Financial institutions all around the world are working hard to increase cashless transactions, i.e. replace the conventional currency exchange with wireless communication payments. Going cashless gives the convenience of banking from anywhere by simply using your smartphones. Funds are on now available on tap, while the money in the bank earns interest. It also brings better tax revenue and pushes for more financial inclusion.
But there’s a large chunk of people who still prefer to use the traditional means of payment. And this is where Connaizen, a startup aiming to increase cashless transactions by incentivizing the use of cashless payment enters the scenario.
India-based Connaizen helps financial institutions run targeted offers which can only be redeemed if the customer uses digital/card payment. Founders Nikhil Garg and Sanchit Kapoor worked on the idea for straight 3 years. They were later joined by their college mate Siddhant Punn, Business Development Head and Vikas Bharti, who took development of the analytical engine in his hands. The four founders together form a strong team and are part of the Startupbootcamp Fintech Cohort 2016.
Connaizen draws insights into consumer purchase data directly obtained by leveraging customer’s card transaction history, geographical location, search history and purchases of peers. These whole-wallet insights spanning across all categories and geographies, give a wholesome view of where and how much the customers spend. This enables merchants to target customers, customize campaigns, optimize ad-spend (increase ROI) and measure campaign performance with competitive benchmarking. In this setup, banks provide relevant deals and offers to its customers through various banking channels. By analyzing terabytes of transactions, the recommender engine allows consumers to see the deals/offers catering to their interests.
The Connaizen Edge
Few firms in the market work on customer data whereas few source offers from retailers, but Connaizen does both. They have created a one-stop solution for banks and retailers to give personalized offers to customers, and use state-of-the-art machine learning algorithms to create customer profiles and curate offers that have the most likelihood of getting redeemed. So the analytical engine analyses customer data and also curates data driven marketing campaigns for retailers.
The team has built a recommendation engine that personalizes retailer and their offer suggestions by leveraging customer transaction data relationships. The state-of-the-art machine learning algorithms understand the unstated preferences of the customers to recommend appropriate offers and enrich their shopping experience.
Connazien’s web crawlers are specially designed web mining tools which collect the openly available information about the retailer. This data helps them understand similarity between retailers and their features. They further use these features in the recommendation. Web crawled data induces the real world insights about the retailers in recommendations. They are also using natural language processing (NLP) to understand the similarity between two retailers.
Journey so far and the road ahead
The startup had approached their current retail partners directly and are working with some of the biggest financial players in India. They will be launching their retail sign-up portal in September this year. The platform will allow retailers to just log in and start creating targeted campaigns. Connazien plans to reach 10 million customers by the end of June 2017. The startup’s expansion plans are on hold at the moment considering the market size of India.