Artificial intelligence, or AI as it’s called, has been a buzzword for nearly a decade already, yet sometimes it still feels as though we’re just in the early stages of discovering what predictive analytics and machine learning can do for enterprises.
Nowhere is this truer than in marketing and sales functions. According to Forrester, as of 2017 marketing and sales accounted for more than 50 percent of all AI investments.
But when you look at investors who have already sunk serious money into AI projects, only 45 percent have seen any results at all. And among those who are seeing results, 25 percent agree that they’ve become more effective in their business processes. These discouraging numbers paint a vivid picture: Most marketing and sales teams simply aren’t properly equipped to implement AI.
As a marketing leader who has helped companies like Salesforce and Deloitte with digital marketing transformations, I’ve seen many “use cases” of how AI is being employed by today’s leading marketers and sales forces. And I’ve learned that often, the best way to kick off an AI initiative and make sure everyone is on board is to show them where others have succeeded.
Here are three ways in which AI has completely transformed enterprise sales and marketing in the 21st century for at least some companies:
1. Predicting outcomes to increase lead generation
Marketing is by nature a very competitive and data-driven endeavor, especially at the enterprise level. Every facet of global, cross-channel marketing relies heavily on a competent knowledge economy comprised of data inputs (and proactive recommendations) gathered at every touchpoint with visitors, leads, and customers.
A great example of an effective AI-powered marketing engine was put together by CenturyLink, which provides cloud and security solutions to digital businesses. Before implementing AI, CenturyLink already had a sales team of about 1,600 people to handle all its incoming leads, and even that number was barely enough to meet the demand, according to Harvard Business Review.
“Angie,” a Conversica AI virtual assistant, was hired to do a simple job: comb through thousands of leads, send them emails, and determine which leads were “hot” and which were not. If she found a quality lead, she would entrust it to a human salesperson.
So, Angie set to work right away and started sending out 30,000 emails per month.
As it turned out, Angie has been extremely good at her job. Not only does she consistently find about 40 new hot leads per week, but she is also able to understand 99 percent of the email replies she receives from customers. The 1 percent she doesn’t understand are forwarded to her human manager. Turns out Angie is also good at routing the right leads to the right reps.
All in all, CenturyLink has earned $20 for every $1 it’s spent on Angie: That’s an impressive 1,900 percent ROI.
2. Recommending next steps and resolving issues
Another major way AI has helped enterprise marketing and sales teams is with the customer journey and customer support — integral parts of the marketing and sales life cycle.
As an example, the printing giant Epson America was drowning in leads and didn’t know how to handle them anymore. Where CenturyLink was using its AI assistant to find and qualify leads (i.e., marketing), Epson had no problem with marketing or outreach — if anything, the company was too good at this. It receives, on average, 50,000 leads per year.
According to Salesforce, it takes six to eight touches for a lead to become a customer. Normally, all these touches are the responsibility of a human sales rep, whose time and availability constraints aren’t required when the company uses an AI sales rep. Epson knew this, of course, and hired the same AI that CenturyLink had used to follow up at the right time, without fail, until it got a response — for all of those 50,000 leads.
In no time at all, Epson realized the force-multiplier potential of AI. It also realized that the AI virtual assistant could help its human sales teams with cross-selling, upselling and recurring orders, as well. It could also discover and report unresolved customer issues to the right customer support reps immediately.
Before it implemented its AI sales assistant, Epson had been accustomed to seeing around 20 responses for every 100 leads. But since implementing the Conversica AI, it now receives a staggering 51 responses — a 240 percent increase — as well as a 75 percent increase in qualified leads.
This led to an additional $2 million in revenue in the first 90 days of using that AI.
3. Creating disposable content, even advertising
Perhaps the most surprising AI implementation I’ve seen at the enterprise level is the ability of AI to replicate human-like writing and content creation. Researchers have spent decades trying to make computers write the way humans do, but only in recent years have they been successful. For certain types of disposable content, AI has already shown itself to be more effective than a content team would be.
The examples of AI writers emerging in the worlds of publishing are numerous: Forbes writers are planning on using an AI to help them pen their drafts; a slew of newspapers, including the New York Times, and the wire service Reuters, use AI to write real-time financial reports and sports recaps (called “robot reporters“); and OpenAI claims to have developed an AI writer so good that it is too dangerous for public release.
Even more incredible, Toyota recently used IBM Watson’s machine-learning capabilities to design a new kind of advertising campaign for the Rav4: one that generates entire ad scripts. They’ve even given it a catchy label: creative programmatic.
According to Ad Age, Toyota gave IBM Watson a list of the top 1,000 recreational activities that you might use a car to get to and tasked Watson with pairing the activities together in unexpected and intriguing ways. Watson’s video script outputs were then fed to another AI tool, a video generator that stitches together stock and original footage, called Imposium. The final results: 300 unique, targeted video advertisements that were used as Facebook and Instagram.
Toto, I don’t think we’re in Kansas anymore.
In the 21st century, AI is starting to look less and less like science fiction and more like the times we’re living in. For enterprises that actually have the budgets to implement and experiment with AI pilot programs for marketing and sales — as we’ve seen, the sky’s the limit.
If I’ve learned one thing from running various digital marketing transformations that also better align sales and marketing, it’s that AI is making its way into every part of the enterprise technology stack. The ROI is there. Its short- and long-term impact can be tremendous.
But don’t underestimate the time and effort required. Take inspiration from other brands that have hit the ball out of the park with AI initiatives. Keep things simple for a pilot, stay agile during implementation, and make sure to hire the right team for the job. You will see results.