The convoluted game of 'hide and seek'
Analysing the other spectrum of platform applications, doing a product brainstorming session, and more.
Welcome again! Today we'll talk about the information exchange in platform applications. We'll discuss the psychology and the thoughts that go behind deciding this display of information. We have a product brainstorming case as well, so without wasting any of your time, let's start.
Zomato - Swiggy, Uber - Ola, Google Pay - Phonepe - Paytm are some globally recognised duos and trios that have captured a great portion of their respective niche India. Tech companies that operate like platforms have to hold both the ends and sometimes all three ends (customer, provider, executioner) to maintain the market fit and increase adoption. Look at Zomato; they must be having three different app versions - one for the consumers, one for the delivery agents and one for the restaurant owners. It's not very easy to maintain three versions of an application and control the knowledge and information flow in all three; in fact, it's quite tricky.
Let's do a product brainstorming session, and you will understand why it's tricky to design rules for platform application:
Interviewer: Can you find out why food orders are getting cancelled on our platform? The ratio of cancelled orders/ orders has been increasing.
Interviewee: How do you define order and a cancelled order? Also, what's the time duration and nature of this drop (sudden or gradual)?
Interviewer: Order is any order done via the app and confirmed by the restaurant. Cancelled order is any order which is cancelled post the confirmation from the partner restaurant. The decline has been sudden and happening for the past 45 days.
Interviewee: Great, can you tell me some specifics from your database? Is the problem location specific? Is it happening only to us, or is it present across all food delivery partner solutions?
Interviewer: Thanks for pointing these out. It's a location-specific problem - limited to Hansganj (Tier-3 city) only, and it's only happening to us.
Interviewee: Very helpful. Can you tell me if the rise in cancellations is across all kinds of restaurants or if only some specific ones are getting affected? Also, do we have any numbers or percentages on what fraction of cancellations are done by Users vs Delivery Partner vs Restaurants?
Interviewer: We face this issue for all kinds of restaurants, and cancellations mostly come from restaurants.
Interviewee: Are there any specific kinds of dishes for which we are seeing an increase in cancellations?
Interviewer: No
Interviewee: What's the average delay after which orders are getting cancelled? What's the average time taken by the delivery agent to reach the restaurant after accepting the order? Are we witnessing any lags here?
Interviewer: We are seeing instant cancellation of orders from the restaurant side ( 2-3 min after accepting the orders). Most of the delivery people are on time to pick up the orders.
Interviewee: Let me get this straight. Restaurants are cancelling orders 2-3 mins after accepting any order.
Interviewer: Yes
Interviewee: Let's draw some inferences here. There is definitely some information flow/ activity happening post order confirmation that are nudging restaurants to cancel orders. I will try to come up with some possible hypotheses:
Orders are not getting retrieved correctly after confirmation (System Issues)
App crashing shortly after accepting booking (System Issues)
Any information that's available after accepting an order is nudging the restaurant to cancel the booking.
Interviewer: We checked 1st and 2nd, and there are no issues there. Let's drill down on the 3rd point.
Interviewee: Can you tell me what has changed in the post-booking confirmation recently or maybe in the last 45 days, the day we started observing a hike in cancellation.
Interviewer: We updated our app 60 days ago and made some changes to the booking confirmation page for the partner app.
Interviewee: What exactly were the changes?
Interviewer: We started showing the customer's full name (First Name + Last Name) on the booking confirmation page instead of just the First Name.
Interviewee: I am not sure if this change could have affected the cancellation number but keeping in mind that this is a Tier-3 city, and external factors can easily mix with businesses and personal relationships.
Interviewer: I get your point. So what do you propose?
Interviewee: I will check some external factors that may have impacted the business. Did restaurant owners had issues with communities of certain kinds in the past 60 days in this region?
Interviewer: There was a communal fight around 50 days ago between two communities A and B. Most of the people belonging to community A are restaurant owners.
Interviewee: I think we have our conclusion. It has been 60 days since the app updates, and 50 days ago, the fight occurred, and we started seeing a drop after this.
Let's take a moment to think about how slight changes in the home screen or any screen can create a difference. Platform apps have to be very sharp before making any changes to any stakeholder's application.
On a similar note, let me ask you a question:
What are the details you expect on a booking confirmation page for the driver's app of Uber/ Ola? A driver confirms the booking of a rider, then what details do you expect to show up on the booking confirmation page?
Let's list them one by one:
Rider location.
Rider distance from the driver's current location.
Rider's rating.
The number of riders.
Approximate cost of the ride.
Mode of payment.
Drop-off location for the rider.
Drive-length.
Drop-off location - Ride demand.
Drop-off location distance to driver's current location.
This list can go on and on, but the tricky part of the question is, out of the above-listed data points, including which data point in the booking confirmation page you think could impact business the most. Take your time and think.
The answer is the drop-off location for the rider.
Have you ever had any experience with Uber where you book a cab, call the driver, and the driver asks you your location? You tell him, and the next thing you see is your ride is cancelled on the app. In India, for most of the tier-1 and tier 2 cities, Uber doesn't show the drop-off location for the rider application unless you are there at the rider's location (Although in Delhi, NCR drop-off location is available for the rider's application).
The reason is simple, to avoid cancellations on the driver's side. They don't want to travel to places where their fuel economy will take a hit. Uber/ Ola drivers just have the option to accept or reject the ride based on the rider's location. Driver side cancellations are kept to a minimum by hiding the drop-off location of the riders. In Delhi NCR, it would be unfair for the drivers to accept the ride without knowing the drop-off location of the rider since the city is so big. So enabling that feature does make sense in a city so big.
That’s it for today’s edition. I am really fascinated by this other side of the platform application and would love to hear your opinion on the same, reach out with your ideas at understandingnuances@gmail.com, we promise we will share your ideas with due credits.
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