Sale is basically activities of email and conversation which are creative and manual. Sales 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. 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. 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 Generative AI will assist sales optimizing performance. Remove Administrative Duties The fact, the more customers 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 A 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 own needs and horizontally to find other customers who might benefit from the same offering. An interactive, conversational user interface makes the application easy to use. In a truly collaborative seller-buyer environment, even the buyer can be part of the dialog. Assisting Learning and Reading Business Reports According to the investigation, learning and reading business reports and…

The global economic outlook for 2023 is among the weakest in decades, with global real GDP growth forecast to increase by 2.3% in 2023, further down from 3.3% recorded in 2022. Though global inflation is expected to moderate from 9.1% in 2022 to 6.8% in 2023, it is still at historic highs. The high costs of living, rising interest rates, and ongoing geopolitical uncertainties will continue to dent private consumption and investment in many parts of the world, undermining the global growth outlook. Customers will hesitate to spend money on expensive things due to rising inflation.  The problem for businesses is How to create an environment that encourages customers to buy? The answer is to build a Customer Experience Ecosystem. Create a Customer Experience Ecosystem as the solution. Developing a Customer Experience Ecosystem will be easier than ever thanks to the advancement of generative AI. But what exactly is a customer experience ecosystem, and how can you create one? Let’s find out through this article. What is a Customer Experience Ecosystem? Ecosystem = living and non-living things that make up an environment and affect each other. Customer Experience Ecosystem aka Business Ecosystem includes customers, staff members, distributors, partners, agencies, competitors, rituals (planning, funding, evaluating, rewarding, reporting, communicating, advancing, and training), and the logistics and interactions between all of these stakeholders and rituals. Like a rainforest ecosystem, you must think holistically about the interdependencies of all elements. Think about the food chain, what informs what, who influences whom, who needs whom, what makes things tick, and what gets in the way of success. Therefore, creating an ecosystem for the consumer experience requires an awareness of how ecosystem components interact. Many firms have used customer interactions to collect data, evaluate that data, and then modify their marketing initiatives and business plans to cater to different client segments. They have a better understanding of clients and a better strategy for dealing with them, which makes them stand out from rivals in every way. How can We Build a Customer Experience Ecosystem? Building an Intelligent Experience Engine New digital media create new ways for users to interact with brands. Location-based tracking and payment systems activated by the swipe of a hand blur the lines across prepurchase (advertising/marketing), purchase (sales/transaction), and postpurchase (service/loyalty) interactions. These capabilities have created intelligent ways to reshape customer experiences, and they enable brands to be distinctively valuable and deepen engagement. Starbucks, for example, geo-targets lapsed customers who are near its stores with ads about new seasonal beverages, and it sends customers personalized in-app offers to encourage them to visit a store or to try their convenient mobile order-and-pay option. Building an Intelligent Experience Engine means building an end-to-end experience but focusing on each micro goal on the journey. Think about how to design the flow of a given moment. Because each positive individual moment creates an overall customer experience. At each moment what information should be provided to the customer? Suggestions for customers to use the cross-channel or cross-party which will be most convenient? Connect…