Clarification questions –

1. Any specific region that we are looking at? Say US only
2. Any specific channel? Say mobile and desktop
3. Any specific time frame? Say one year

Assumptions –

1. Reviews on Monday will be on orders done during the weekends
2. Majority reviews are given by people who have ordered a product from Amazon
3. Products are delivered in 1-2 days
4. Rating is given before review in the product flow

1. Amazon.com has a logged in user base of 1 million, of which say 5 lakh place orders
2. Each user places, on an average, 5 orders
3. Total orders in an year – 25 lakh
4. Assuming majority (60%) orders are placed over the weekends, as that is when people have time
5. Total orders placed over the weekends – 15 lakh
6. Assuming each order will not get a review –
   1. Split of type of users who order – Motivated (20%), Demotivated (60%), Dissatisfied (20%)
   2. From the above lot, only the “Motivated” and “Dissatisfied” will be eager to give rating
   3. Only 10% of the users who give rating actually write a review
7. Total ratings (on all Mondays) – 40% X 15 lakh = 6 lakhs
8. Total reviews (on all Mondays) – 60K
9. Total reviews on any given Monday – 60000/ 52 = 1153

Clarify:

• US only or world wide ->  Assume US Only
• Amazon Fresh / Whole foods to be included? – No just amazon.com retail reviews

Let’s come up with an equation

# of household that makes purchases on a given day * % of users who write reviews

Let’s dig deeper:

# of household that makes purchases:

• There are roughly 300 Mil people in US.
• # of households = 300/3 = 100 Mil households

Out of 100 Mil, I’ll take 80% of the US household has ordered atleast once on Amazon.com = 80 Mil

I know Amazon’s revenue for 2019 was roughly 300 Billion and 5% of that came from Amazon Prime but that is world wide.  So I’ll choose 2% from Prime,  Which equates to 6B.  Now let’s devide 6B by 120 (Prime subscription) which gives 50Mil.

So out of 80 Mil that have used amazon.com,  50 Mil are Prime users and I would tag them as high usage (buys multiple times a week) and I would put 20 Mil as Bi weekly shoppes and 10mil as low usage (once a month)

Out of 50 Mil, I would say only 10% of the people write reviews and probably around the same for biweekly and I would not touch monthly or low usage as it would be negligible (Low engagement anyways).

Rationale for 10% : Most of the reviews are if the users are very happy or very unhappy about a product and Amazon does a good job of vetting products that are really crappy.

So that puts us at 10% of 50 Mil = 5 Mil and 10% of 20 Mil = 2 Mil and a total of avg 7 Mil reviews a week

Now, I know for the fact (I have read it somewhere) that majority of the delivery happens on Wednesday and Majority of the Orders happens on Thursday / Friday (Excluding any  holidays / deals where there is a spike through out the week)

• Given the above information, I would say 60% of the reviews are written on Wed / Thursday => 60% of 7 Mil = 4.2 Mil
• I would then allocate 10% each of reviews are written on Friday, Sat and Tuesday => 700k each = 2.1 Mil and
• 5% on Sunday and 5% on Monday which equates to 350k each since there are very less deliveries on Sunday and Monday being a working day (busy) after weekend, I would keep it at 5%.

Self Critique:  The highest number of ratings I have seen is 2000 reviews for a product and least is couple hunderds.  The patterns I have seen is that less than 25$ item gets a ton of ratings and as the price increases the number of reviews decreases.  Perhaps we could split the 10% rating for weekly and bi weekly based on average product price and then do the math.

We need one clarification in the question about the country in which the question is applicable to. As Amazon is present in most of the countries around the world, is the question applicable to all the countries put together or any specific country like India or US

Let’s assume that the question is about Amazon India.

90% of the time reviews will be given by people who have purchased that item through Amazon recently. 10% could be by people who have already purchased it outside and wanted to share their experience.

So, we I derive the average number of reviews on a day from the average number of orders and the % of users who purchase and give reviews to products using the below formula:

# of reviews per day = # of orders  per day* % of users who give reviews

# of orders per day = ((# of users who shop online in india * average # of orders per year ) * Amazon India’s market share)÷365

In india about 1/3rd of the population is shopping online which is about 400 million

From avid shoppers who shop weekly to people who shop rarely, it would be safe to assume that a user shops twice in a year online. That would make it 800million orders. Amazon India market share is about 30% . So the number of Amazon orders = 240 million.

# of orders per day = 240 million÷ 365 = ~ 750k

Usually about 10% users come back and write a review of a product that they purchased.

# of users who give review per day= 10% of 750k = 75k

Usually people have more time during weekends and tend to right more reviews than average and Monday being the week’s starting day, may see less traffic than weekends. If we assume Mondays receive only 80% of the average activity, the average number of reviews on a Monday could be equal to 60k