Introducing Revenue AI
For today’s B2B salespeople and marketers, the process of B2B lead generation has become harder than ever. The number one reason for this is data. All too often, the data that B2B sales and marketing teams are working with is incomplete or out of date. B2B data starts to go out of date as soon as it’s captured in a CRM, creating issues in identifying decision-makers and the appropriate prospects to do business with.
This kind of data decay can have numerous damaging impacts on a business, from lost sales opportunities to wasted resources - and ultimately, a reduction in revenue.
However, a solution to this problem is at hand. Artificial intelligence and machine learning represent a significant opportunity for B2B companies to improve the quality of the data they hold. Cognism is at the forefront of this cutting-edge technology and has created its own pioneering AI engine - Revenue AI.
Revenue AI is a patented technology that provides a breakthrough in how labour market data can be structured in order to facilitate lead generation. It leverages large-scale graph-based machine learning approaches to map the inherent structure of firms, employee career paths, and the types of skills that are most likely to match a specific product. These structures provide an extraordinarily granular and useful view of different individuals, departments, firms, industries, and the entire economy as they change over time.
Will someone soon be promoted into a decision-making position? Does a person now qualify for new investment products? Is a company changing strategic direction or adopting more AI technologies? Revenue AI uses enriched graph-based structures to predict the likelihood of people being good targets for products, to identify firms that might be considering new technologies, or industries ripe for targeting.
The high-quality, real-time aspects of Revenue AI’s enhanced B2B data means that lead generation can be conducted in a more timely and effective manner, helping organisations to hit and exceed their revenue generation goals.
The co-founder and CEO of Cognism, James Isilay, is an expert in algorithmic technologies, natural language processing and machine learning. He developed Cognism as a means to initiate an event-based approach to lead generation and sales management.
Before founding Cognism, James was employed as an Algorithmic Trader at Axpo Group and as a Quantitative/Technical Analyst at EGL Trading. James has an MEng in Information Systems Engineering from Imperial College London.
Cognism has assembled a world-class team of AI experts and data scientists. Their work has led to the development of Revenue AI and its practical application in providing deep and accurate customer data to B2B companies.
The team is led by James Hodson, Cognism’s Chief Science Officer. James is a researcher, leader and entrepreneur in the fields of artificial intelligence, machine learning and economics. He currently serves as Senior Researcher at the Artificial Intelligence Department of the Jozef Stefan Institute in Slovenia, and as the CEO of the AI for Good Foundation, a UN-backed platform that promotes the beneficial use of AI in business and society.
Prior to joining Cognism, James built and directed the AI Research group at Bloomberg in New York, leading a team of 20 in a rich cross-disciplinary research agenda. James was also a researcher at the German National Research Laboratory for Artificial Intelligence (DFKI) and holds several patents across Machine Translation and Network Inference.
BA in Computer Science, specifically NLP and ML, Princeton University
PhD in Artificial Intelligence, Jozef Stefan Institute, National Artificial Intelligence Laboratory
Researcher, German National Research Center for Artificial Intelligence (2009-2010)
Director of AI Research Lab, Bloomberg LP, New York (2010-2015)
CEO, AI for Good Foundation (2015-present)
Angel Investor, Scientific Advisor, Machine Learning and Sustainable Development Startups (2016-present)
Cognism was granted a Revenue AI patent in December 2018. The patent, referred to as the “System and method for computational disambiguation and prediction of dynamic hierarchical data structures”, puts Cognism at the forefront of the B2B data industry.
Summary of the Patent
The Revenue AI engine was designed to disambiguate and enrich dynamic datasets, in order to improve information about the interrelation between company profiles and individual profiles in a CRM environment (for example, a user profile comprising resume information such as work history, job title and other evolving data).
Revenue AI achieves this aim by deploying a unique combination of computational, statistical and machine learning methods. It provides a system for computing broad representations of user profiles, termed ideal customer profiles. These ideal customer profiles can then be used to find similar profiles in other countries across cultural, geographical and linguistic barriers.
The Advantages of Revenue AI
The advantages of Revenue AI include the ability to predict fields within user and business profiles in a CRM and any changes that may affect them, including any changes to:
James Hodson explains why such a system is essential for B2B organisations to adopt:
James Isilay adds:
“Not only does static CRM data rapidly lose its relevance, we know that in most cases it is contextually flawed at the outset, which means that organisations are missing out on both identifying and targeting their most valuable prospects. Through the Revenue AI engine, not only can companies identify the most relevant, timely revenue opportunities on an international scale, but a deep and accurate customer data resource can transform the accuracy of sales and marketing activity. Companies are not only prioritising outreach activity at the right time, but each prospect interaction is more focused and relevant to each persona.”
“With a constant feedback loop provided by our Revenue AI engine, our B2B clients are achieving real bottom line growth. This comes from using Revenue AI to better understand their core market, from purchase triggers to decision making personas. In today’s ever more discerning market, being able to deliver a personalised B2B sales message in the same way that people have become used to in a consumer environment will soon become a key to competitive advantage and profitable business growth.”
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