Josh Sapienza

Hawser

"Course is an app that learns your personal taste and then matches you with the restaurants you're most likely to love."

Genuine Hospitality Is Mass Personalization

When it comes to taste - no opinion matters more than yours. But is personalizing restaurant recommendations an entirely new concept? No. Not by a long shot.

But those who have previously demonstrated success have built their recommendation platforms with a heavy reliance on other people's opinions (i.e., social media activity) which may have been groundbreaking 5-10 years ago but since that time, even the least tech-savy among us have come to understand how the algorithms generally work far more than they did back then: "More likes and better reviews equals more exposure".

Social Media activity and public reviews are now easily monetized, manipulated and corrupted in an effort to "help the algorithm" or produce desired results for individuals and businesses via benevolence, abuse, fraud and now bots.

Audience Effect tells us that online public behavior is not a perfect reflection of genuine interest or feeling. The mere fact that public online ratings are for the benefit and attention of others, demonstrably influences those ratings and reviews. That's one of the reasons we’ve found our anonymous first-party and zero-party granular data to be the most reliable, informative and immediately actionable data out there.

3 out of 4 Americans now identify as "foodies" and many are willing to adopt a more humane approach to restaurant recommendations in exchange for the critic-culture mindset that has long plagued the industry .

Traditional public rating platforms still editorialize millions of reviews and encourage diners to issue one-size-fits-all scores to restaurants; but modern technology now affords us the ability to analyze personal taste and help people find more restaurants they'll love without having to build another public review soapbox that serves more as a place for people to air grievances than it does to build much needed bridges between guests and the restaurants they'll love.

Marc Randolph

Netflix

"What I love about applying data to taste is that I believe it's completely possible and you should be prepared to surrender yourself to the data."

"The Best" is Subjective

"In a 2022 survey of more than 20,000 hotel, resort and STR guests*, 94.5% of respondents agreed that, although they realize lodging operators have little to no control over the local dining scene, their off-property dining experiences had a direct impact on their overall level of satisfaction with their trip which they ultimately associated with the property at which they stayed.

This tells us , categorically, that the same way scent and memory are so deeply connected; the dining experiences a guest enjoys during their stay are inextricably linked to their overall impression of their accommodations.

Given that fact, one can see why a hotel would want to personalize restaurant recommendations to suit each and every guest’s individual taste and personal style.

And yet the reality is that restaurant recommendations at many hotels often consist of a canned concierge spiel or a print out that highlights only the most popular outlets nearby.

As a hospitality industry veteran with 3 decades of experience, I know just how much guests appreciate great recommendations. I also know what goes into making them.

Making a great recommendation requires knowing (among other things) where that guest has dined before and been delighted, where're they've gone and been seriously disappointed - which places are on their radar - the one thing on a menu that they'd never let cross their lips, etc...

In short - it gets A LOT easier to make a guest happy if you spend a little time getting to know them.

But who has the time to get to know every single guest when you're hosting thousands?

That’s where Course®comes in.

We let technology do the time consuming work of getting to know each and every every member's Personal Taste Profile™️ to continually calculate their personal compatibility with local restaurants.

Course also takes the lists of restaurants you and your staff recommend into the 21st century by turning them into interactive digital experiences."

-Josh Sapienza | Course

Taste Is Personal.

"When it comes to taste no one's opinion matters more than yours."

LEARN MORE

Potential membership if capturing 1%
of the market share held by traditional leaders:

Yelp

730,000

1% of Yelp's 73 Million users*.

Trip Advisor

4,000,000

1% of TripAdvisors 400 Million users*.

OpenTable

15,720,000

1% of OpenTable's 1.572 billion users*.

Zomato

3,840,000

1% of Zomato's 384 million users*.

Membership Goals & Projected Gross Profit

2022: 200 Members ($331,773)/yr.

2023: 10,000 Members ($1,733,232)/yr.

2024: 50,000 Members ($1,290,960)/yr.

2025: 100,000 Members $ 4,891,980 /yr.

2026: 500,000 Members $115,295,830/yr.

2027: 1,000,000 Members $251,628,800/yr.

Market Availability

"Restaurant reservation platform OpenTable aquired Ness Computing (LikeNess) the personal restaurant recommendations app in an all cash transaction worth $17.4MM in 2014...Ness used machine learning technology, deriving results from social signals that you provide it from Facebook, Foursquare and Twitter as well as other online social behavior to figure out which places you'll like the most.." aquiring 200,000 users in Year 2 and 300,000 downloads by Year 3. https://techcrunch.com/2013/04/17/with-its-biggest-update-yet-ness-debuts-instant-personalized-restaurant-recommendations-says-events-nightlife-is-next/

Tech Crunch

"Happy Cow, a restaurant finder app focusing on and rating only a restaurant's ability to cater to customers with dietary restrictions, food allergies or specific dietary preferences (and not on the quality of food, service or atmosphere) has attracted over 450,000 members. in 2019*"

Natural Products Global | GreenQueen UK.

BRAND CONSISTENT COMPANIES & CATEGORIES

AIRBNB, VRBO, OPENTABLE, RESY/AMEX, CHASE,
LTD SERVICE LODGING, GOLDBELLY, DOORDASH/BBOT
GRUBHUB, OLO/OMNIVORE, GOPUFF, MEREDITH/CONDÉ NAST, DISCOVERY/FOOD NETWORK, TOAST, STR/COSTAR, WAYZE, UBER & LYFT

Synergy With The Lodging Sector

Chip Conley

Airbnb

"You could have your best or your worst experience at an Airbnb and so - with a more adventurous traveling public, what comes with it is more of a willingness to try out a boutique hotel or to try out an Airbnb experience because if there’s a high likelihood of it being your best experience...and you can sorta figure out how to make sure it’s not your worst experience, then it’s more worth trying.”

3 out of 4 Americans identify as “foodies” and whether they’re traveling for work, taking a family vacation, attending a conference or trying out the co-living life — ALL of them have a deep desire to belong... to live - just for a moment - like a local there.
Which means that, for 3 out of every 4 guests, a big part of living like a local - is eating like a local.

If you own or manage a hotel and are still married to that tired old paper list of "Local Restaurants" - or have a front desk staff that's writing down the names of restaurants on maps or post-its....we should talk (484.800.1323).

Pre-Seed Funding Round

Detailed GTM Strategy, Monetization Plans & Financial Projections Avail Upon Request.

Seed Round

$2.5MM

Y1 USES

Advertising & Mktg
$1.25MM

Payroll
$1.2K

Acctng, Legal HR & Insur
$100k

Other / Misc
$200K (from Rev)

Series A Round

$4.75MM

Y2 - 3 USES

Advertising & Mktg
$2MM

Payroll
$1.95MM

Acctg, Legal, HR & Insur
$575K

Other
$265K

Summary

2022
We're thrilled to announce that we've successfully self-funded our MVP, Pre-Seed Round of financing and made the PWA version of Course Restaurant Guide available as a native app in the AppStore & Google PlayStore.

We are now seeking both angel investors and limited service hotel owners, operators and asset managers who see the value in offering Course's cutting-edge technology as an innovative, relevant and practical FREE amenity to their guests.

Hawser's unique approach, of merging machine learning with private restaurant ratings, yields an incredibly intuitive and industry-friendly restaurant recommendation platform / digital personal concierge service that has been well received among industry professionals and ardent supporters of independent restaurants.

With the completion of our seed round raise, we anticipate self-funding our Series A round primarily from revenue generated by in-app purchases and ads (native and interstitial) promoting products and services attractive to the food-loving lifestyle traveler.

Course is committed to facilitating more positive dining experiences for our members and providing exclusive access to actionable zero-party data of unprecedented granularity.

As a B2C SaaS provided by a public benefit company, Course is designed to be as practical as it is profitable. We see ourselves as a people-centric hospitality company using technology as opposed to a technology company using hospitality. Our humane application of technology is rooted in treating our members like the valued customers they are and that begins with safeguarding their personally identifying data instead of selling it to the highest bidder.

Our purpose is simple: We support independent restaurants and the communities they serve by making personal, engaging and culturally rewarding experiences more accessible through technology.

We believe our values are our vertebrae and that by keeping our platform agnostic; we ensure the reliability of our data and the sustainability of our company. We're not trying to "own the guest" or force them into any one booking, ordering or payment channel. We're just trying to better serving them.

2023
Following Course 2.0 and the introduction of List Following, we're planning to launch ClubLevel (where members can not only see their compatibility with other ClubLevel members but also: connect with & message other ClubLevel members, set proximity alerts for other ClubLevel members or outlets saved on bucket lists, engage in group compatibility searches and filter searches via customizing the algorithm). Hawser also plans to expand Course into multiple markets with various new applications (e.g., Metaverse, AR & Web3) starting with the lodging industry.

2024
The Lodging plug-in will allow any member to privately rate lodging accommodations and see their compatibility with different properties in any market when looking for a place to stay.

The lodging algorithm we're currently developing is based on the same architecture as our restaurant & bar a.i. - the main differences being the elements / aspects that members can privately rate....namely:

With sufficient investment, we project (and are committed to) driving gross annual revenue upwards of over $20MM and an IRR of between 32 and 33% by Year 5. In order to meet these goals, we must ensure that Course doesn't become just another great idea that no one's ever heard of.

Our ideal angel investor has existing holdings or experience with M&As in the technology and hospitality, travel or food sector(s) and/or can bring some successful marketing & advertising experience to the table

For a copy of our Executive Summary or a walkthrough of our deck, please call 484.800.1323
or email: josh@hawser.org.

Josh Sapienza | Hawser LLC.
484.800.13234 josh@hawser.org