Onboarding project | Swish

Ideal Customer Profile

1.About Swish

Swish is a food delivery app designed to provide swift and reliable meal options, ensuring convenience and satisfaction for urban professionals. Known for its seamless user experience, Swish integrates technology to optimize delivery speed and offers a curated menu tailored to diverse tastes. Founded by industry experts passionate about transforming the food delivery landscape, Swish emphasizes customer delight and operational efficiency. Its standout benefits include tailored recommendations, transparent tracking, and user-centric features, making it a go-to solution for time-conscious food enthusiasts.

Core Value Proposition

The core value proposition of Swish is its ability to provide lightning-fast (<=10minutes), reliable, and hassle-free food delivery, tailored to meet the needs of time-sensitive urban professionals. Swish simplifies meal choices with a curated menu, transparent order tracking, and seamless user experience, delivering meals swiftly while maintaining quality and convenience. It positions itself as a solution for users seeking efficient meal delivery without compromising on taste or reliability.

2.Understanding Users

Defining ICPs- Who is signing up?

B2C Table

Criteria	ICP 1	ICP 2	ICP 3
Name	Aaryan	Sia	Megha
Age	25-35	18-25	30-40
Demographics	Male	Female	Female
Need	option to quickly fulfill food cravings during work	Need quick yet tasty option to satisfy hinger cramps during study hours, don't want to waste much time	can't cook quickly to meet cravings of kids
Pain Point	Caught up in hectic office culture, doesn't plan much in ahead and realize hunger only when its at its peak	Student mostly caught up with assignments, classes or preparing for exams. Late night study sessions alone or with friends	Working moms juggling between catering the priorities of office and home sometimes skip cooking and order food
Solution	10 minute food delivery	quick resolution of hunger	on demand delicious and healthy food to delight kids
What do they watch	OTTs- Netflix, Prime, social media- Facebook, Instagram, X; news- Inshorts, Ride- Rapido, uber, payment: paytm, credit cards	OTTs- Netflix, social media- Snapchat, discord, Instagram, podcasts, ride- rapido, metro, paytm/phonepe	OTTs- Netflix, Prime, social media- Facebook, Instagram, Ola, uber, paytm/phonepe
Perceived Value of Brand	Delivers food fast, popular in startups. Perfect for in-between meals	deliver delicious food fast, at low cost	Delivers healthy food fast
Marketing Pitch	"Busy startup life? Let Swish fuel your hustle with quick, delicious meals delivered straight to your desk—no time wasted, just great food."	"Need a break from textbooks? Swish delivers your cravings straight to your door, fast and fresh."	"Juggling work and kids' cravings? Let Swish handle the mealtime madness with quick, delicious meals delivered whenever you need them—so you can keep everyone happy without the hassle."
Goals	convenience and time-saving by receiving meals quickly	diverse, tasty food options and time optimization by receiving meals quickly without planning well ahead	alternate to home food, quick and tasty food options on demand
Frequency of use case	2-3 times a week	2-3 times a week	1-2 times a week
Average Spend on the product	500	250	500
Value Accessibility to product	accessible	accessible	accessible
Value Experience of the product	High	High	Medium

3.ICP prioritization framework:

Criteria	ICP 1 (Young professional)	ICP 2 (Student)	ICP 3 (working moms)
Adoption Curve	Low	Medium	Low
Appetite to Pay	High	Low	High
Frequency of Use Case	High	Medium	Medium
Distribution Potential	High	High	Medium
TAM	High	High	High

What do we observe here?

We are prioritizing ICP-1 (Young Professionals) because they exhibit the highest potential for both adoption and frequency of use. They have a high appetite to pay, which means they are more likely to engage with a service. The distribution potential is also high, as this segment often operates in environments where word-of-mouth and social networks can quickly expand the app's reach. Additionally, while all three ICPs have a high total addressable market (TAM), the combination of a high willingness to pay, frequent use, and a broad network makes ICP-1 a more attractive target for initial focus and growth.

JTBD and validation

Customer Journey Map

We have created below journey to understand what are our customers trying to do.

3.User Goals and JTBD and validation

To understand why our ICPs are using the Swish app, we have noted down their user goals and JTBD of Swish users.

*We have color-coded JTBD and interview table in order to link user goals with actual user interviews

Goal Priority	Goal Type	ICP	JTBD	Validation approach	Validation
Primary	Functional (quickly fulfill food cravings without disrupting work)	Young Professionals (prioritized ICP)	Save time and stress on food ordering and delivery	User interviews (user-1*)	“I love how I can get snacks and coffee delivered while I’m stuck in meetings. It saves so much time.”
Secondary	Personal (fulfill food cravings without stress)	Young Professionals (prioritized ICP)	secondary research (reviews on app store and google play)	"Lunch breaks are so short, but Swish makes it easy to get a full meal delivered without stress"
Primary	Functional (quickly fulfill food cravings without disrupting studies)	Students	User interviews (user-3*)	“Swish has been a lifesaver during late-night study sessions. I can grab snacks or a quick meal without leaving my desk!”
Secondary	Personal (fulfill food cravings without stress)	Students	secondary research (social media reviews)	“Affordable and fast delivery makes Swish perfect for a student budget and schedule. It’s always on time.”
Primary	Functional (quick and healthy food options on demand for kids)	Working moms	User interviews (user-2*)	"As a working mom, Swish helps me get meals quickly when I’m too busy to cook. The options are great, and delivery is reliable"
Secondary	Personal (fulfill food cravings for kids without stress)	Working moms	secondary research (social media reviews)	"When my kids crave something unexpected, Swish makes it easy to get food delivered fast without extra stress.”

Documentation on user interviews:

We spoke to 6 users from different backgrounds and have documented the learning in below table. Luckily we got a chance to speak to churned users as well. We are keeping the names anonymous to save the personal information.

User	Insights	Age	Gender	City	Role Model	Type of User	Living Condition	Occupation	Hobbies	Personal Goals	Professional Goals	Weekly Spending Habits	Monthly Spending Habits	Yearly Spending Habits	Spends Time During Week or Weekend	Source of Awareness	Trigger to Use	UX Experience	Natural Frequency	Do They Have Notifications On?	Natural Frequency Before Deletion	Reason for Deleting	Have They Deleted the App?
User 1	Frequently orders snacks during work breaks.	27	Male	Bengaluru	Elon Musk	Frequent	Lives alone	Software Engineer	Gaming, cycling	Stay fit, eat healthy	Achieve promotion	₹1,500	₹6,000	₹72,000	Weekdays	Social Media Ads	Mid-day hunger cravings	Positive experience	4-5 times per week	Yes	1-2 times per week	App was buggy during peak hours	No
User 2	Orders family meals and quick snacks for kids.	35	Female	Mumbai	Priyanka Chopra	Family-oriented	Lives with family	Marketing Manager	Reading, gardening	Spend more quality time with family	Build a successful team	₹3,000	₹12,000	₹144,000	Weekends	Word of Mouth	Busy work schedule and family needs	Very satisfied	2-3 times per week	Yes	N/A	N/A	No
User 3	Orders budget-friendly meals during study breaks.	22	Male	Delhi	Virat Kohli	Price-sensitive	Lives with roommates	College Student	Watching cricket, coding	Balance studies and leisure	Get an internship	₹500	₹2,000	₹24,000	Weekdays	University Flyers	Affordable meal options for students	Neutral	1-2 times per week	No	Rarely	Costlier than peers	Yes
User 4	Orders health-focused meals after gym sessions.	30	Female	Hyderabad	Serena Williams	Health-conscious	Lives with friend	Fitness Trainer	Yoga, running	Maintain fitness and diet	Start a personal fitness brand	₹2,000	₹8,000	₹96,000	Weekdays and weekends	Fitness Influencers	Post-workout meal needs	Highly satisfied	3-4 times per week	Yes	N/A	N/A	No
User 5	Orders during late-night cravings after long hours of work.	29	Male	Pune	Mark Zuckerberg	Occasional	Lives with friends	Product Manager	Watching movies	Maintain work-life balance	Launch a product feature	₹1,000	₹4,000	₹48,000	Weekdays	App Store	Hunger cravings late at night	Neutral	1 time per week	Yes	N/A	Limited options during night hours	No
User 6	Orders food for casual hangouts with friends.	25	Female	Kolkata	Alia Bhatt	Social	Lives with family	Graphic Designer	Sketching, traveling	Travel to new places	Build a design portfolio	₹1,200	₹5,000	₹60,000	Weekends	Instagram Ads	Food sharing during weekend plans	Positive experience	1-2 times per week	Yes	N/A	N/A	No

Onboarding Teardown

Please find onboarding teardown below

Swish- Onboarding Teardown.pdf

Activation metrics

Parameters to track your activation metrics:

Hypothesis 1: Place 1 order in 1 hour of signup

Reason: Choosing "Place an order within 1 hour of signup" as the activation metric for Swish makes sense because it captures immediate value realization, leveraging the user's high intent during the critical first hour. It indicates that the onboarding flow effectively demonstrates the app's value, reduces drop-offs, and drives early transactions, which are directly tied to revenue and retention. This metric also highlights any friction in the signup or ordering process, providing actionable insights for optimization. For a quick commerce or delivery app, this aligns perfectly with the need for immediacy and convenience, encouraging habit formation and user loyalty.

Why 1 hour? Core ICP- Young professionals and Students are busy with work/studies, even if they sign up , they might miss ordering right at the sign up, some time will also go in discovering the app. So keep all these factors under consideration, 1 hour is a feasible time for first time food ordering.

Hypothesis 2 - Addition of credit card on platform

Reason: The addition of a credit card to the platform is a strong indicator of retention because it signifies a user's intent to transact and their trust in the platform's security. This step reduces friction for future purchases, making it more likely for the user to engage repeatedly. Furthermore, having a payment method saved increases the likelihood of impulse buying and simplifies the checkout process, fostering habit formation and long-term engagement with the platform.

Hypothesis 3 - A user who refers Swish to a friend within their first 30 days of using the platform is likely to retain on the platform.

Reason: A user who refers Swish to a friend within their first 30 days is likely to retain on the platform because referrals indicate a high level of satisfaction and trust in the product. When users recommend a platform, they invest social capital, which strengthens their emotional connection to the app. Additionally, the act of referring often leads to rewards or incentives, encouraging further engagement and use. Referrals also create a network effect, as users are more likely to stay on platforms where their friends or social circles are active, further boosting retention.

Validation

Since Swish is in PMF stage, but transitioning early scale soon, we will look at 3 things for validation:

Q1 - Commitment - Does the metric demonstrate user commitment? (retention)
Q2 - Value realization - Does user realize value from the current product? (referral, WOM)
Q3 - Conversion - Does metric affect conversion? (ARPU or LTV)

All three need to be "YES"

Hypothesis	Question impacted	Valid/invalid
1	2,3	Invalid
2	1,2	Invalid
3	1,2,3	Valid

Metrics to be Tracked

Qualitative

Metric	Explanation	Which Questions does it answer?
App downloaders	Are Swish visitors coming from referral and WOM or SEO determines if they are realizing value	Value realization
Social Interactions	Sentiment analysis-How are Swish users portraying Swish on social forums such as reddit or Linkedin or Product Hunt. We'll check App store/play store reviews	Value realization
Backward customer journey	Mapping customer journey backward through click maps, heat maps, session recordings and scroll maps to understand what actions customer is taking and whether we can improve any part of onboarding	Conversion, Value realization
Onboarding Funnel (TOFU, MOFU, BOFU)	Using funnel analysis tools like Mixpanel or Amplitude. Segment users by source, campaign, or persona to identify specific pain points. Are the customers clicking through products categories, adding to cart and doing payments	Conversion

Quantitative

Metric	Explanation	Which Questions Does it Answer
Website visitor to app download ratio	Tracks the effectiveness of driving app downloads from the website, viewed on a cohort basis with time intervals (D1/D7/D15/D30).	Conversion
App Store/Play Store impressions to download ratio	Evaluates how effectively the app listing converts impressions to downloads, identifying areas for improvement.	Conversion
Page-by-page analysis of sign-up form	Identifies specific steps where users drop off during the signup process, enabling targeted optimizations.	Conversion
TAT between sign-up and placement of first order	Measures the time taken for new users to place their first order, providing insights into onboarding effectiveness.	Value Realization, Conversion
% of users who sign-up and do not place an order within 15 days	Tracks ghost users, helping to understand retention and identify potential churn points.	Commitment
Cohort-wise bucketing of users by weekly order frequency	Segments users based on order frequency to understand behavior patterns and loyalty levels.	Commitment
D1/D7/D15/D30 retention figures	Measures the percentage of users placing at least one order in specific time intervals post-signup.	Commitment, Value Realization
DAU/MAU on platform	Tracks active users (those placing orders) daily and monthly to assess engagement and growth trends.	Commitment
Number of orders placed by user within D7/D15/D30/D45	Tracks purchase frequency over time to understand user stickiness and engagement.	Value Realization, Commitment
Drop-off on ordering flow	Identifies where users abandon the ordering process (e.g., cart, coupon application, payment), enabling process improvements.	Conversion
NPS for users by bucket of order frequency	Measures user satisfaction and likelihood of recommending Swish, segmented by order frequency.	Commitment
Frequency of orders by user	Tracks how often users place orders to assess behavior patterns and identify loyal users.	Commitment