“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