The concept of artificial intelligence or AI refers to machines that can be programmed to think, anticipate and act like humans. Today, the area of focus has moved from developing machines capable of solving complex problems to creating AI systems that can accurately simulate the cognitive patterns of the human brain. The most widely cited application of AI and machine learning is in consumer oriented products and services, from self-driving cars to digital personal assistants and recommendation engines. However, AI systems can also revolutionize business-to-business (B2B) services.When compared to B2C enterprises, B2B services typically have a more complex business systems as well as purchasing and sales processes. Here are some examples of how AI and machine learning are being adapted to improve processes in B2B companies.
1. Lead Generation
The lead generation process for B2B companies is labour-intensive and time-consuming, as it requires sales reps to mine contact information for prospective clients from various business and professional websites. This process can be automated using AI systems which can sift through data from large volumes of emails, phone calls and social networking sites. Machine learning algorithms can also be used to analyse patterns from past leads and effectively determine criteria for identifying new prospects.
On an average, the buying cycle for B2B enterprises is longer and more intensive since the target clients often include multiple stakeholders from various departments. Businesses today also have to deal with a large volume of data from various channels, which can take up a lot of manpower to manually analyse. With AI & Machine learning solutions, companies can quickly correlate historical data of past efforts and results to better understand what products and services are preferred by customers in a particular sector. With these insights, companies can tailor their marketing efforts for maximum efficiency.
3.Customer Experience & Transactions
Given the complex nature of B2B services, customer support is a critical aspect aspect.
AI chatbots can be tailored to provide relevant answers for client queries on features, pricing and contractual issues, thereby saving on manpower costs for customer services reps.
Unlike B2C transactions, where transactions are made via only one portal, B2B transactions can happen via email, documents and electronic gateways. normally require a more complex business system. AI systems can be tailored to accept orders from various formats and integrate all the records maintained via invoices and accounts.
4. Predictive Account Management and Sales
Through an analysis of sales trends, AI systems can accurately forecast revenue predictions for a given quarter based on past data. This can help business and sales managers take corrective action to review team performance, reallocate resources and maximize productivity for better profits. An analysis of past data about valid leads can help identify signs and signals that indicate greater chances of conversion. This way, sales reps can focus their efforts only on prospects that offer high chances of conversion. For B2B sales, prices also vary by customers depending on the size of the orders or special conditions. AI systems can also recommend custom pricing based on past sales to provide sales reps with recommendations on discounts and commissions.
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