Post on 14-Jan-2015
description
“Where do we go eat tonight?”
“What’s open?”
“I’m new here, but everything looks closed”
“Yelp said this restaurant was open but they lied!”
We take the frustration out of late night cravings.
…We’ve All Been There
About 75% of those surveyed across the US have experienced
that problem
Easily find what’s open late near you
Enhanced accuracy of listings
Simple one-click functionality
Existing Solutions
What did you do when you had trouble locating a place?
“Either gave up or tried calling a bunch of places”
“Using Yelp with their pathetic filtering feature which never gives me the right result on the basis of time”
“Driving around aimlessly”
Addresses Critical Pain Points
Accuracy Simplicity & Ease of Use
Aggregation of Open Venues
Diversity of Options
Other-
20%
40%
60%
80%
100%
53%40%
60%
32%
15%
Chart Title
% o
f R
esp
ondents
Limitations of Existing Providers
Let’s Take a Look…
Simplicity and Accuracy
User Participation rewarded with “Badges” based on behavioral
patterns
Active Verification Passive VerificationLeveraging existing data from
Foursquare, Yelp, and Google Places for baseline data and ongoing
automatic check-in and check-outs
SuperGeek
VampireInsomniac
Business Model Evolution
Ad RevenueStrategic
Partnerships
Data Subscription
Bootstrap Expansion End-State
Revenue Model
Cost Structure
Team
Questions?
Appendix
1. Gaming / Rewards System (Slide 13)
2. Strong Initial User / Vendor Feedback (Slide 14)
3. Distribution and Business Model Detail (Slide 17)
4. Back-End Data Population (Slide 22)
Reward SystemAfterPM’s Reward System and Active User Verification create a
sustainable ecosystem by achieving greater accuracy and rewarding beneficial behavior
vE
VEN
DO
RS
US
ER
S
*Note: Deals engine achieved through strategic partnerships (OpenTable, Groupon, Yipit, etc.)
Discounts and reward badges
Active verification of
hours of operation
Deals* and ad revenue for
sponsor position
Incremental foot traffic and
intelligent customer data
Strong Initial Feedback
• “After pm is a pretty cool concept!! definitely helpful after a late night out” – Based in Boston
• “I’ve always needed an app like this!” – MV
• “Would be pretty sweet in SF” – Based in SF
• “Cool idea…cause so few things are open late in SF” – Based in NYC
User Feedback Vendor Interviews• “I think it would be very helpful
because people don't know that we're open late” – Ahn Sushi & Soju
• “Sounds like a great idea, customers tell us we’re one of the only places open late night” – Hana Sushi
• “Corporate would take a definite appeal to that” – Extreme Pizza Folsom
• “It’s a good idea, right now people maybe use the internet” – La Perla Pizza
User Review of Features
Location / Proximity
Discount / Deals
Trending Popularity
Ability to Email
Friends
Ability to Make
Reserva-tions
-
20%
40%
60%
80%
100%
83%
11% 15% 9%
15% 15%
45% 47% 40%
34%
Necessary! Nice to Have
% o
f R
esp
ondents
98% of surveyed users are looking for data on location/proximity of restaurants open late
Verticals of Interest
Fast Food
Sit Down Restau
rant
Club Bar Gro-cery Store
Drug Store
Spa Movie The-ater
Other-
20%
40%
60%
80%
100%
66%
81%
38%
60%51%
40%
15%
45%
13%
Chart Title
% o
f R
esp
ondents
To begin with Food & Drink …To move to other verticals later
Distribution Plan
App Store Distribution Techniques
Viral / Social Outreach to Target Market
Initial focus on niche market (young adults / graduates)
Revenue Model Detail
Ad Revenue Strategic Partnerships
Data Subscription
• In-app display ads to cover basic startup costs
• Vendor bidding for preferred “sponsored link”
• Initiate conversations with large chain vendors and strategic partners
• Focus on growing user base and getting traction
• With demonstrated user traction, establish revenue share / royalty relationship with strategic partners
• Generate additional margin and vendor awareness with limited sales activity by leveraging partner networks
• Potential partners include: OpenTable, Groupon, Yipit
• Establish advertising relationships directly with vendors
• Monetize data stream to create operating leverage
• Provide subscription data service to vendors with insight on customer dining/purchase preferences
The AfterPM team plans to add additional revenue streams at each stage as the application gains concrete market validation
Business Model Detail
Ad Revenue Strategic Partnership
Data Subscription
• In-app display ads• Offer bidding for
“sponsored link”
• Revenue share / royalty agreements with strategic partners
• Monetize data stream to create operating leverage
Bootstrap Expansion End-State
Revenue Model
Cost Structure
• Co-founders only• Focus on growing
user base
• Gradually establish sales team after significant user traction
• Streamline costs to manage for growth
Automatic Check-In System• AfterPM is constructed to be easy-to-use with minimal input
required of the user– Initial rollout is manual check-in– With validated back-end, will shift to auto check-ins and check-outs
• Auto Check-In– Users no longer fumble around and click a button (requires about 5
clicks)– AfterPM tracks arrival & departure from a venue with high location-
based accuracy (1 click)
• Integrated into Rewards System– Length-based rewards for Users to drive valuable behavior– Valuable customer activity data for Vendors to understand positioning in
late night dining/activity market
• Feeds long-term data strategy with powerful database to drive intelligent suggestions/recommendations
SWOT Analysis
• Well-rounded team with relevant relationships and experience
• Satisfies key customer pain points through gamification (accuracy, simplicity)
• First mover advantage in niche market• Low initial capital investment to launch (iOS,
Windows Mobile, Website currently available)• Quick validation of user adoption
• Significant time to scale with meaningful data and partner relationships
• Health-conscious trend may reduce late night dining
• Requires salesforce to for expansion and vendor engagement
• Some users may feel current Yelp or Google Maps functionality is sufficient
• Users have consistently verified through survey data and in-person interviews that this is a service they would like
• Strong alliances exist to provide revenue share and vendor access with relatively low startup cost• Groupon Affiliate Program, Yipit, etc.• OpenTable Affiliate Program
• Potential acquisition target with strong technology
• Large competitors including Yelp, GoogleMaps, etc.
• Low barriers of entry to replicate before sufficient branding
• Revenue dependent on strategic partnerships• Highly saturated app market may be difficult
for new entrants
Strengths Weaknesses
ThreatsOpportunities
Initial Data Population Existing data will be leveraged with Yelp to provide a location
database
FourSquare APIs
Venues API
Mapping services (free)
Google Places
The gaming element then provides continuous input to refresh for accuracy
A cornerstone of our data processing is respecting the rules of our partners
Our approach is well currently well within the acceptable use policies of intended data partners
We use caching & elaborate models within the terms of our data partners to adhere to their policies and limits
Our service takes gradual approach to build relationships with our data partners, and exploits the services they offer in most appropriate of our own data
Passive Verification
Backend uses checkin data from data partners like Foursquare, Yelp, and Google Places, combined with our statistical processing to determine venues that are open with a high confidence level
These will provide foundation of our geo-spatial-temporal engine
We will participate in 4Square-motivated venue harmonization process
Venue harmonization gives unique ID to venues that are consistent across differ databases and services. It enables collaboration to share information data
We don't store partner data except to cache & limit the rates we use their APIs
We store harmonized venue IDs with our checkin data and partner real-time checkin counts (where allowed, using real-time counts of checkins from google and 4square) to validate open and closing times. We incorporate checkins and false positives in our own application to continually improve the accurate of our own data
Leverage Existing Data
The Technology