Many banking organizations have a "voice of the customer" program for capturing insights via surveys and such other signals as speech analytics and digital behaviors. Many have also implemented a "voice of the employee" program relying on similar signals. Yet few bring these together in a meaningful way. They are missing an opportunity. Business units with top quartile employee engagement see customer ratings that are 10% higher compared to units in the bottom quartile, according to a Bain & Co. survey from 2016.

Lockdowns are lifting but customers aren't rushing back to their offices in a hurry. The Covid era fast-tracked sales professionals into a world of digital selling whether they were ready for it or not. Grounded sales teams have quickly had to learn how to network and engage digitally. Before Covid, the average sales person spent 36% of their time in contact/meeting customers. During Covid, 77% of sales professionals said they're holding more virtual meetings.

Throughout most of recorded history buying and selling has been part of daily life. Whether it's agricultural products or the latest software, selling is a communication process whereby one side works to fulfill the needs of a second party via their product or service. The ability of the sales person to properly communicate why a prospect should buy or sell is the reason their role exists. Once an account relationship is in place less human interaction may be required (or desired) and automating the ordering process probably makes sense, except for new products or up-selling opportunities requiring human sales interaction. AI sales tools can augment the sales process both today and in the near future in so many time saving ways (if the right technology is applied, the reps are properly trained, buy into it and use it every day).

Hands up if you still think Artificial Intelligence or AI is a Spielberg film, and has something to do with Robotics? Until quite recently, it really didn't occur to me that AI Artificial Intelligence had anything at all to do with selling. So should we be using AI in Sales? But first I will explain why I might take this view. You see when I started selling ET had just been released on the big screen, and the Space shuttle had not long started its missions into the final frontier.

Mumbai: Sebastian Thrun is a man of many parts. The president and co-founder of e-learning company Udacity, is not only an innovator and computer scientist but also CEO of Kitty Hawk Corporation that makes flying cars and chairman of Cresta.ai--a Germany-born Thrun was earlier a Google VP and Fellow. At Google, he founded Google X and Google's self-driving car team. He is currently also an Adjunct Professor at Stanford University and at Georgia Tech.

AI is rapidly creeping its way into the software we use on a daily basis. Everything from CRM to Account Based Marketing (ABM) to marketing automation is getting "smarter." The promise of AI powered systems to suggest qualified leads to a B2B sales person is very exciting. One aspect of AI that is very exciting is its ability to tap into unstructured data to learn more about prospects as they engage with a brand's digital channels. Examples of unstructured data include online engagement such as tweets, comments, likes, shares, etc. Think about the potential for smarter systems to reduce much of the heavy lifting associated with identifying qualified sales opportunities.

Do your sales people have what it takes to be successful in educating, engaging with, and selling to your customers? Ensuring that each sales person has the right information and content at their fingertips to help them to improve the likelihood of closing a sale is critical to sales ops, sales enablement, and sales team managers. Over the last 20 years, since the inception of the digital revolution through the laptop, finding ways to help the busy sales person to get this content ready to go has become even more important....

Artificial intelligence (AI) technology has exploded in recent years. Common AI personal assistants such as Siri, Alexa, and Google Assistant are helping people figure out their daily schedules, controlling the lights and thermostats in homes, and helping commuters find the best route to work. And while these recent advancements are amazing, they're really only a sneak preview of how AI can and will impact society as a whole. Sales efficiency is an area ripe for AI assistance – AI is at the point where it can be just as useful, if not more useful, in the office than at home on one's handheld device. Business AI has evolved from being a sophisticated calculator or database analyzer to an entity that can tell businesses solve their biggest challenges and enhance their market offerings. Although more organizations spanning industries are tuning into the potential of AI, many are still not capitalizing on its potential to transform their sales practices.

The B2B salesperson is dead. There are scores of studies telling us that most of a customer's buying process is already accomplished before a salesperson is even contacted and is merely allowed to make the transaction. Forrester Research predicted in 2015 that 1 million US salespeople would lose their jobs to self-service and ecommerce by 2020. While they updated this report in March 2017 the statement largely stays the same. The highly reputed Edelman Trust Barometer reveals in 2017 that trust in businesses declines and that "CEO credibility decreased the most, dropping to an all-time low".

With the permission of both sales people and the customers, calls are recorded and stored in the cloud (as both audio and video files). Gong goes through a first-pass machine transcription of the calls and then applies NLP to work around the inaccuracies of the initial transcription and deal with the complexity of human to human interactions. In contrast to the relatively straightforward human to machine interaction in the case of Siri or Amazon Echo, the sales conversations Gong is tackling are free flowing, multi-party, and riddled with interruptions and speech fragments. The text of the transcription is categorized by pre-set topics such as "budget," "timeline," "pricing," "competitors," and "urgency." The analysis of the conversation shows which topic was discussed, when, and by whom, how much a sales person is talking vs. listening, which questions are asked, and the objections raised.