Artificial Intelligence (AI) has changed nearly everything – and Sales is no exception.
It affects how customers buy – and how salespeople need to sell.
AI fuels buying choices we make every day – from the shows we watch and the routes our driver takes to the next item we order online.
Recommendation, location and association algorithms are our behind-the-scene buying influencers – and they make AI creepy and cool: Creepy that our devices know and connect so much about us. Cool that what it does is actually helpful.
“The power of selling is moving away from the individual and toward the machine – machines that can now prospect, follow up, present, and propose without human intervention,” says Victor Antonio, author of Sales Ex Machina: How Artificial Intelligence is Changing the World of Selling. “In some cases, the machine will obliterate sales functions, while in others it will dramatically shift the locus of the focus further into the sales cycle.”
As with any industry evolution, some changes are good. Some will have a negative impact.
Here are 16 ways AI is changing sales – and how you can adapt with it.
1) Leads rise
Sales teams that have adopted AI have increased leads and appointments by about 50%, according to McKinsey research in the Harvard Business Review. In those organizations, AI (aka Machine Learning) has taken on the time-consuming tasks of connecting with leads, qualifying, following up and sustaining the relationship, researchers said.
2) Relationships grow stronger
AI technology can automate many sales activities – such as gathering customer information to determine needs, processing sales, taking product orders and preparing contracts. AI-enabled salespeople spend 40% less time on those activities, McKinsey researchers found. That leaves them more time to build relationships.
3) Selling time increases
With AI, most salespeople can spend more time actually selling.
“AI can absolutely have a positive impact on sales operations if it’s focused on decreasing the 63% of non-selling time spent by sellers,” says Mario Martinez Jr., CEO, Founder, and Digital Sales Evangelist at Vengreso, and host of the Selling with Social Podcast.
Martinez offers a real-life example: “We’ve deployed an AI-SDR bot from Conversica. Our SDR bot never goes to sleep, never makes a mistake, always updates the CRM, and always follows ups. These are tasks that weigh down sellers. Now we can focus on every buyer who says, ‘Yes, I’d like to have a phone conversation with your sales rep.
“We allow our sellers to focus more time on the preparation of the first meetings, rather than entering data and lead sources into the CRM.’ ”
4) Call time decreases
Sales teams already using AI are dropping call times by as much as 60%-70%, according to the McKinsey study. AI helps salespeople identify needs and align solutions before they make the call so they have less exploring to do on calls.
5) Costs drop
By automating lower-level sales activities with AI technology, some organizations have cut costs in half, researchers found. Salespeople time is spent increasing profits.
6) Time to close decreases
Because salespeople spend less time doing tasks at the top of the funnel, they have more time to devote to bottom-of-the-funnel tasks such negotiating smartly and closing deals, researchers found.
7) Personal touch decreases …
Experts say customers will manage as much as 85% of their relationships with some companies without interacting with a human by 2020. Customers will rely almost completely on automated bots and online transaction options, the McKinsey researchers found.
8) … but human touch persists
As AI is increasingly adopted, salespeople and managers will need to focus more on managing expectations, clarifying the ambiguous, making judgment calls and ultimately choosing the strategies that AI suggests.
Because AI will potentially offer more sales opportunities than organizations can handle, salespeople and leaders will need to monitor relationships and manage leads more closely so big sales aren’t lost in big data.
“We have to be smart about how we exploit (AI),” says Dave Brock, CEO of Partners In Excellence. “These technologies fall very short in the things that are most important to our customers in complex B2B buying. We can’t fail to develop the capabilities in our salespeople to help our customers.”
9) Management becomes less analytical …
Sales managers’ roles will change as machine intelligence can increasingly gather and analyze performance data, recommend solutions and make daily data-based decisions, according to research gathered by MBA Centra.
10) … but remains critical
But researchers admit: Leaders in sales will always fulfill critical roles that AI can’t. Leaders will still:
- create workplace culture
- build relationships with employees and customers
- hire good-fit salespeople, and
- act as moral and ethical guideposts for salespeople and the sales process.
11) Pricing becomes easier to optimize
AI looks at specific details of past deals that were won and lost – such as size of deal, alignment with product specifications, number of competitors, client’s ability to spend, territory, timing and influencers. Then AI can give specifics on optimal pricing.
12) Forecasting gets a boost
Despite challenges, sales managers do a good job of predicting their team’s sales numbers and setting goals.
But AI can help them predict with a higher degree of accuracy, Antonio says. That also gives organizations a leg up on operations – knowing better how to plan for production, inventory and resources.
13) Upselling and cross-selling becomes more obvious
Salespeople often focus up- and cross-sell efforts on all their clients. AI can help identify who is most likely to buy more and when. AI algorithms can help pick existing clients who are likely to sign on for more or better solutions.
14) Prioritizing becomes easier
Salespeople can often identify which leads to pursue, but knowing which leads to pursue first isn’t always obvious.
AI can take the gut-instinct out of those decisions with algorithms that compile historical transaction information, interaction details and social media posts to rank leads and chances of closing.
15) Customer lifetime value improves
Determining customer lifetime value has always been a challenge for sales leaders and salespeople. Who will renew? Who will leave? And, most importantly, why?
AI can help identify the health of relationships and point salespeople toward those that need attention and those that are healthy. Some organizations use AI to do this monthly so it’s never too late to extend the lifetime value, according to Louis Columbus, Principal at IQMS.
16) Best practices get better
AI helps sales organizations dig down into the techniques, approaches and time management strategies of its top salespeople (and the lesser performing salespeople, if you wanted it for comparison).
Then sales leaders can share insights and best practices across the team. This knowledge also helps managers choose new team candidates with similar capabilities consistent with quota-achievers.
Data matters first in AI
Adopting (or enhancing) AI requires full buy-in and committed resources. The good news is you don’t have to overhaul or get rid of everything you know and trust now.
Antonio suggests these best practices for AI:
- Focus on the data that already exists within your company that gives you the most complete picture of your existing customer base. Call on sale’s purchase and interaction data and marketing’s website analytics, campaign data and response rates to everything.
- Go beyond the obvious. Gather and add data from shipping, fulfillment, customer service and technology on what and when products and services are questioned, returned and/or replaced by customers.
- Put the data together with your Customer Relationship Management platform that has intelligence tools. (Most CRM platforms have embedded them or offer add-on apps now.) In many organizations, silos prevent leaders from combining and overlaying data. AI helps you get valuable predictions – on things such as response rates, prices and customer lifetime value – when as much data as possible is entered and combined.
5 traits of a strong AI project
What makes an AI initiative in sales successful? AI expert Andrew Ng suggests in the Harvard Business Review that AI pilot projects and existing programs:
- Are customized to a current business context. Whatever the company is focused on now – perhaps growing existing business, broadening brand awareness, launching a new line or increasing revenue – needs to be at the root of any AI initiative.
- Will be quick wins. Early AI projects need to have a high chance of success within six to 12 months. Focus on one that requires only the data you already have so there’s less data-collecting. Then there’s more analyzing, suggestions for action, actual action and review of results.
- Deliver meaningful, right-size results. AI projects need to deliver meaningful data and results – at least a little bit more than your existing analytics does. Aim for projects that focus on a specific, meaningful goal and prove about a 5% improvement.
- Partner with experts. Bring in an AI expert who can help launch and analyze the initiative – then possibly help build an entire AI program.
- Create value. Every AI initiative needs to either reduce costs, boost revenue or create new opportunities for business.
“AI for sales is badly needed to make us smarter and more well-informed while at the same time reducing the 63% of non-selling time,” says Martinez Jr. “That’s when salespeople can focus more on what they do best: sell. And their leaders can focus on optimizing their talents, the data and the results.”