This type of website targets the “lazy” shopper who does not
want to constantly check for sales since this website will alert the user via
e-mail. Since many similar
shopping-assistant websites already exist, like Groupon, Ebates, and Price
Protectr, with similar functions, this idea may not survive as a startup. However, this website will be unique in that
it takes the best features of many shopping-assistant sites, like the price
tracker and recommendation system, to help users shop for their desired
products in the cheapest possible way.
Some of these useful features include alerting the user of price drops,
recommending retailers where a lower price may be offered, organizing products
that the user may want to purchase, and offering better deals for products
bought through the website.
This website will have three key functions. The first is to take as an input the URL to a
specific product and alert the user of any price drop that occurs as soon as
possible. The second is to recommend
similar retailers who also sell the product.
The purpose of the recommendation list is not to show lower prices from
other retailers, but rather to give the user alternative places to purchase the
product. For example, the list may just
be called, “These retailers also sell this product:”. Finally, another recommendation list will
show products similar to the specific product as done on any retailer
website. Since we will have a history of
products that users are interested in, we can implement this feature using
algorithms similar to Amazon’s “Frequently Bought Together” and “Customers Who
Bought This Item Also Viewed” functions.
All of these features are meant to assist the user in
finding the best deal on a certain product or similar product by alerting them
of falling prices both before and after the purchase and of displaying options
of where to purchase the product.
Therefore, this website needs to check the given URL for updated prices
as often as possible so that the user can be alerted quickly to take advantage
of a sale or possibly diminishing supply of the product.
To simplify the development of this website, we will start
by supporting only one or two input websites (for example the URL given by
users must be from a specific store or two).
Once the functionality for the features is up and running for these
starting retailers, the website can expand to take URLs from other retailers’
websites as well.
Related Websites
The following are similar websites and their descriptions
online.
Use Price Protectr to track prices
of things you're thinking about buying, and save money even after you buy.
There are lots of stores out there that offer price protection policies -- when
the price drops on an item you've purchased, they'll refund you the difference.
But there's a catch... it's up to you to watch prices. Price Protectr makes it
simple to watch prices, keep track of your purchases, and get rebates off price
drops.
Camelcamelcamel provides free Amazon
price drop alerts and Amazon price history charts, helping users buy when the
price is right.
Online
shoppers love finding exactly what they want online and we love providing them
with the comparison shopping technology and large selection of products to do
it! Save time and money through Become.com’s comparison shopping site and shop
for online discounts and the lowest prices from name brand retailers. From
diamond rings to smart phones, find the best online deals and interesting shopping insights on
Become.com!
Our shoppers
can also depend on Become.com’s product research engine for advice on what
they’re shopping for online, from buying guides for LCD
televisions to product reviews on baby strollers, as well as editorial tips for
the hottest online deals and products for the season. Use our comparison
shopping site to find your next purchase and give us your feedback on how to
make our online shopping experience even better!
Become does not have our price tracking feature, but it does have
a great price comparison feature when a user searches for an item that we would
like to implement in our “suggested similar items” section. Meanwhile, Camelcamelcamel
has a great feature of showing the history of prices, but since it only works
with a few websites such as Amazon, Best Buy, Newegg, etc, we wish to build on
its price history line graph to provide users with more options. Overall, the
website most similar to our idea is Price Protectr. Price Protectr provides
services that watch prices of items in online stores, alerts when the price of
the products drop, and deals with refund issues when users buy products before
their prices decrease by giving detailed information about what users should do
to get money back. What separates our website from Price Protectr and
camelcamelcamel is our desire to build a better user interface, and provide two
additional recommendation features, discussed below.
General Approach Based on Prior Work Done in Class
Our website will have two recommendation features. One
feature is to suggest different websites that sell the same item that a user
wants to buy. Each website has a different price and deals so we want to
provide the user with more options to get the best deal available. For example,
if a user wants to buy a Macbook Pro, he/she can choose from various online
stores such as Apple, Amazon, or Best Buy. Our website will crawl these
websites and show our users everything he/she wants to know without requiring
them to visit multiple sites at once. Another recommendation feature that we
plan to include will suggest items similar to the item that the user wants to
purchase. If a user does not have a strong preference to buy the item he/she
originally intends to buy, we might be able to sway the user into buying a
similar item. This feature will be similar to Amazon’s “What Other Items Do
Customers Buy After Viewing This Item?” list.
We will create a web crawler to constantly browse the items’
webpages that our users submit for price watch and to parse the prices for any
updates to the price. In Homework 2, we already wrote a crawler that traverses
through websites within Caltech’s domain. For our website, users will input the
address of the webpages they want us to watch over. Then our crawler will take
those inputs, visit the webpage, and send relevant information back to our
website.
To enable the feature of recommending similar items, we will
study and utilize the ideas of the web graph and characteristics like
clustering. We also need to decide how often we are crawling different websites
to get the price, which involves studying the heavy tail distribution to figure
out which websites need to be crawled more frequently. Since we are keeping a
list of desired products of each user after they input an URL, we can study how
successful we are at the “User who viewed this also viewed” section. The
results we collect will be used to constantly improve the features and
functionality of the website.
Our website will not only search for similar items but also
enable sellers to partake in the suggestion process. We will create ad
positions for suggestions and let sellers or advertisers bid on these ad
positions to compete for the opportunity to advertise their products. Before
opening up the bid, we require that the items of each advertiser follow a
certain criteria; we do not want unrelated items spamming the ad space of a
certain product. Then, based on the bids, we will decide when and where to show
the products and prioritize certain items if the bidders of those items bid
higher than their competitors.
Product
The end product will be a website
that assists users with their personal shopping experience. Its functions are:
1.
Given a URL of a product, the website would inform
users via email once the price has dropped. The alerts will continue until a
few days after the user makes a purchase so that if the price continues falling
the user can take advantage of the price exchange policy to get an even better
deal.
2.
The website will keep a product price history available
so users can look up how similar products’ prices have changed and decide when
is the best time to make a purchase.
3.
The website will suggest other places to buy the same
item, especially if a cheaper price can be found. We will also use this feature
for situations when the desired product is sold out on the original
website. Positions in this list will be
determined by auction. Retailers can bid
for the highest positions on certain products.The purpose of this is to give
users an alternative place to shop.
4.
To make a related products list, we can look at shopping
behavior and recommending products algorithms, similar to Amazon’s “Frequently
Bought Together” and “Customers Who Bought This Item Also Views” sections. The purpose of this is to encourage the user
to continue shopping by recommending similar products.
5.
Finally, we would ideally like to pair up with
companies and give people money back for purchasing products through the
website. This money could be in form of store credit that they can use to buy
more products through our website, similarly to eBay’s eBay Bucks, or it could
be checks or gift cards, similarly to Ebates’ cashback. (The point will not be
accomplished in this semester).
References
“Tutorial: Develop a local Amazon
price tracking application.”
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