Business Enrichment

A complete audit of the current business model both external and internal were studied. The proximity detail between the warehouse and the store, architecture flow inside the company, target user study, and information about the stake holders were also collected.

The findings were documented and referenced from time to time. Market study on the competitors’ business model and the existing business models in the market were also considered.

Based on the information collected, and the problems faced, a functional model was proposed and miniature designs of the model were prepared and tested. An e-commerce platform proved to be effective out of the other models and thus an e-commerce platform with all the products was built to improve the product reach to the consumers.

Page response analytics were embedded in the system to capture the kind of product searches the users do, the price range of products they spend their time on, and filter them on the respective keyword. Upon recognizing the user pattern, specific user behavior identification algorithm was created.

User behavior identification algorithm was all about capturing the user clicks, keeping a note on the user search in the product list, grouping the price range of the searched/selected products, and analyzing the user purchase history. Information collected through user behavior algorithm gets stored in the big data.

Integrated user behavior identification algorithm helped in grouping different kinds of users into different categories: first time user, visitor, the regular customer, browser, the smart shopper, & the deal hunter etc. based on the number of purchases, number of interactions, interval of visit, interval of purchase, and the duration of the user’s presence in the platform.

The entire system works on big data analytics. Big data analytics helps examine huge chunks of data to uncover hidden patterns, identify market trends, and other valid data related to business. The findings can help in developing better marketing campaigns, increase the revenue of the firm, improve operational efficiency and yield other business benefits.

User behavior information collected gets stored in the big data database. Based on already programmed metrics, the user related information gets grouped in the backend of the big data system.

Once the grouping of users is done, the admin will look into the list and announce the promotions. Through admin promo management, individual promotions based on the wishlist of the individual, the search pattern, interval of interactions, time spent on individual pages, and already purchased products’ combo offers and other promos can be sent to specific individuals.

Campaigner support system helps in sending automated push notifications and e-mails containing promo offers and discounts to the appropriate customers in relation to the user behavior algorithm mapped before.

With an easy to use interface and wide features, Campaigner support system is an effective email management system that provides 24*7 support, high deliverability, and stability. Using Campaigner support system, it is possible to send 100,000 mails in a span of 10 mins.

The campaigner system along with the big data system is the heart of this application. They help monitor each and every customer, based on their history different set of products will be featured in the promo e-mails. For the customers who have already purchased something, the algorithm will send the information of the products that are related to the products they have previously purchased.

The promo emails sent will intrigue the users to visit the site more often and buy some products. Though the initial conversion ratio will not be high initially, down the line more visitors will be converted to customers. Through constant interaction with the customers the amount of probability that he/she will visit the site and the chance for a conversion is really high.

After the onset of an ecommerce site with built-in analytics, the increase in the site traffic and the increase in the revenue were clearly visible. Thus making the ecommerce site a vital option and a big hit.

Based on the page response analytics, the user behavior system, and campaigner support system will adapt itself.