Product Analysis / Product Management for Laundry Marketplace App - JUST CLEAN, A Kuwait based startup. The home screen of the app is very critical part of User Experience and with data analysis and qualitative analysis we will see how we can guide the product management in the right direction.

1. JUST CLEAN
Sales Business UX
Marketing Growth Feedback
A CASE STUDY ON

2. Series of Releases
Funnel Analysis
Scatterplotter- Linear Regression Models
Order and Win- Event Tracking
Other App Metrics
Q U E S T I O N 1

3. SERIES OF RELEASES

4. FUNNEL ANALYSIS
Laundry List
Laundry Selected
Pay
Drop off Rate = (Y/X) * 100
Conversion Rate = (Z/X) * 100
X
Z
Y

5. MEASURING PERFORMANCE OF THE SCREEN
Drop off Rate
ConversionRate
The scatter plotter shows a negative correlation.
We, from visual analytics perspective can say that
the drop-off rate at Laundry List screen has
negative implications on the overall conversion
rate.
The hypothesis we make is that increase in the
Conversion Rate is inversely proportional to the
drop-off rate. This can be visualized as a scatter-
plotter and a linear regression can be applied to
verify the hypothesis.
The validation of the linear regression can be done
via. Calculating R square. If regression holds good,
the value of R square is close to 1 (After taking care
of outliers and confounding variables).

6. MEASURING PERFORMANCE OF THE SCREEN
BounceRate
Loading Time
To further measure the performance of the
screen , we will establish a relationship
between Loading Time and Bounce Rate.
It has been researched that about 85% users
leave within 4 seconds of loading time. Thus,
Loading Time is one of the critical UX aspect.
We will be interested in knowing that whether
Just Clean users are bouncing because of
never ending Loading Time.
The adjoining graph used as reference can be
read as: Higher the Loading Time, higher the
Bounce Rate (Positive Correlation)

7. TRACKING EVENTS- ORDER AND WIN
Track the Order and Win Button
on Laundry Listing Screen:
Tracking the number of taps on this button will
help determine the "Interest Over Time". We can
correlate the taps on the "Order and Win" button
with the increase in sales and CLV.
The positive correlation between the daily number
of taps and average daily basket size can give
business the right indicators to continue in
putting the efforts in the way most needed and
most effective
When we roll out new features inside the "Order
and Win" campaign or check its profitability for
the overall business, we can do the same analysis

8. OTHER APP METRICS WE SHOULD MEASURE
Measuring Engagement Measuring App health
Daily Active Users
Monthly Active Users
Customer Retention using Retention Cohorts
Average Session Duration
Install Rate
Churn Rate
Adoption Rate
Crashfree Users Percentage

9. Qualitative Research- Heat Maps
Other Research Methods
Q U E S T I O N 2

10. It let's us about behavior and attitude of
users. We will use tools generating heat-
maps for:
Taps
Scrolls
Screen recordings can be researched to
understand the customer behavior at a
micro-level
QUALITATIVE RESEARCH
Heat Maps

11. OTHER QUALITATIVE RESEARCHES METHODS
Customer Interviews that are
Purposive and Well-defined
Creation of User Personas to further
know the customer needs holistically
Review Analysis of Laundries
Taking customer Feedbacks
Sentiment Analysis of Live Chat and
Social Media interactions

12. Short Term Recommendations
Retouching the UX
Medium Term Recommendations
Long Term Recommendations
Q U E S T I O N 3

13. RECOMMENDATIONSSHORT TERM
UX NEW FUNCTIONALITY BUSINESS
Other Recommendations:
Fix the content issues in T&C of "Order and Win". With all humility, "We Wash You Win sounds more cool"
#1 Apply the "Social Proof" as an e-
commerce principle further, by
showing the Reviews for 5 recent
orders . Social Proof helps customers
take decisions quickly
#2 Auto-pick the customer location
and map it with Just Clean Area List.
Or, if possible, give a customer an
option to auto-fill the address using
the current GPS location. This will
reduce the barriers / pain points,
because we all know that no-body
wants to fill long forms
#1 Minimalist Approach for
defining each laundry in listing
screen. Laundry Logo, if it is too
important can be shrunk . The text
can be squeezed further.
Assumption: Less Cognitive Load,
Less Load Time, Clean Design
#2 Reduce the over-usage of
multiple colors at places as it
compromises Von Restorff
Principle
Each laundry is not enough
separated from laundry below in
the list (Law of Proximity)
Increase the brand-awareness
further using AppStore /
PlayStore Optimisation
Keep tab on Paid and Organic
Acquisitions
Keep tab on cost per install

14. RETOUCHING THE UX

15. RECOMMENDATIONSMEDIUM TERM
UX
Enrich Laundry Images and
other media
NEW FUNCTIONALITY BUSINESS
Customer Referral as it will
increase the Word of Mouth
Marketing of Just Clean. From
looking at the app it seems that
Word of Mouth Marketing is at
the centre place of the Marketing
Strategy, so pushing it will be an
added advantage
Rope in more Laundries and
standardize them. They can
later be categorized
Social Login to increase logins,
re-logins. It will be easy for the
customers to start off with
experiencing the app
Filtering the laundries based on
Minimum order, Delivery Price
payment modes, Order and Win
applicability

16. RECOMMENDATIONSLONG TERM
UX FUNCTIONALITY BUSINESS
Give option / Show English user the
translation of Arabic Reviews and
vice-versa
Segment Laundries for their
specialties. Like "Best Laundry for
Traditional Clothes"
We can have Just Clean Prime for
Premium Customers
Agreement with the clothing brands
and give concession on such brands.
The idea is to create a synergy and a
win-win situation with other players
in the ecosystem
We can contact Factories,
Corporates, Hotels to have a B2B
arrangement with us
Apply the gamification principles
further to drive the user
engagement.
Create Customer Tiers and give
avatar for each customer

17. Q4: INTRODUCING IN SDLC
Be Agile! Today, Tomorrow and Always!

18. Q5: EVALUATING SUCCESS
To evaluate success, we have to take care of the below things:
Pre-Release we will calculate the KPIs that we think can be improved after
releasing a new functionality. This will involve Benchmarking
Post Release we have to recalculate these KPIs that we had set and
compare the difference.
We will also analyse how these KPIs affect the Primary Business KPIs (
Increase the avg. basket size, Increase the re-order rate , Increase in
retention)
The most fundamental/ generic / broader daily KPI should be "No. of clothes
washed in a day".
We should see how these KPIs trickle down and a very specific KPI
enhancements lead to enhancement of a generic/ broader KPI. This
requires working with Decision Trees
Keeping note of above points will help us in evaluating success.

19. LAST: CEO CONUNDRUM!

20. LAST: CEO CONUNDRUM!
Ideally, any suggested requirement that leads to a strong hypothesis creation is worth
implementing and move through the process cycle shown in the above slide.
However, if CEO thinks a requirement is cool, we should still investigate it and with all
our professional ethics.
Some requirements can be out of the scope of the data that we may be collecting and in
such case it will be advisable to perform:
Market Research
SWOT Analysis
Competitor Analysis

21. DON'T DELIVER
A PRODUCT.
DELIVER AN
EXPERIENCE.

22. THANK YOU!