AI declares war on sales dinosaurs
Commentary by Michael Märtin
The coronavirus pandemic has turned all our lives upside down. B2B sales has also been affected. No networking, no personal appointments, no interpersonal decision-making based on the emotional approach of potential customers by experienced sales professionals. Many long-established salespeople, who are still firmly convinced that high closing rates are a question of gut feeling, are increasingly falling behind. You could say that the coronavirus is the meteoroid that is putting an end to sales dinosaurs.
The coronavirus pandemic is preparing the breeding ground on which AI-supported B2B sales can develop. From upstream persona definition by marketing to planning and forecasting to evaluating leads and calculating closing probabilities - artificial intelligence has the potential to revolutionize B2B sales in the long term. Provided that companies have a large pool of data (big data). By analyzing customer-specific information that is already stored in the CRM system, marketers can define buyer personas that are based on empirical data with regard to the specific characteristics of real customers - and which therefore reflect the wishes and needs of potential buyers much better than the subjective gut feeling of a sales dinosaur. Such a data-driven approach not only delivers accurate buyer personas, it is also significantly more efficient than conventional approaches.
Handed over to sales at the right time, data-driven employees can focus on the most promising leads - especially by using predictive analytics methods. Predictive analytics uses historical data to predict future events. This involves an AI analyzing very large amounts of data from the past and combining it with many other factors to derive predictions about future developments.
How will customers behave? Which sales measures can be successful? What is the probability of closing open leads? What turnover can result from this in the next financial year? AI can answer these and similar questions much better than humans. As predictive analytics tools quickly and automatically analyze extensive data sets from a wide variety of sources (historical and current, internal and external, company-specific and macroeconomic data, etc.), they relieve sales employees of the time-consuming and often tedious task of forecasting - especially as the results are much more accurate.
In addition, supplementary AI applications estimate the demand and willingness to buy of new and existing customers. To do this, the system automatically creates a scoring for new inquiries: using its self-learning properties, it evaluates the probability of closing, the duration of the sales process and the quality of the leads, for example. By prioritizing them according to the probability of closing, sales employees can not only focus on the most promising inquiries, but also respond more quickly and correctly. Modern AI solutions provide sales staff with specific recommendations for action. The benefits: more precise forecasts, improved decision-making and significant time savings. Time that sales employees can invest in maintaining customer relationships - even if this is currently mainly done online and digitally.