How would you design an app that helps consumers find Happy Hours?

Users go to happy hours primarily because they want to find good liquor at a cheaper cost. This helps them avoid the steep cost of alcohol, at the same time helping them sit with their colleagues and friends in a new environment and have fun.

Users need to reach and place an order within the happy hour duration to gain access.

Key User Segments

Working Professionals - Folks who want to hangout with their colleagues
Students - Folks who want to hangout with their friends

I will pick working professionals here because the user segment is larger and working professionals are busier than students.

User Journey and Pain Points

Leaving office
1. Not sure if they can leave in time
2. Not sure if they can find a group that is large enough for a certain location
Reaching the destination
1. Need to find the right type of commute
2. Need to ensure there is no traffic/or that they would be able to reach the location in time
Placing the order
1. Don't know what all liquor is available on happy hours
2. Don't know if they can still place the order in time

Solutions

Discovery tool and Cataloging by Location - Users can filter the pubs and bars in their location and identify the ones they would want to go to, similar to yelp but specifically for alcohol. It would have other features to compare cheaper prices by location, seating arrangements, safety, distance, seat availability, good for (large, small groups), food availability, etc.
1. Effort - High
2. Impact - High
3. Verdict - Table Stakes
Booking and Order placement - Users will be able to directly place an order and reserve a place for a price.
1. Effort - Medium
2. Impact - High
3. Verdict - Must Have
Bidding system for the tables - If there are too many people coming to a certain place, there can also be a bidding system to book a table by paying a higher premium
1. Effort - Medium
2. Impact - Medium
3. Verdict - Good to Have
Collaboration - Add your friends and ask if they would want to go to a certain pub and place an order collaboratively before going to the location itself, saving time and ensuring that they are able to get the seat in the location
1. Effort - Medium
2. Impact - Medium
3. Verdict - Not important

Metrics to Measure - only user side

Awareness
1. Number of visits on the website
2. Number of bounces on page 1
3. Number of users from various channels
Activation
1. Number of users running a search
2. Number of users using a filter
3. Percentage of users booking a table
4. Number of users favoriting pubs and bars
Retention
1. Weekly Active Users
2. Average number of searches per user by city
3. Average number of favorites per user by city
Referral
1. Number of social media shares
2. Number of users referred

productiq · Answer 2 · 2021-01-19T23:23:13+0000

Clarifications and Assumptions

Would you agree on the following definition of happy hour:
A time frame for reduced prices on in-house buying and in-house consumption of certain alcoholic drinks offered by pubs, restaurants, clubs and other similar establishments
This is generally offered during slow hours
Yes

Would this app act as a discovery channel for customers to find happy hours?
Yes

Would you concur that the overall aim of the app would be to increase convenience for customers to find happy hours and to increase traffic and revenue for restaurants during happy hours?
Yes

I would like to design for India.
To begin with, I would like to create an app catered towards the urban metropolitan areas, as most of the mid-high income customers who frequent establishments of a certain stature and average-high end establishments offering alcohol are located in such spots.

Users

Customers looking for a happy hour, restaurants
As per the question, I would mainly like to focus on the customers wishing to visit the pubs, and not the pubs themselves

Customer Segments:
College students
Friends & Colleagues - Working population - ages 23 to 50
Corporate parties - assume separate package, happy hours not applicable
Ladies Night - Discounted drinks for women only
Group Sizes may vary: 1, 2, 3-5, up to 10-15 usually

Customer needs:
With little to no planning
quickly find a relevant pub, possibly closeby
to consume copious amounts of alcohol (of choice) for a low price,
order starters
without calling beforehand or waiting after reaching a pub
often a large number of people - seating for everyone
pay the bill
bonus - go home safely, no drink and drive

Prioritizing customer pain points:
Happy hour applicable on customer segment (am I eligible) - high
On demand current or upcoming happy hour - high
Availability of Seats - high
Location of pub, Distance of pub (and time to reach) to current location - medium
Happy hour offers - medium
Happy hours estimated cost - medium (customers go in with the expectation of spending less, end up spending more to the benefit of the restaurants, who are other users)
Happy hour applicable on which drink - high
View menu - High
Pre-ordering of food - low
To reach home safely - medium
Ratings, Reviews and feedback of other customers - medium (eg. how many interested, how many booked)

Would first focus on the high impact pain points

Solutions

Segment restaurants and provide appropriate filters, eg -
Happy Hour Characteristics - customer eligibility of happy hours, happy hour timing, drinks and brands available for happy hour, offer type by getting this data from restaurants
Restaurant Characteristics -
establishment kind (eg pub vs club), pub location, cuisine type

Seat Availability -
Reserving certain seats for app booking (hotel booking model)
Dynamic update of available seats to be displayed to customers, a caveat - there would be seats allocated for walk-in which would not be displaced
Reservation of seats for a fee - reserved till x min after slot booked to reach restaurant ends
Option to input group size and filter for pubs with at least those many seats available
Ask restaurants to periodically update current no of vacancies by day and time as a whole to predict current vacancies, other factors could include day of the week, restaurant capacity filled in nearby restaurants etc

View happy hour time slots, offers, relevant alcoholic drinking available (eg cocktails available for 30% off all cocktails) in a text format
The remaining alcohol and food menu can be displayed as pictures initially, and later text.

Prioritizing solutions
Filters for happy hour characteristics are high impact and can be easily implemented with accuracy for standard menus
Similarly for restaurant characteristics (except higher accuracy cuisine classification - may require menu parsing and topic modelling)

Seat availability - booking, filtering and monetization for app reserved seats can be easily implemented
Predicting current overall seat availability is difficult to implement, and will be low accuracy without a require a lot of good quality (historical) training data

The goal of the app is related to happy hours, so this info must be clear.
Food Menu related information clarity and availability is not as important a need for a customer looking primarily to drink for cheap prices
Alcohol brand (in happy hour) and other availability of items problems are more complex logistically, and can be added as a feature later

Others -
Distance to pub is of lesser importance for impact but is a feature most customers expect nowadays can be easily implemented by accessing Google Maps API

A bonus feature (a differentiator), and a good way to launch the app would be to partner with a ride-sharing app to pre-book rides to reach the next destination, also a good chunk of the existing user base of the ride-sharing app can be made aware of the app and captured. This can be later extended for rides to the pub and other features.
This is not a necessary feature in the first launch but only a differentiator.
Reserve overnight parking spots at the pub if available

Some more monetization strategies
Paying the bill via the app such that the app gets a % of the bill as earnings is not a customer important need, and requires hashing out complexities with restaurants, but is another way to monetize the app
Similarly for pre-ordered food bills - as this would guarantee the restaurant sales

Ad space for restaurants on the app

Some features which can be provided to restaurants -
best case footfall estimates of expansion/downsizing strategy planning

using data give recommendations for types of happy hours they can offer, offer types, depth, best day-time combination (different days than other restaurants in the vicinity)