According to a Harvard Business Review study, data-driven decision-making improves business performance. Data-driven decision-making refers to the practice of making decisions based on data analysis rather than intuition. These data-driven companies that pioneered the use of AI in sales are overjoyed with the results, which include a more than 50% increase in leads and appointments, 40%-60% cost savings, and 60%-70% call time savings. When the benefit of allowing sales professionals to spend more time completing transactions is considered, AI's allure becomes even more compelling.

Machine Learning and Artificial Intelligence, a general view

AI and machine learning have the potential to eliminate the most time-consuming, manual activities that prevent sales teams from spending more time with clients — automating marketing processes, using predictive analytics, forecasting, reporting, and advising, all of which help clients upsell. All of these are methods for reducing labor in sales teams. When using data-driven decision-making, businesses in the top third of their industry are 5% more productive and 6% more profitable than their competitors (McAfee and Brynjolfsson, 2012).

Caruana and Niculescu-Mizil (2006) examined the top machine learning models with higher performance as well as those that aren’t as significant and are commonly used in sales. The best machine learning (ML) models, such as random forests, boosting, support vector machines (SVM), and neural networks, are demonstrated in this study. In terms of predictive performance, these models outperform simple, interpretable models such as decision trees, naive Bayes, and decision rules. Companies that do not use the aforementioned open-sourced models use their own patent AI and ML models.

Dealcode - the AI Selling Software.

Dealcode is an AI Guided Selling Software that extracts data from CRMs and processes it using its own AI and machine learning model. It is a predictive analytics tool that predicts the likelihood of success for sales pipeline prospects and risks. It gives sales teams the most up-to-date information on which deals to prioritize and who to contact right away. This predictive analytics is performed by analyzing sales processes using a patented machine learning model. Dealcode identifies individual factors that contribute to the success or failure of a sales team. Sales are noticeably more effective as a result. It also saves money on expensive resources for complex data analyses.

What services does Dealcode offer? Read more on Dealcode’s capabilities from my blog and company’s website - link.