The ‘art' of selling and related approaches are not only a cliche, but they are also a waste of time. For example, about 80% of B2B Sales-Qualified-Leads do not convert, and over half of previously committed or expected sales (54%) do not close.
Businesses are aware of the issue and are increasingly implementing sales technology such as CRM systems, auto-dialers, e-signatures, email tools, and other tools. These are helpful, but according to a recent survey, only half of salespeople (51%) use them, and the majority still rely on people skills to clinch a sale
The issue is that much of the technology is geared to automate processes rather than address the true issue: the soft skills required to close a deal.
The next step forward is AI and deep learning.
Multiple industries are progressively embracing the advantages of cutting-edge artificial intelligence breakthroughs. AI integration in sales is predicted to increase faster than any other technology, according to a recent Salesforce analysis. It is not intended to replace salespeople; rather, it is intended to boost sales efficiency and skill sets.
Until recently, the most sophisticated way for companies to use sales-technology to optimize sales performance was to analyze transcribed previously recorded sales conversations (via Zoom, Webex, MSFT teams, etc.) and apply NLP/NLU methods to extract and understand what the best performing sales professionals say to prospects, on the assumption that what is being said, literally, by a successful. Conversation Intelligence (CI) is the name given to this technology, yet it has considerable limitations.
Substrata, an Israeli firm, is utilizing deep learning's ability to take things even farther. “The analysis produced by most companies using CI is insufficient if you genuinely want to understand the interplay between the salesperson and the prospect,” says Substrata CEO Ori Zuckerman. It's all based on the syntax, the words used, and what was spoken. We examine the manner in which things were said or communicated.
“Present-day sales-technology solutions, such as CI, miss what is truly being expressed and are unable to detect implicit social signals hidden in the nuances and subtleties. Because attitudes, intentions, sentiment, sarcasm, and relative social standing are expressed non-verbally, non-verbal parts of discussions are not noticed. We set out to develop a device that could detect nonverbal social signals. We concentrate on the subtext – the dialogue's profound underlying social context.”
According to studies, nonverbal communication accounts for 66 percent to 93 percent of interpersonal communication. Substrata developed software that can precisely assess essential social signals conveyed through body language, location & distance, voice prosody, and interpersonal synchronization in order to promote insight and understanding.
Substrata does this by combining deep learning and deep reinforcement learning architectures. This new technology may be used in a variety of communication channels, such as emails and online conference calls, and it interacts with Gsuite, Salesforce, MS Dynamics, and other systems. The data acquired is then utilized to assist salespeople in becoming more aware of and sensitive to implicit social cues in sales interactions. This data is remarkably useful in supporting sales teams in completing deals and strengthening client relationships.
“We want to replace a lot of old sales techniques and help ordinary salespeople become highly sophisticated dealmakers,” Zuckerman says. “We're deconstructing the 'art of sales' and replacing it with the 'science of sales.' This was previously impossible and has now been made possible by new deep technologies. It is the industry's next step.”
Technology and scientific advancements have the potential to propel sales to new heights.
Substrata's methodology is based on the exciting and groundbreaking new subject of social signal processing (SSP). SSP makes sense of nonverbal communication using deep learning models. It is a multidisciplinary field encompassing computer science, social science, and cognitive and behavioral psychology.
PIE (Pragmatic Intelligence Engine) is a multimodal conversation analysis API engine included in Substrata's social signal processing technology. PIE is a piece of software that analyzes nonverbal clues in text, audio, and video communication and makes the results available to third-party software. On the other hand, its ‘Q Beta' product is a sales communication assistant that assists sales professionals in improving deal win-rate in real time. It can be integrated with existing email providers, sales software, and CRM systems.
The cutting-edge models look at more particular interpersonal factors like perceived competence, impression management, social roles, and interpersonal synchronization in addition to sentiment. These advancements, especially in light of recent global events, push the frontiers of what sales technology can achieve and where the industry is likely to go next.
Zuckerman notes, "Substrata was founded in 2019 with the help of some of the best minds in the field." “In the business software industry, discoveries in the realms of social signals, social intelligence, nonverbal communication, and pragmatics are under-explored and under-utilized. When we first started looking into the area and possible applications for our ideas, we realized that using technology to B2B sales was a no-brainer.”
“We've crunched the numbers. The ‘traditional' sales approaches do not work, have never worked, and will never work as long as the crucial aspect of interpersonal interaction is overlooked. The increased usage of emails, texts, phone conversations, and videoconferencing has already aggravated the situation. Then came the epidemic, which hastened everything. This type of technology can significantly improve the soft skills required of salespeople in today's world.”
The sales technology industry is gradually turning sales into a science. The next obvious step is for forward-thinking organizations like Substrata to use deep learning (AI). Human contact can be delicate and difficult to judge, but technology is likely to assist.
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