Match<IT>: a smart B2B platform for provision and selection of technology providers

• Grant number: 22/04248-6
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: September 01, 2022
• End date: May 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Roseane Jamile Lopes Ramos
• Grantee: Roseane Jamile Lopes Ramos
• Company: Match It Serviços de Tecnologia Ltda
• CNAE: Desenvolvimento de programas de computador sob encomenda
• City: São Paulo
• Pesquisadores principais: Didier Augusto Vega Oliveros
• Associated researchers: Ivan Nevado ; Lilian Berton ; Marcelo da Silva Reis ; Pedro Augusto Palhares Braga
• Associated research grant(s): 23/06335-6 - Match<IT>: data efficiency and intelligence connecting B2B IT services supply and demand, AP.PIPE
• Associated scholarship(s): 22/15599-4 - Design and implementation of backend and database for improvement of recommendation of Sellers to Buyers, BP.TT; 22/14666-0 - Applying Natural Language Processing and data mining for buying and selling IT services, BP.TT; 22/14465-4 - Development and improvement of user-friendly interfaces of the platform, BP.TT; + associated scholarships 22/13857-6 - Optimization of user base growth structures - Growth Marketing, BP.TT; 22/10868-7 - Match<IT>: a smart B2B platform for provision and selection of technology providers, BP.PIPE; 22/11104-0 - Integration of machine learning-based recommendation mechanisms into the Match platform, BP.TT; 22/11620-9 - Connecting the research to the specialist IT market environment, BP.TT - associated scholarships

Abstract

In 2020, US$48 billion were invested worldwide to hire information technology companies. In Brazil, where there is a deficit of qualified people in technology, the investment in IT services grows around 10% a year. The allocation for this demand is satisfied by outsourcing to service providers, here called Sellers, which represent 30,000 companies with this profile in the market. However, contracting information technology services is an arduous and costly task. Moreover, the process involves a complex ecosystem of manufacturers (software development brands) and sales channels (distributors, resellers, solution partners) that is inefficient in presenting solutions to potential customers, here called Buyers. Trust and personal relationships are crucial elements for negotiation in many countries. In this sense, social networks are platforms that allow the generation of trusting meta-relationships between individuals in the real world, such as friendship networks, offer and search for jobs, among others. However, trust is a subjective metric, and the needs of these companies are not fully met, mainly due to: (I) platforms offering low-quality functionalities and not focused on the Business to Business (B2B) environment in IT, given the lack of scientific-technological support in the use of intelligent algorithms; (II) targeting is not specific and tailored according to the needs of the contracting companies and service companies' portfolios; (III) the challenge of generating trust in trading between companies in a virtual and technological environment, which can be very impersonal and not very predictable. Therefore, and addressing these gaps in this project, we propose the development of an intelligent B2B platform for the provision and search of IT services. We seek to optimize the connection between the offer and demand of corporate services in an intuitive, efficient, intelligent, and fast way, as determined by the current era of meta-society. This Match platform allows a simple and efficient Match or assertive connection between service demands and company portfolios. The main differentials are I) The Match or suggestion of the ranking of the most indicated Sellers for a Buyer, which happens in an automated way from a rich base of knowledge generated from the Sellers' register in the platform and from the interactions, comments, and feedback from the clients. II) Use of Artificial Intelligence (AI) models that learn and evolve according to the new demands and evaluations by the Buyers, in a self-supervised and active way. For example, the criteria of importance and optimal investment characteristics in IT vary according to the client, although it is the same demand. III) Focus on specialized and value-added business intelligence services, directed according to the company's area of activity and requirements according to the projects, offering differentiated market positioning that allows companies to evolve and leverage themselves to become more competitive. (AU)