The Key to Business Growth: Using AI to Break Barriers in Sales Conversations
Every year, businesses let hundreds of millions of dollars slip through their fingertips because they fail to give customers what they want.
This isn’t a matter of indifference. It’s a matter of missing opportunities embedded in conversational nuance. Turns out that us humans, the very architects of language, have a hard time deciphering – and acting upon – subtle language indicators in conversations.
This has been an enduring problem for businesses that transact sales over the phone, since 92% of all customer interactions happen over the phone, according to GetCRM.com. But that’s about to change.
Major advances in artificial intelligence can now help businesses decipher conversational nuances at scale. Most importantly, AI can guide companies on how to seize sales opportunities that would have been lost until just recently. According to Harvard Business Review, the number one use for AI in business is sales and the second is marketing. AI generates about $1.4 trillion to $2.6 trillion of annual value in sales and marketing.
Data learned from hundreds of millions of customer-to-business calls shows that when customers are ready to buy or when they feel frustrated, they say certain phrases, at certain moments, to communicate their intent or emotional state. Yet only 13% of customers believe a salesperson understand their needs, and miss these signals – or react with their own vitriol or frustration, according to The Brevet Group. The latter can spell disaster for a brand.
A salesperson is often the first point of contact a customer has with a business. When sellers don’t understand what customers want – or worse, get overtly frustrated – customers can unleash via social media, creating negative word-of-mouth impact.
Herein lies the struggle. Understanding consumer intent is difficult and messy, but it’s critical in order to close more sales and drive growth for the long term. Here’s how AI can help in three important ways:
Understanding consumer desires in real-time
What does the consumer want? Ah, the (multi-)billion-dollar question. Each customer conversation has its own unique arc and flow, but when hundreds of millions of these conversations are analyzed in aggregate, concrete patterns emerge.
The data shows that certain phrases or subtle shifts in sentiment can affect sales outcomes and impact the quality of the customer experience. The net effect of these bad experiences can, over time, taint the reputation of a brand. (Just run a search for “cable” and “customer service” in Twitter and watch the repeat offender companies that scroll to the top.). Thirteen percent of unsatisfied customers tell 20 or more people when they’re unhappy with a product or service, according to White House Office of Consumer Affairs.
The value of AI is that it can help inform sales tactics by shedding light on how to respond best during customer dialogues. It also helps provide personalized experiences, both of which are key to driving growth. According to research from
Salesforce.com, 64% of consumers and 80% of business buyers said they expect companies to respond to and interact with them in real time.
AI can also extract out key words and home in on product or service mentions during a conversation, which may get missed in the course of a fast-evolving dialogue.
Customers – surprise – aren’t always direct about what they want. And sellers are only human. They may not catch every detail or upsell opportunity. For a salesperson, AI is like having a teammate sitting with you on the call, reminding you of what to talk about next.
The power to predict outcomes and rescue lost opportunities
You could argue that a smart, successful salesperson is a master of her craft. She’s honed her skills over hundreds of hours of customer conversations. And her ability to empathize and understand customers is what puts her at the top of her game.
But even the best of the best can’t capture every lead every time. Which is where AI comes in. It fills the gap. Through natural language processing using deep learning models, it scans entire conversations, gathers insights and produces analyses in real time as conversations are happening.
With AI, businesses can, for instance, get an alert when potential buyers hang up without making a purchase – or even when customers leave the conversation disappointed. That’s because AI can identify negative sentiments in real-time, predict outcomes with high confidence and rapidly communicate this feedback to a business. Is the customer likely to buy or likely to leave? Did the seller understand what happened after the call? Did the customer’s intent get fulfilled?
Say, for instance, a customer wanted a certain item that wasn’t in stock. Instead of saying no, which is the norm on most customer calls, AI stockpiles this data and alerts the sales team to call that customer back when the item is in. It can also inform the sales manager to call a customer back when they’ve had a poor experience – BEFORE that customer calls a competitor. AI supercharges the overall customer experience and saves what would have been lost opportunities.
Recommending Next Best Actions – The “NBA” of sales
Sure, all this data is great, but how can businesses harness the power of AI to convert more and grow customer loyalty over time? The answer: offer suggestions tailor-made for each caller. Every person who calls a business wants to feel heard. And the way to cement that feeling at the end of a conversation is to offer next best actions, such as incentives, products or add-ons, that fit exactly what that customer is interested in. The aforementioned Salesforce report also shows that 59% of customers say tailored engagement is very important to winning their business.
This is key because we’re all so used to being sold things we don’t need. AI can take conversational data, glean customer interests, and build that against demographic data to create a rather robust profile of each caller.
The data is abundantly clear: traditional selling tools are no longer sufficient. We’re on the threshold of a new era, one in which increasingly sophisticated AI technology will seep into every facet of everyday life. In fact, sales teams that use AI see an increase in leads and appointments by more than 50%, cost reductions of 40% to 60%, and call time reductions of 60% to 70%, according to the Harvard Business Review.
If you need a dialogue engine that will allow you to develop next-gen conversational IVR applications while being compatible with the VoiceXML standard, this is a must read.
27 Nov 2019
The combination of AI and speech technology is transforming the way marketers think about customer experience, but many are still hesitant to put plans into action, as consumer expectations may outpace technological reality.
04 Nov 2019
Today's consumers don't just want personalization, they expect it. And the call center is no exception. As organizations attempt to meet these expectations, gaining an understanding of the Voice of the Customer is imperative.
30 Oct 2019
The latest advances in speech-to-text technology enable analytics software to deliver the most accurate and complete customer insights. To do so, robust ASR solutions must be able to do five things.
16 Oct 2019
GDPR has already had wide-ranging consequences for companies collecting data, and now some are calling for federal regulations in the U.S. Voice-data isn't exempt from the regulations, and vendors need to be ready.
25 Sep 2019
For years, investments in the voice channel have taken a backseat to digital. But thanks to the rise of IoT devices and AI-driven conversational experiences in the consumer realm, organizations must rethink the role of voice.
18 Sep 2019
Sentiment analysis has the potential to revolution voice search, but as of now, search providers are not taking advantage of all it has to offer. Find out how using sentiment analysis can lead to more accurate search results and happier customers.
28 Aug 2019