Sales Performance Increase 200% With Generative AI

Sale is basically activities of email, and conversation which are creative and manual. Sale is not only finding customers and talking about the products with hoping they will buy them. Researching customer behavior, and customizing content to be suitable for particular customers takes a lot of time. Besides, salespeople have to do manually some related tasks such as logging contact in CRM, classifying customer groups, creating deals, and lots of other unnamed manual work. That is why sales are well-suited to the capabilities of generative AI models. Selling is interaction and transaction-intensive, producing large volumes of data, including text from email chains, audio of phone conversations, and video of personal interactions. These are exactly the types of unstructured data the models are designed to work with. The creative and organic nature of selling creates immense opportunities for generative AI to interpret, learn, link, and customize. But to realize the true potential, there are hurdles and challenges to overcome. Generative AI must be non-intrusively embedded into sales processes and operations so sales teams can naturally integrate the capabilities into their workflow. Generative AI sometimes draws wrong, biased, or inconsistent conclusions. Although the publicly accessible models are valuable (hundreds of millions of users like us have already used ChatGPT to query the knowledge base on practically every topic), the true power for sales teams comes when models are customized and fine-tuned on company-specific data and contexts. This can be expensive and requires scarce expertise, including people with significant knowledge of AI and sales. So how can sales organizations harvest the value without wasting energy on heading down unproductive pathways? Before we get into how, consider What AI will assist sales optimizing performance. Remove administrative duties The fact, the more customer you have the more administrative tasks you have to do. If the amount of customers is around 10-100 people, you find it easy to remember every piece of information like the email address, hobbies, behavior, and content of your conversation with them. If there are hundreds of customers you have to care about, it’s impossible to handle the giant information in a manual way. AI can automatically log customers’ email, company, and associated conversations, write emails, respond to proposal requests, and organize notes. Supporting Customers is piece of cake Communicating with customers is much easier than before due to the auto chatbot. But for B2B businesses that mostly communicate with customers through email, the application of AI to email is very limited. Because most current email tools only get customers’ general information. By layering on generative AI, the models can produce better recommendations. One example would be considering customer sentiments gleaned from the nuances of language and subtle signals of customer interest or distrust — in emails, conversations with salespeople, posts on social media sites, and more. Further, the salesperson can collaborate with the system to improve recommendations in real-time. For example, after receiving a suggestion to approach a customer with a new offering, the salesperson can dig deeper — both vertically into the customer’s…
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