Ailink business proposal

2019-4-15 Unilink Business
Proposal
AiLink

2019-4-15
UNILINK BUSINESS PROPOSAL
1 / 20
I. Executive Summary
a. Problem
b. Solution
c. Market
d. Competition
II. Opportunity
a. Problem Worth Solving
b. Our Solution
c. Validation of Problem and Solution
d. Roadmap/Future Plans
III. Market Analysis Summary
a. Market Segmentation
b. Market Needs
c. Market Trends
d. Key Customers
e. Future Markets
f. Competition
g. Competitors and Alternatives
h. Our Advantages
IV. Execution
a. Marketing Plan
b. Sales Plan
c. Location and Facilities
d. Technology
e. Equipment and Tools
f. Milestones
g. Key Metrics
Executive Summary

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a. Problem
Housing problem always remains an urgent problem for
university students and economical workers. Firstly, most
students complain about how hard it is to find an apartment after
they are overflowed by dormitory. In order to find a housing
place quickly, they choose to live with whom they don’t prefer to
live together for the rest of the school year. As a result, they
complain about having different lifestyles, and personal conflicts
with their roommates. Furthermore, most workers also need a
place to live without too much burden on their family budget.
Therefore, it is very necessary to have a convenient and efficient
platform that not only provide enough rented houses, but also an
easily accessible and convenient way to integrate miscellaneous
information such a wise recommendation of preference matching.
b. Solution
Our product allows customer to find a house that perfectly fits
their housing preference. Just imagine you want an apartment
with gym, transportation, and shopping malls close by, but with a
lower price. Our product will intelligently recommend houses
that matches similarities you select. While you might be a early
bird who wakes up before 8 am. However, your roommate is a
night owl who is noisy after 1 am. Then it comes to our product,
which smartly solve your problem by finding roommates that
matches your lifestyles, habits, or even personalities.
c. Market
According to our desk research, the rental housing market is
growing currently. As cost of property purchase increases, more
and more people will choose to rent houses in order to sustain
their income. Most of rental houses are through online platforms
such as Zillow, but they do not provide enough and convenient
tools to shorten information gap between renters (individual or
multiple) and landlords. The product we offer to customers can
shorten the information gap, accelerate the searching process, and
even innovate the rental housing platforms.
d. Competition

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There are some existing solutions in the market such as Zillow.
However, these websites are not tailored to customers for their
specific and individualized needs. Therefore, based on user
experience, our customer-focused product will capture a lot of
customers’ needs, and provide efficient and convenient solution.
Opportunity
a. Problem Worth Solving
According to Census Bureau housing data, rental rates for people
younger than 25 years old in the United States rises from 57% to
60% from 2008 to 2018. Households of all education levels are
more likely to rent their homes and more than 40% of bachelor’s
degree students are in the rental market. Looking for a
comfortable neighborhood has always been a big concern of
college students, especially in the campuses which do not provide
enough housing. Besides the living conditions, according to our
survey, students also complain about their roommates due to
differences in living lifestyle. Meanwhile, people below 35 also
concerns about the housing issues in which they have to rent a
suitable, preferable, and cost-effective place.
However, the current housing market does not provide an
efficient tool to facilitate the searching process. Most of them
simply filter price, location and size range, but fail to match a
roommate or give a recommendation at the same time. In some
social media applications, there are housing groups where people
post housing and looking for roommates. In our survey, students
also complain about the inefficiency of these groups. They say
that “the information flashes through housing groups”, “tired of
asking each post but the room is already gone”, etc. Thus, if there
is a product that can learn students’ preferences and matches the
best house and roommate for them, it certainly captures the needs
of this huge market.
b. Our Solution
Our product aims to provide a match of room and roommate at
the same time for students. Students who have an empty room or

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have a need to rent out can quickly access other housing
information via Unilink. By entering their need of the living
environment, such as nearby bus station, grocery store around,
and roommates’ preference, students would get the best match
according to the information they enter.
To provide a package of rental housing service, we integrate
various payment of relative housing expense including rent,
insurance, electricity, gas, internet, and etc. to a single final
solution. Furthermore, the live chat for contacting leasing office
is also designed in the application for those who prefers to seek
normal standards of finding places to live. Lastly, our unilink is
able to publicize second-hand sale of furniture to accommodate
users’ experiences and promote customers’ stickiness. When
students move out, they need to dispose of their furniture and the
incoming renters would likely take over this furniture. This
function can help students to buy or sell their furniture when they
move in or move out.
c. Validation of Problem and Solution
We already established a simple prototype of our product but it
stills requires more marketing survey and technical improvement
in order to be officially put in use. Our product team consists of
experienced software developers, who have strong skills to
deliver and improve viable application to the market through
agile development pattern. Our market team consists of public
relations officers, who can acquire resources from institutional
housing provider, and customer representatives, who can promote
our sales to general customers. Our algorithm team consists of
experienced data scientists, who can explore the idea of
recommender system through cold start phrase to latter phrase.
d. Roadmap/Future Plans
We plan to release an alpha version of Unilink in May, which is
estimated to be tested by 200-250 people in UCSD. In June, the
beta version will be available to put in use. Around 1000
customers will experience our app to find their matched
preference on both housing neighborhood and roommates. The
version 1.0 will be released at the end of June, with an initial
market in San Diego. Around September, the market will be

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expanded to Los Angeles, and northern California by the end of
year.
Market Analysis Summary
The housing market can be divided into homeowners and renters’
households. According to the 2018 census, the renter households
occupy 35.6% of the total number of households in the United
States. The total market revenue in 2019 is estimated to be $177
billion by IBISWorld.
a. Market Segmentation
In general, we target both renters who merely hope to rent a
single room and those who want to share or rent the entire
apartments. Anyone customers are free to select one bedroom to
live or share a house with their friends. Specifically, our targeted
groups are low income population such as youngsters or adults
below 35 years, international immigrants, as well as local
minorities. According to the population survey from U.S. census
bureau, we also observe the following facts that additionally
supports our targeted direction of future customers:
1. Youngsters and age below 35 are the major renters of
housing market
2. Family who have lower income than median usually rent a
house instead of purchase as a result of insufficient budget.
3. Minority is more likely to rent houses than non-Hispanic
white population
b. Market Needs
1. For off-campus college students in the USA: They want to find
roommates who share similar daily schedules and living habits
with them. But they also do not live with parents. Hence, they are
our targeted single renters.

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2. For on-campus college students in the USA: Most university
lacks a systematic solution to assign suitable roommates. It raises
problems such as assigning students with totally different living
habits to one room. Since the assignment cannot be changed
easily after students move in, such problems will have negative
effects on students’ living and study for a long time. Therefore,
universities are really in need of an app that helps assign
roommates based on similar features instead of assigning
randomly. Besides, on-campus students who plan to live outside
the campus next year also benefit from our application.
3. For temporarily or permanently relocated workers: People who
are very likely to be the prime members of our product because
they need a useful and informative tool to quickly learn the
current rental housing situations.
c. Market Trends
The average price per square foot for this same period rises to
$443, up from $436.The median sales price in California
currently grows at the rate of 6.3% for all properties of different
real estate.
In comparison, the average rental price per bedroom is widely
below $1,000, which is a very cost-effective way to solve
housing problem in short period.

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Over the past 12 months, the demand of rental housing rises to
3.4% due to harsh housing affordability from house price
pressure.

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Currently, youngsters are still the major renters of the housing
market while group from 35 to 44 years are the second largest
rental population.
In terms of family income, households who have higher income
than median tend to purchase a house while households who do
not have higher income prefer to rent a house, driving the low-
income population rental demand to be the majority such as
college students and relocated workers.
Besides, it is observed that Black, Hispanic, and other races tend
to rent houses than non-Hispanic white.
0.0%
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60.0%
70.0%
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Under
35 years
35 to 44
years
U.S.
45 to 54
years
Rental Rates By age
Source: U.S. Census Bureau

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Key Customers
1. All college students in the USA (Finding suitable
roommates)
2. Out of state employees (Finding relocations)
Future Markets
In the future, we also consider the market beyond U.S.A. like
Asian market such China, Japan, and etc. Those markets have
tremendous population base with strong preference on rental
houses due to unaffordable housing price in the cities.
As for the future trend of US market, there are some factors that
need to be paid attention:
1. the rising homeownership rates in U.S. greatly benefit the
rental market since fewer fellow will compete with another
and renters have stronger bargaining power than landlords
to make decision on rent pricing.

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2. the decreasing rental vacancy rates in U.S implies an
increasing number of renters who actively seeks for vacant
houses and most of rental property takes less time to be
leased than in the past.
3. the stable national unemployment rate ensures a sustainable
and safe housing market since no large fluctuation will
appear to affect the rental and purchase demand
4. the increasing urbanization might lead population increase
further, forcing the price level and rental housing demand
booming as well
5. the rising interest rate might spur demand for rentals over
the next year, driving the housing market to be more
competitive than previous days.
Competition Environment
Most of renters look their future housing location via social
media, online housing websites, leasing offices, and in-phone
applications.
First, the influence of non-housing sites to advertise rental
property listings is very extensive and powerful. If you have a
listing on a site or on your website, you can advertise it to your
community online through social media. If you're having
particular difficulty renting a property, create an infographic with
property details. While Facebook, Twitter, and Instagram may
not be property-focused, they allow you to reach out to your
communities and turn the search for tenants into a more sociable
experience.
Among many housings’ websites, Zillow, the leading real estate
and rental website in the United States according to monthly
website visits, has approximately 36 million unique monthly
visitors. Then it comes to Trulia, the second most popular real
estate website with around 23 million monthly visits. Finally,
Yahoo! Homes places in third with around 20 million monthly
visits. The detail of monthly visitors of popular real estate
websites is shown below.

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The online apartment listing industry is competitive because it is
very easily for renters to recognize whether this website is
informative, convenient and efficient. Specifically, renters do not
really have enough time to drag down the screen one by one.
Another thing is that most website can not promise their
timeliness. Some of the information are posted later than it
should because in usual it takes time to follow up and some of the
other information are not deleted after it has been rented. All
those problems contribute to an inefficient and inconvenient
browsing environment that waits to be improved.
As for mobile app market, due to need of the short apartment
hunt time periods, mobile apps come in handy, allowing users to
browse listings whenever it's convenient – from standing in line
at the store to watching TV in the evening. Mobile really turns
searching for an apartment from kind of a desktop into a 24 hours
shopping experience.
Alternatives Analysis
1. Social media
Social media such as Facebook, Wechat, etc. has rental
group, where people post and acquire housing information.
36,000,000
23,000,000
20,000,000
18,000,000
6,000,000
5,000,000
2,500,000
2,000,000
1,800,000
1,750,000
1,600,000
1,500,000
1,400,000
1,300,000
1,200,000
Zillow
Yahoo!Homes
RedFin
ApartmentG…
ReMax
ZipRealty
Rent
ForRent
Top 15 Most Popular Real Estate Websites

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2. Online housing platforms
a) Craigslist
The ubiquitous Craiglist is where people turn for almost
everything, including housing that's focused on a specific
metropolitan area. The benefits: it's inexpensive, and it
allows you to write in your own way and with your own
photos. The drawbacks: you'll get many inquiries, and
many of them will be from those who are not always
serious about your rental.
b) Oodle
Like Craigslist, Oodle is a classified listing service that
includes rental housing. It's not just property-focused but
it's good for attracting renters who are local and may
stumble on your listing as they browse for other items.
c) Zillow
With its photo listings, interactive map, and ability to easily
sort by features such as bedrooms, bathrooms, and rental
price, Zillow is a popular rental property listing site. It also
allows prospective tenants to compare two listings side by
side.
d) Hotpads
Looking for a website that allows you to list your unit in a
multi-family building? Try Hotpads. This site also caters to
pet owners with pet information upfront, and like Zillow,
it's based on an interactive map.
e) RentalHouses.com
While the website itself is a little bit dated,
RentalHouses.com lets property owners and managers post
their rentals to the nationwide database in a few clicks. As
of this writing, it's unclear how much they charge for rental
listings and how long the listing duration is, though.
f) Realtor.com

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Realtor.com manages both rentals and real estate sales. It
only accepts listings from property managers and owners.
The interface is a little less straightforward and attractive
than sites like Zillow, but it provides a simple search
function for price and location.
g) Trulia
Trulia is an attractive and simple property listing site that
allows renters to set parameters to see a group of photo
listings with vital statistics about a property right
underneath. Make sure you have a single great photo for
adding your property to this site.
h) Rentals.com
Rentals.com makes it easy for tenants to search for exactly
the type of home they want, with searches compiled into
condos, lofts, duplexes, and more. There's less information
required about amenities, and it has your contact
information and the availability flagged to press people to
call.
i) Rent.com
At first glance, Rent.com appears to be largely geared
towards apartment rentals but it is home (pun intended) to a
significant number of rental houses as well. It's also one of
the higher traffic'd sites on the list so it's definitely worth
looking into when you're looking for your next potential
tenants.
j) Zumper
Zumper is a value-added site that offers up neighborhood
information and city guides for your tenants. Its initial
listings feature minimal information and a single photo, but
its detailed listings offer you the opportunity to add an
engaging paragraph about your property.
3. Leasing offices

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Leasing offices, where people acquire information
regarding specific leasing office in combination with their
websites.
4. Mobile apps
Our Advantages
1. Information/Service integration
Our product preserves housing information in a uniform
platform, which can fall into neglect in social media group,
where there is too much information for renters to process
at one time. In addition, we provide a series of service
package so that every user would not worry about paying
rents, utility, electricity, gas, internet, and etc. Finally, we
also design the business chat pages so that users can
directly contact any other housing providers for consulting
purpose.
2. Recommender system
Our product improves user experience through
recommender system. Unlike traditional platform, people
never have to scroll to the end of list to see all information,
which can be unsatisfied or irrelevant to them. The
recommendation system provides the most accurate match
between roommates and living rooms. Any customer who
utilize our product will have no difficulties on finding
things they hope for a housing application.
3. Third-party selling platform
For those who seek to find preferable or cheap furniture,
we utilize recommendation system to shorten searching
process and facilitate customers’ special needs on furniture.
For example, if a customer’s preference selection indicates
he/she is a quiet renter, we might recommend some
furniture that is not very colorful to smartly meet their
needs.
Execution
a. Marketing Plan

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Since we focus on housing for college students, we will
make direct connections with colleges from the following:
1. Housing, Dining, Hospitality
We plan to reach out to the housing, dining,
hospitality department of universities to advertise our
product. When students first move out from
universities, they would first seek for university
resources. We expect to become the provider of the
off-campus housing resources. Since our product
keeps the user population as students only, we would
use student safety as our biggest selling point to
cooperate with universities.
2. Student organization
We plan to cooperate with student organizations to
promote our product. We would work with student
organizations which has strong impacts in schools,
such as Chinese Students and Scholars Association
(CSSA) and Phi Beta Lambda. We would advertise
our product through their Facebook Page or WeChat
official account in order to expand our user
population.
Secondly, social media is an important tool to expand our
customer base. Students use social media to acquire
information. Thus, we would promote through social media
mainly from the following three platforms：
1) WeChat: There are three ways to promote with
WeChat, which are official account, group chat
and mini program. We will first establish our
official account. In the official account of our
product, we will post housing-related articles of
useful information, such as what to be careful
of when renting a room and encourage people
to talk about their stories of renting rooms. We
would also use group chat and mini program in
WeChat to promote our product. Before our
application has launched, we will build a mini

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program to help students to generate their
description of their rooms to be rented out and
post them in the group chat. By using group
chat and mini program, we first aggregate some
popularity in students. Then, when our product
is published in May 2019, we can direct the
students in the group chat to our product.
2) Facebook: We will use Facebook page and
Facebook groups to promote our product. We
will establish the page of our product to post
updates about our product. We would also like
to contact with the large off-campus housing
rental groups such as UCSD Student Off-
Campus Housing, which has around 27,000
members, to advertise our product.
3) Twitter: We will establish a Twitter account to
update and expand our user base.
b. Sales Plan
1. Commissions
Our product is a housing platform, we will generate
revenue from the following:
1. Institutional housing provider
Users in our product has need for rental. We will
provide a platform where leasing office can post
housing information, we will receive revenue through
commissions.
2. Individual housing provider
Users in our product can post their housing for
finding roommates. We provide such a platform to
help them reach connection, we will receive revenue
through commissions.
2. Advertisements

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Our app provides in-app purchases, such as furniture. We
will provide a platform where third-party furniture
company can post their product. We will retrieve
advertisement revenue. We will also promote our future
product by in-app diversion.
3. Complementary services
a. Utilities: Users in our product has housing and they
need utilities for living. We will provide a platform
where utilities company can post service
advertisements including Internet, Electricity, etc.
b. Insurance: Users in our product needs insurance for
their housing. We will provide a platform where
insurance company can post service advertisements.
c. Furniture Transfer: Users in our product can leave
their furniture for future users. We will provide a
platform where furniture can transfer from current
users to future users. We will generate transfer
commissions.
Location and Facilities
1. Southern California (04/2019-11/2019)
2. Whole California (12/2019-06/2020)
3. China (06/2019)
4. East Coast (06/2020)
Technology
1. Features
The goal of our product is to assist our customers to not
only find a satisfying property but also suitable community.
Our features will evolve through time to respond to the
needs of our customers.
2. Cold Start Phase
Cold start problems refer to the situation when we don’t
know the users' preferences. We need to recommend a
reasonable list of listings/roommates to users and learn

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about what users like. During the cold start phase, we
construct our input features by utilizing both the users and
listings’ tags. Users have two sets of features: one set
corresponds to users’ preferences as owners, the other set
corresponds to users’ preferences as renters. Listings’
features consist of property information and owner’s
personal preferences. A similarity score will be calculated
to rank the listings and roommates. Flexibility is very
crucial for all recommendation systems. We grand our
system flexibility by introducing additional variables
adjusting based on users’ actions toward recommended
listings and roommates. Each user has his or her own set of
variables. The variable will then affect particular feature
entries’ weight during calculation.
3. Collaborative Filter
The key idea of collaborative filtering is that we predict the
interest of a single user by collecting preferences of a
couple of other users. In our model, we would like to use
this technique after collecting much information from
house posts and users history. The reason why the
technique works is that similar persons are likely to have
similar choices. When recommending listings/roommates,
we look at users’ view history of houses and then rank the
similarities between users to pick the top results.
4. Community-Classification two stages approach
We run a clustering algorithm on both users and listings.
Then we create various mapping relationships between user
clusters and listing clusters. During the recommendation
phase, we picked listings from the community which is
connected to the user’s community. In this way, we can
effectively speed up our recommendation process which is
essential for a large-scale recommendation system.
5. Siamese network
Siamese network is a natural choice to calculate similarity.
The network is expected to perform better than the
collaborative filter approach because this is an automated

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and highly non-linear approach. This network has two
identical sub-networks that accepts two inputs, in our case,
one listing and one user. Then the two outputs run through
a similarity layer to calculate the similarity. In this stage,
we have much knowledge of what a user likes through their
explicit feedback. In training time, when one user likes one
listing, we make the distance in similarity space close by
using the mean square loss; when one user dislikes one
listing, we make the distance in similarity space far by
using hinge loss. In testing time, one user and one listing
are inputs and they run through a forward pass through our
network and the network will output a similarity score.
Then we order the potential listings to output the
recommendation list.
6. Evaluation
We have three metrics to evaluate the performance of our
algorithm. This first metric is the explicit feedback: after
recommending an apartment for a user, he/she can
explicitly chooses ‘Like’ or ‘Dislike’ the recommendation
and the choice will be regarded as our label to calculate the
accuracy of the model. The second way is using the time
spent in the recommended post: we sample a distribution of
the time spent on all house posts and give a percentage to
indicate whether we should regard our recommendation as
a successful one. The third way of evaluation is the
frequency of refreshing the page: our recommendations are
liked by our customers if there are relatively few pages
refreshes.
Equipment and Tools
1. University housing
2. Social media
3. Student organization
4. Summit
Milestones

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1. 2019 first Quarter
In the first quarter of 2019, we settled what function our application would
have and decided our marketing plan. We planned to first launch our
product in the second quarter of 2019.
2. 2019 second Quarter
At the beginning of the second quarter, we will prepare for the launch of
the beta version of our product, including the promotion of the product
and our product. We will publish our beta version in the middle of the
second quarter in San Diego, California. Based on the feedback of our
product, we will prepare for version 1.0 of our product.
3. 2019 third Quarter
At the beginning of the third quarter, we will publish version 1.0, with
main features: housing and roommate matching, second-hand furniture
sale, business chat, reminder and easy transfer for lease and utilities fee.
Based on the feedback of our product, we will prepare for version 1.1 of
our product.
4. 2019 fourth Quarter
At the beginning of the fourth quarter, we will publish version 1.1, with
main improvements: accurate prediction of housing price (including lease,
utilities, insurance), housing and roommates matching improvement (from
cold start phrase to latter phrase), furniture featuring(recommender system
for furniture and housing). Based on the feedback of our product, we will
prepare for version 1.2 of our product.
Key Metrics (Promotion efficiency, customer conversion rate)
a. Acquisition - How do users find out? "Get in the door"
b. Activation - Do users have a great first experience? "Connect the
promise to your Product"
c. Retention - Do users come back? "Return to your website or product"
d. Revenue - How do you make money? "Customer Pays"
e. Referral - Do users tell others? "Word of mouth"

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