Shopster - A Social Mobile App

Project Feasibility

parisiona — Thu, 26 May 2011 16:56:56 +0000

Our initial plan and goal was to have a prototype of Shopster ready until the Dragon’s Den Pitch, but due to limited time we were not able to do that. However, it is possible to be implemented as a working project in a small amount of time.

We would implement the first version of Shopster using Android SDK, because the majority of our team is an Android-device holder. Android could give us the initial blossom to the application due to the fact that it is used in a big number of different devices as Operating System. We could also make a version for iPhones but this is can be done in the future, depending of the success of the initial application. Existing third-party APIs can be used to get some information and data for our application, such GPS locations for shops from FourSquare, Facebook’s and Tweeter’s APIs for users to connect to them and ProductWiki’s API in order to give some information about every single product of each offer (if the offer is for a specific product). These actions imply short implementation time and minimum effort for development and operational maintenance.

In order to have some initial offers in the system, we would post some offers ourselves. Without any initial offers we will not going to be able to attract any users. Another way to attract users is the use of the reward system and the free-registration of the normal users in the application.

An application like Shopster must be in some ways profitable. We would use the “freemium” model in order to generate profit. These ways are well explained in a previous post, the “Potential Profit through Shopster”

Concluding we can clearly say that our project is more than capable to be implemented and be used in the real world.

Potential Profit through Shopster

kyriacos — Thu, 26 May 2011 14:46:44 +0000

Shopster would be an application capable of producing profit for its developers. After consideration of the possible revenue models, we decided that since we will categorise users to simple users and shop-owners, it would be a good idea to charge shop-owners with a membership fee. This would a sensible thing to do since, if a lot of users use Shopster, it would be a value for shop-owners to register as well and be able to advertise their offers in the system. Shop-owners would also have the ability to control a shop’s page within Shopster and therefore see which users “like” the shop.

Related to the previous point, Shopster developers could also charge shop-owners or potential companies for supplying them with anonymous statistics. For example, shop-owners might want to know whether more male or female users like their shops, the location of users who like their shops, what age groups are attracted by specific offers, etc. Of course, all these information would be given with privacy issues always in mind.

Finally, 3rd parties like websites, companies or other organisations might want to advertise their businesses in Shopster and this would generate extra revenue for Shopster developers.

It is therefore important that if we can find people to invest in Shopster, some of that money should be spend on advertising the application and attracting users to start with as well as contacting shop-owners, after a number of users start using the system, and convince them that it is worthwhile to become members in Shopster.

Recommendation Algorithms

kyriacos — Wed, 25 May 2011 23:02:12 +0000

As explained in the features list published earlier, the Recommendation System will be a very important feature for Shopster. One of the kinds of recommendations that it will offer, will be offers indirectly recommended by a user’s top friends. To find a user’s top friends, we are planning to introduce a measure of similarity for calculating top similar friends. This can be done using the Pearson Correlation coefficient which is a neighbourhood based algorithm for comparing past ratings on the same offers by both users and producing a value between -1 and +1, which would be indicative of the strength of their relationship. After that, the top rated offers of each top friend will be recommended to the current user, considering that he/she has not already rated them. These recommendations will be available to the user when he clicks on the “Recommendations” tab in the Search screen, as shown in this mock-up screen.

If the user, however, does not have any friends yet or is a new user to the system, the recommendations offered in that tab will be the top ratings of the most trusted users in the system. A user will generally have a high trust rating if his ratings on offers are similar to the actual average rating of an offer but also on the amount of helpful comments he/she has posted in combination with the ratings he/she has received on offers posted by that user.

Another simpler type of recommendation will be the top rated recommendations of all users and this is also the 1st tab shown in the Search screen mock-up. Offers from shops that a user has “liked” (or in other words, subscribed to) can also be accessed in the 3rd tab of the search screen.

The next also very important recommendation algorithm will be the recommendations that a user will receive when viewing a specific offer about a product. We can use the Item-to-Item Collaborative Filtering approach for recommending similar or related products to the products described in the offer currently being viewed (just like Amazon’s item-to-item recommendation – users who bought this also bought that, etc).

Dragon’s Den Pitch – Presentation Video

spyros — Fri, 20 May 2011 22:07:01 +0000

Click on the below link to watch the Dragon’s Den Presentation

YouTube Link

Dragon’s Den Pitch – Final Presentation Slides

kyriacos — Fri, 20 May 2011 22:06:14 +0000

Here are the final slides for the Dragon’s Den Pitch that took place today (20/5/11).

The video recording of our presentation will also be available shortly.

Presentation Slides (PDF)

Shopster UML Use Case Diagram

marios — Wed, 18 May 2011 22:17:40 +0000

Shopster's UML Use Case

Search for an offer and for a shops location

marios — Wed, 18 May 2011 20:54:14 +0000

Diane is a 22 years old student. She studies at the University of Southampton, and she decided to go for shopping with her friend Laura. Diane is very interested in offers, and so she decided to have a quick look at Shopster’s application.

Diane starts the application and enters her username and password for logging in. Diane after herlogin is navigated at the Home page. Diane clicks on the advance search button for searching some interesting offers. Diane fills in information about the offers she is interested. She searches offers on clothing, which are 50% off and are located in Southampton. The application shows the results of potential offers that maybe are good for Diane. Diane clicks on an offer and is navigated to the offer’s page. The offers rating and commenting are too convincing so she decides to go and check for the offer with her friend. The problem is that she doesn’t know where the shop is located. So, she clicks on the shop for finding more information. The shop page is presented and Diane clicks on direction button. The next screen includes a map that gives directions about the shop’s location and how to get there.

UML Use Case

Search for an offer and for a shops location use case

User Interface Storyboards:

Logged in to Shopster

Select Search

Submit Search criteria

Select an offer from search results

View the Shop

View the Map Directions to the Shop

View top rated offers

marios — Wed, 18 May 2011 20:22:42 +0000

Lucy is a 15 years old student. After an exhausting day at school, Lucy wants to buy some new clothes, and she will go for shopping. Because she is exhausted decides to search for the top rated offers and to see if there is an offer that will be nice for her.

Lucy starts the application and enters her username and password for logging in. Lucy then is redirected at the Home page. Lucy clicks on the offers button and is navigated to the Offers page. Afterwards, Lucy clicks on the Top Rated offers tab for viewing the top rated offers and to decide if she will follow an offer. After a quick view, she finds out one offer that interests her and clicks on it for seeing more information. The offers rating and commenting are too convincing so Lucy decides to go and check for the offer by herself.

UML Use Case

View top rated offers use case

User Interface Storyboard:

Logged in to Shopster

Select Offers

Select an offer from search results

Select Comments

Insert Comment

Search via GPS

marios — Wed, 18 May 2011 00:15:08 +0000

Christine is a 30 year’s old married woman with two kids. Today she has found some free time, and she decided to go for shopping. However, because she hasn’t enough time for comparing prices and searching for offers and discounts, she decided to use Shopster application for finding the nearest offers and chase them.

Christine starts the application and gives his username and password for log in. Christine after his login is navigated at the Home page. Christine then clicks to enable the GPS locator search. The GPS is loaded and now she can see the nearest shops that provide offers. Christine clicks on shops with offers that she is interested for. Subsequently, Christine is navigated at the page of the offers, and she reads some comments as also she view the rating about the offer (for deciding if he will chase that offer).

UML Use Case

Search via GPS use case

User Interface Storyboard

Logged in to Shopster

View Home

GPS Activation and Search for nearby Shops

Select a shop from the map

View the offers by the shop

Select a specific offer from the shop

View Comments

Insert a Comment and Rating

Search for an Offer-Rate and Commenting it

marios — Wed, 18 May 2011 00:05:47 +0000

Jeremy is a 19 years old student. He recently learned about Shopster application, and he wants to contribute to this new idea. Jeremy has just return from his shopping, and he has used Shopster for finding some offers. After he checked those offers at the stores, now he wants to leave some feedback (rate and comment) about those.

Jeremy starts the application and gives his username and password for log in. Jeremy after his login is navigated at the Home page. Jeremy clicks on the advance search button for searching a specific offer. Jeremy writes the needed information for the offer (the offer he checked today) and asks for a search. Then, Jeremy is navigated at the search result’s page. Jeremy clicks on the appropriate offer and is navigated again at the page of the offer. There can see reviews from other users as also the overall rating. After reading those reviews Jeremy shares his experience by posting a comment and rate the offer according to his own experience.

UML Use Case

Search for an offer and rate and commenting it use case

User Interface Storyboard:

Logged in to Shopster

Search for an offer

Submit search with criteria

Select an offer

View shop

View Comments

Insert Comment and Rating