DealSmash, a sensible looking discounts and rewards application startup primarily based out of Islamabad, has raised a funding of PKR 8.8M from National ICT R& D fund.
The raised funds are going to be used to develop an by artificial intelligent shopping advocate system which can recommend live deals and discounts to buyers in line with their previous searching trends.
DealSmash is a mobile-centric technology startup that guarantees to bring ancient shopper retail to the digital age. At the guts of it, is its individual mobile app, DealSmash, that uses business/social analytics to produce worth to shoppers through customized offers at their favorite stores supported their interests and shopping for patterns at no cost to them.
From the attitude of customers, this not solely saves them cash however conjointly enhances client experience.
From the perspective of retailers, this not solely allows client loyalty and increase their revenue however also allows them to induce insights into consumer behavior, inventory control, etc
DealSmash mobile app is currently operating in Islamabad and has recently been launched in Karachi, offering discount coupons at various stores across the city. It also has a incentive System for most loyal customers who can get cash-back merely by shopping and dining at any store/ café.
While talking about this latest development Syed Ali Husnain Shah, CEO of DealSmash, explained, “The funding from ICT R&D will facilitate us to build our (Artificial Intelligence-based) recommender system to handpick for our customers the most appropriate offers supporting in their interests and their buying patterns. This way, we won’t spam the customers or desecrate their valuable time with pointless/ irrelevant offers.”
There is a lack of smart intelligent mobile applications, DealSmash application is hoping to alter theirs through their smart analytics-based system. The startup has currently 10 brands on board for its reward and discounts system but is aiming to twice over this number in the next few months.
The central component of the DealSmash recommender system is an intelligent, adaptive software-based system that can learn, both offline and online, the preferences, shopping behavior, geographic attributes and demographics of the client base, reciprocally providing a customized searching expertise to every client by suggesting solely relevant offers to his or her mobile device in a very context and location-aware manner.