Dunzo Case Study

1. Increasing Average Order
Value for DUNZO
A Product Teardown Case Study
Ujwal Pawar
Analytics Associate,
Eversana (D&A - Commercial Analytics)

2. Problem Statement
Dunzo is looking to come up with ways to get young couples and families with kids to
engage more with their platform and as a result, increase their AOV by 30-40%. Here,
you are allowed to make an assumption for the based Average Order Value while
targeting a cohort and frame your solution respectively.
Try to devise some product strategies/features or growth campaigns that will help
Dunzo increase its Average Order Value. Research user spending behaviors for grocery
and food shopping and how they differ for different dates in a month for these user
cohorts and try to build an understanding of what would work best for them.
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3. Contents
● Objective
● Problem
● User Persona Research
● Your Solution
● Metrics/Impact
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4. Objective
● To build a profitable & Sustainable business in long run
● To find ways to increase average order value as it is one of the major
factors to make business profitable
● To plan a product strategy/feature or campaign to drive the Average
order value up to make the unit economics positive and drive the
business towards profitability
Just Dunzo it!
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5. Problem
● Why problem is important?
● Problem understanding
● Towards profitability

6. Why problem is important?
● Long term sustainability of business is impossible without profitability
● Unit level profit is very important in grocery business given the thin margins
● Competition is at the both ends - cost and price
○ Cost competition is due to the partners leaving platform for another high paying platform
○ Price competition is due to users jumping on the other platform for low cost options
● Efficient use of resources is of ultimate importance
● Unit level profit simply means selling enough through each order to cover the cost for that order plus some
profit for company
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7. Problem understanding
● Profitability is at the heart of the problem
● Average order value is one important lever to pull the profitability up
● Hyperlocal model is the game of making every order profitable. This makes it very important to look at unit
economics of the business
● Three ways to look at the problem of profitability -
○ Increase value of cart everytime user checkout (AOV)
○ Decrease the freq of orders per user keeping the spendings same by letting users aggregate their orders (AOV)
○ Decrease the cost per order by buying some time from users to collect other orders in that area (Orders per hour)
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1
2
3
x Reference these numbers on the next slide

8. Slide 08/20 Increasing Dunzo AOV INSURJO 2022
2
3
1
Min Wages per hour of delivery partner
=
# Orders fulfilled per hour
Total Merchandise Value
AOV =
Total number of orders
Monthly spending per user
AOV =
Monthly # orders per user
Batch orders to increase orders fulfilled per hour-
● Expectation of every full time delivery partner is to earn at least
20,000 per month
● Considering 8-9 working hours per day and ~25 working days a
month min expected wages per hour comes out to be Rs.90-100
● If we just deliver one order per hour, which is current industry
average, we are spending 90-100 per order.
● We need to increase order fulfilled per hour to decrease the delivery
cost per order
Increase AOV by clubbing orders of each user-
● If a user spends 3,000 per month on the platform but
makes three orders across the month. So his Average
order value is 1,000
● If we help him club his orders and bring his orders down
to 2 then his average order value goes up to 1,500.
● We want to play this a little cautiously as we don’t want
user to decrease his total spendings of month while we
push him to club his orders
Selling more items to users -
● When users are adding items to cart, motivate them
by showing discount thy get if their cart value goes
above certain value.
● Win win situation for both buyer and seller
Towards Profitability
User level AOV

9. User Persona
Research
● User Research
● User Persona
○ Their Habits
○ Biggest Pain Points for the User
● Ideal Solution

10. User Research - Key insights
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● Families who bulk shop groceries like twice a month or once a month, they tend to it in local stores and not on any
online grocery platform (Almost 80%* mentioned this)
● Reasons for the not bulk shopping on online platforms are unavailability of all required products, higher prices
compared to local stores and unavailability of option to compare varieties of same food
● When asked about a scenario question having three options -
○ Many (75%*) chose to accumulate small 2-3 orders or chose to get it next day morning to avoid delivery charges
and they explained this saying that they generally tend to forget some items and end up ordering again, also
some said that they would add some regularly used items or stock up in advance for upcoming month to avoid
delivery charges.
○ Only a few (25%*)chose to go to a local shop to buy if there are delivery charges
*Survey size was just 17 respondents. So quantitative data is little hazy but directionally good. But qualitative data like reasons is strong since the respondents were given free hand to write whatever comes to their mind

11. User Persona
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Behaviour & Habits:
● Tina generally takes care of grocery when it
comes to online ordering, but Arun takes her out
when she wants to shop groceries offline
● They tend to bulk shop groceries on weekends
in local store once a week or twice a month
because they get all required groceries in local
stores and the prices are also affordable.
● Tina prefer the online platforms for buying
remaining small items during the week.
Pain Points:
● Unavailability of all the required items at one
stop.
● Prices are also high on online platform for some
commonly used items like cereals and pulses
etc
● She tend to forget many items when
purchasing online which her grocery store
owner helps her remember
Behaviour & Habits:
● Kiran and Soumya finding it hard to manage the
household tasks like buying groceries while
working in a full time job
● Kiran and Soumya use grocery apps for their
almost all grocery purchases
● They order things as and when required. They
keep forgetting many things in every order
Pain Points:
● Unavailability of all the required items
● Non availability of guide for mostly used items
Arun and Tina are working individuals living
in Mumbai with their two kids kriti & Amit
Kiran & Soumya have just married and
shifted to Banglore. Both are working.

12. Ideal solution
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1. Increasing SKUs for commonly used basic items like wheat & rice etc, increasing their availability and keeping the
various qualities & price points similar to local shops. (Solution for only pain points)
2. Helping users not to forget commonly bought items by creating a flow of purchase for weekly/monthly stock up
(Solution for profitability & Pain points both)
3. Motivate users to bulk order by keeping volume discounts (Like flat Rs.50 above Rs.800, Rs. 100 above Rs.1200 etc)
(Solution for profitability & Pain points both) (Pain point that we are solving is high prices for some of the items. If user gets some discount at the end they are okay)
4. *Motivating & helping users to club their orders wherever possible by prompting them to either choose
a. to add more daily essential items to increase order value above a threshold to make it a free delivery
or
b. let the order get delivered next day with other orders in the area.
(Solution for only profitability)
*Considering that we need to keep delivery charges for order below some threshold at least for the unit level break even if not profit. This can be applied for only irregular and historically low volume users.

13. Your Solution
● How did you ensure that you have taken a well rounded approach to the problem
● Solution Overview
● Purchase Flows
● Gamification of Discounts
● Apply & teach to avoid delivery
charges

14. Solution Overview
● Purchase flows (Solution 2 from Ideal solution) (Partial Solution 1 from Ideal solution)
○ Monthly grocery list (sorted from basics to luxury) with options of variety & brands
○ Add at least ample variety of basics like wheat & rice because that is where the grocery list
starts for most of the Indian users
● Gamification of the discounts (Solution 3 from Ideal solution)
○ Progress bar for carte value progress towards next cart value threshold mentioning the
discount
● *Apply delivery charges for irregular and historically low volume users and give ways to
avoid it (Solution 4a & 4b from Ideal solution)
○ Prompt users “We deliver every morning to your area and ask if we can push this order to
next morning. Take your time and keep adding items till then” to avoid delivery charges.
○ Prompt users to add daily essentials like milk, bread etc to increase cart value to avoid
delivery charges
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*Considering that we need to keep delivery charges for order below some threshold at least for the unit level break even if not profit. This can be applied for only irregular and historically low volume users.

15. Purchase Flows
● This can be thought of as general routine things a grocery owner suggests customers
● Step 1 : List of all these general items sorted from basics to specific luxury
● Step 2 : When user clicks on an item, as overlay should open with all varieties showing their
info, quantity, prices and button to add to cart with quantity added.
(Eg. Users clicks Rice, gets option of various brands/prices, he selects one, closes the overlay)
● This list should have some filters such as “No Pets”, “No Junk Food” etc
● These flows needs to be on the home page at prime location and should be given as pop up
to user at least once when he starts adding items to cart
● These flows can be custom made for 2-3 most common user personas
● This will immensely help users tackle their pain point of forgetting items
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16. Gamification of Discounts
● we have various offers shown on the home page but user doesn’t feel tempted to grab those.
● If we always show progress bar as overlay at the bottom of the app which tracks only the next
offer that is available at nearest higher cart value.
● This will ensure that we have that progress always showing 70%-80% always completed.
● This will make user tempted to complete that remaining 20%-30% to grab the offer.
● Eg. If we have first offer at Rs. 600 we will start showing the progress bar when user’s cart
value is Rs. 400. This will show user 66% completion directly. Once this is 100% we have next
offer at say Rs. 1,000 this progress automatically starts with 60% or more!
● This is simply utilization human psychology of loss avoidance and effective use of offers at
disposal
● This discounts can be cash or points or card payment discounts
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Add products worth Rs.200 to get Rs.50 discount

17. Apply and teach to avoid Delivery charges*
● User Segmentation is needed to implement this.
○ Segmentation - A. Low user level AOV1
, B. Medium user level AOV1
, C. High user level AOV1
(Based on past 4-5 weekly AOV values and only for users who are at least 1 month old on platform)
● We want to slowly convert A type customers to B type by applying delivery charges to them
● These A types should be pushed for either next day/batch deliveries or addition of some daily essential
items to increase cart size to avoid delivery charges. We can afford to lose these loss making customers
● Type B are our break even or above breakeven customers. We want to let these users know that we are
making this particular low value cart free delivery since they are regular and loyal customer. But still we
will ask them if they want to enjoy this benefit for their more urgent purchase. If this is not urgent they
can voluntarily push for next day/batch delivery or add some daily essential items to increase cart value
● Type C are our ideal customers we want to retain them for long. So we can give them surprise discounts
whenever possible.
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*Considering that we need to keep delivery charges for order below some threshold at least for the unit level break even if not profit. This can be applied for only irregular and historically low volume users.
1
User level AOV = Total spendings of a user / # orders of that user in a particular time frame (Preferably in a week)

18. Metrics/Impact
● KPI & Impact
● Long-term behavioural shifts

19. KPI - Operating margin
● Secondary Metrics
○ Average order value (AOV)
○ # Orders fulfilled per hour
○ Ratio of monthly spendings per user to Monthly # orders per user (User level AOV)
● Impact measurement of features [For Early signs of impact & long term impact]
○ The AOV should increase as it is the first direct impact point related to Purchase flows & discounts
gamification. Rate at which this increases will add in to the confirmation of success of feature.
○ Impact of strategic implementation of delivery charges can be measured by increase in user level
AOV and #orders fulfilled per hour (# orders fulfilled per hour will be a early impact measure)
○ Behavioural shifts in purchasing styles will be a measure of long term impact
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20. Long term behavioural shifts
● Youngsters who order every now and then are most likely to start thinking a little bit plan at least for
2-3 days before ordering. This is expected to happen when we put delivery charges and give them
options to avoid it. This charges to be put specifically based on user history.
● If we increase variety and availability of at least basics then we will be able to attract more bulk buying
natured customers. Because these customers bulk buy because they want get done and dusted for
the month in one go without any hassle. But if we are not able to provide then everything at one stop,
they will prefer offline where they get all they want.
● Purchase flows will help users shift from ordering frequently to ordering in bulk
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