it really low risk so we can just roll
it up roll it out to one to two stores they and they felt like this seemed like the right strategy so uh i was able to get people on board about this the second one it took me a lot more i had to do a lot more homework on the second one to solving the complex technology piece i had to talk to the post providers i had to understand like i had to actually convince some other people in finance to upgrade the pos infrastructure at store so we bought better machines we installed better wi-fi we
installed better software so there was some cost involved in doing so but uh because everything was just at a small scale at a pilot scale people were not really concerned about like shelling out a lot of money so got it got it so the the pilot sort of helped you be the canary in the coal mine to figure out whether or not this is going to work and then you scale it up um i i guess i'm curious to hear a little bit more about so so you ran this pilot where were the were the
metrics really good when you ran it was that sort of what was convincing after that yeah so we were tracking two metrics as i was saying like number of people who download they have to give a sense of are people willing to use the solution to the thing that this is something that will be helpful for them and second was like how much it reduced the average transaction time how much it reduced the actual problem of rating uh of payment so was the solution really working at all and i and the way it happened the
weight evolved over those six to eight weeks was that uh there was a very strong high adoption like this was a good enough problem and we were able to come up with right messaging that there was a lot of downloads but i think it took us some trial and error to get the the the average transaction time to get down from 40 seconds to 20 seconds for people who were transacting there was some difficulties we faced but we solved them through iterations can you tell me a little bit more about what those challenges were and
how you solve them sure so some of those simple challenges were like this was 2015 i guess or 14 i don't exactly remember so it was some time back and one of the challenges was like you know we didn't end so this needed internet connectivity on users mobile phone to work and those were and there were some people were working using 2g at that time like and so those are some of the things that i didn't anticipate like and because of those lags it was taking a long time and so one of the things that
we had to do was like as a temporary solution installed wi-fi devices at stores but also there were like a lot of minor ux issues like it was very very the onboarding experience was really cumbersome there was so much friction like for people to load money for people to like create accounts so we simplified all of that and that took a lot of iterations like doing those minor minor changes uh was something that we we we fixed over that course of the time got it yeah that makes sense um i guess i'm also just curious
you mentioned the metrics that you evaluated like what sort of like can you tell me about the role of metrics in launching this product and maybe some metrics that weren't as useful that you thought were going to be useful and why you pick the metrics that you picked sure um so i think we picked like a bunch of metrics to pick uh one to answer your first question why we use metrics was i was very clear going into this that this is an experiment that's how i convinced everyone that see this is going to be
an experiment and when you run an experiment you need to either at the end of the experiment you need to tell that you know you were able to prove or disprove your hypothesis so metrics played an extremely important role and we said like okay we are going to look at these three or four metrics and we are going to say that if we get more than 500 downloads that means the solution is working so that was exact and we define a metric and we defined certain threshold and those thresholds were like i didn't do like
i didn't build like huge data models to come up with what those thresholds were but it's based on some quick estimation like how much traffic we were getting we said like okay based on the traffic that we were getting if 10 of people would download the app that's good enough for us so uh that's how we kind of define the metrics and their thresholds um some of the other metrics that i was also tracking i wanted to track was how like around how frequently people would be using the app once they downloaded it what the
ticket size on that those metrics would be how much are they spending like what's the revenue that we would we would be getting so i think those were useful metrics to track just to keep an eye on but in terms of proving this hypothesis is wrong or right those were not as useful as the first two one that i talked about got it got it that makes sense um so i guess maybe uh just a tangential question i have for you is if you were to redo this experience like what what have you learned and
what would you do differently from from how you launched that yeah i think i'll just say something that i feel i'll start with something that i feel i did we did well overall i think it was just to kind of show we we didn't waste a lot of time in terms of designing experiment or like thinking a lot about it we launched it quickly and we got it off we i mean like i think having that bias for action was extremely important and that helped kick start this program having said that i feel like i
could have done a little bit more research around thinking about all the edge cases like i uh things that can go wrong so for example one of the things that i had not anticipated about were potential security concerns or like fraud uh fraud scenarios that could come up uh once this experiment started what we started seeing was that because people were loading money on their digital wallets and then using qr codes some users some customers started taking screenshots of their pr code and started circulating it and i had not at all anticipated that and that
led to some fraud cases that led to some difficulties in accounts reconciliation at the back end and uh so i would going ahead i would still like to operate at that pace but at the same time think about certain edge cases think more exhaustively around like what can go wrong even if i don't intend to like take action or build solution for them in the first version i just like to keep that in mind and keep everyone informed about that yeah that makes a lot of sense it's hard to catch all those things but yeah
it does sound like an insight there is just learning that you can anticipate some of the challenges earlier on as opposed to finding out last minute yeah yeah um awesome well i i do want to uh start to get towards the feedback section but you know if there are other um points or interesting areas of this story that you'd like to share we'd love to hear any other aspects of it before we we have like a couple minutes before we move on to the feedback part uh i think we covered most of it i think
this was one part this is one small thing which i feel like helped me align stakeholders more closely and it's to do something with the understanding the human element uh you know uh behind what goes on building these kind of products so one of the things that i knew was the ceo who had the loudest voice amongst everyone he was a big fan of starbucks and what i knew about and when i was doing my research is starbucks had launched something like this and knowing that you know if i presented that story to the ceo
he would be persuaded a lot to kind of develop it and like back this so understanding what motivates each of those individual stakeholders help you kind of move the product vision ahead uh and that's a lesson that i've carried on even late in later products that i have worked on yeah it makes a lot of sense was there something specific that you did that you want to share about knowing the intent of the stakeholder that you positioned really well so he loves starbucks he's be he talks about starbucks all the time and one of the
things that i did was actually talk to him about like just share some data around what are some of the metrics around this program was around starbucks loyalty program was how many users it has a lot of the features it was using and i think that that kind of convinced him that this is a similar direction we should also follow so just sharing that data was like uh kind of pushed him a little bit in that direction got it totally makes sense um all right awesome interview on it um we can take a deep breath
and sort of transition now from the interview stage into sort of just talking about the interview and talking about how it was for you and maybe any tips and things like that um so before i jump into some of the notes that i wrote down about what made this interview really really awesome i would love to hear just a little bit of your self-reflection what do you think went well what would you change within this interview yeah sure i think what went well why why i generally like this story is that not only it's like
a very relevant story in a product management interview it's also especially for amazon it kind of highlights multiple of their leadership principles like customer obsession ownership bias for action earning trust uh so i generally like to so so so one thing to keep in mind is like try to pick stories which can highlight multiple of these leadership principles uh what i find generally challenging is that while you know i lived through this experience so it was very clear and vivid in my mind uh it's always a challenge to balance like being concise versus making sure
you are describing everything in detail so that's something that i find challenging and maybe you can give more feedback on like how i did there uh or what are the areas of improvement on that front got it yeah um yeah totally great points and and i did think one of the most effective parts of this interview is how clearly it demonstrated some of those principles and you didn't really have to explicitly call them out like it's not like oh this is the thing but you you you clearly had done your research and thought about it
and thought about this example as it relates to those values and so you were able to bring that into your interview really effectively um so just some notes that i wrote down on what i thought really went well um so i thought you did a great job setting context so sometimes interviewees will jump in really quickly into problems without providing necessary context and so there were a couple times you caught yourself even you were like oh the past is like pos oh by the way point of sale um you know to make sure that people
understood where you're coming from because not all interview interviewers will know the exact context and i thought that was like particularly effective because you were talking about an example in india where you know as a person who's living in america right now like i don't know what the state would be like i don't know how the qr code ecosystem is and so it helped to ex exemplify the aspects of your accomplishments that were really really remarkable right um so i thought that was an excellent job with context setting throughout the interview um i think that
overall you had a really conversational and friendly tone um and that was really helpful like it put me at ease i felt like we were talking brainstorming and kind of just talking about a product it wasn't so stiff you were very like casual but um at the same time it was clear that you had really had expertise and you could easily answer questions you could dive into any topic that i threw at you so i think that that almost is the exact sweet spot of how you want to come in these interviews is you want
to come in with a casual sort of friendly attitude comfortable attitude while also being very confident and being able to speak to anything that comes up um i would say that there yeah and i think this maybe could help to the point that you're saying about like how much to talk i think a little bit of like structure around the experience might have helped a little bit so you could introduce it very late on but it's like oh yeah phase one was the pilot phase two was this thing and then phase three was analyzing the
results or something um or or breaking it down into components because that just helps me as a interviewer know where to dive into a little bit more you know and then you can actually it's actually a smart tactic on your part as an interviewee to break it down like that because then you know sort of how i'm thinking about it as an interviewer and i'll probably dive into those specific topics um i i thought overall i didn't i wasn't lost at all in your interview but providing a little bit more of the structure around it
could help uh guide the interviewer which helps guide your answers sure great that's a great feedback and i think this is something to do with like what you were trying to do and how it came across in my mind i was trying to do it phase wise but maybe explicitly calling it out that first i did this and second phase was this and third phase i think totally makes sense yeah it's funny how like something as simple as a name to that thing like phase one actually provides a ton of logistical clarity and i sort
of got that you were doing that that's why i'm giving you this picture absolutely um it's like oh yeah just like make it a little more explicit and just call it out a little bit right and i think it could be really awesome and yeah i mean i think overall it was this is like your personal experience it's clear you had a lot of i thought your discussion on metrics was really thoughtful um and so i i thought you really aced this interview overall um so it's clear why you got a job at amazon because
you're really excited at some of these interviews yeah yeah great any thoughts or reactions to anything that i just said or any other additional tips things that you want to share with folks watching this video sure so i think i'll just share a couple of tips for generally prepare preparing for amazon product interviews um i don't know how amazon product interviews are for everyone but especially for mba grads uh and amazon recruit a lot of mba pms uh the most of the focus about a 75 to 80 of the focus is on these kind of
stories so out of the four interviews i had three were like just stories and one was like standard product interview and the really what helped me uh prepare well for these interviews were two things so one tactical things when you're preparing your stories try to prepare in the standard start format uh situation one two three phases phase one phase two phase three and then results and when you're trying to say results uh do it in a very concrete data driven way like speak out data don't just say like i improved sales but say i improved
sales by 20 over this period of time so having that star format and being very concise in each part is very explicit in each part is important the other thing is that uh it's very important to be very thoughtful about your stories and make sure every story ties back to one or two or more leadership principles and understanding what the leadership principles really mean like for example customer obsessions in terms of amazon means uh not just talking to customers or identifying their pain points but even more importantly identifying those needs which customers are not even
talking about going how do you dive deeper into that so thinking about your stories thinking about an experience and like thinking how you would type those specific experiences to your stories so i think those things generally helped me prepare for amazon interviews and finally just doing few mocks like specifically with people who had either cracked amazon interviews or people who work at amazon i think that gives you a lot of lot a lot of good perspectives totally great advice on it um yeah i agree with a lot of what you're saying and i think it's
it's definitely almost a different beast of an interview sometimes the um which is challenging for people um awesome well thank you so much ahmet for taking the time to be on the show it's been awesome having you um contribute and help other people in the exponent community um and good luck to those people who are watching on your upcoming interviews you
