AI in marketing

AI in Marketing: The New Frontier

If you haven’t seen the cover story for the latest issue of PeerSphere magazine, check it out! The article features Conversica CMO, Carl Landers, along with other marketing leaders in the technology industry, on their perspectives about how AI will positively impact the way marketers work. 

During Super Bowl LI, more than 100 million viewers heard that “one of the most powerful tools our species has created” was being unleashed to search out every possible deduction for individual tax returns this year through H&R Block. An hour later, Patriots quarterback Tom Brady appeared to leverage his own version of artificial intelligence when he learned the subtle weaknesses of a clearly more talented Falcons team, overcoming a 25-point deficit and securing a win.

While AI functions have been widely deployed for years to improve everything from manufacturing efficiencies to personalized searches, marketing has yet to realize the full potential of this game-changing innovation. However, it is most certainly on marketers’ radar.

Last year, a report by Weber Shandwick showed that 68 percent of CMOs were planning for the AI revolution, and a majority said they expected AI to have a bigger impact on marketing than even social media.

Dario Debarbieri, Chief Marketing Officer for IBM Watson Customer Engagement–North America, also believes that AI represents a revolution for marketers today—and that the CMO who fails to leverage cognitive computing tools today would be like the CMOs who failed to establish company websites in the late 1990s.

“Imagine you were a CMO in 1999, and you decided that you were not going to create a new digital channel by building a website that had the capability to sell your products,” Debarbieri says. “It’s almost the same comparison today with cognitive computing because if you’re a CMO, acting and reacting on old data and using unintelligent tools will be a fatal mistake.”

 

Looking Beyond the Past

 

The ability to look toward the future to predict consumer behavior is potentially one of the greatest benefits that AI has to offer. While most marketers still look to past data to inform their customer engagements, the holy grail lies in marketing’s ability to process and act on customer data in real time to create the personalized, relevant engagements that they expect. However, according to a recent CMO Council study, only 7 percent of marketers revealed that they are able to consistently create real- time, personalized engagements for the customers across both digital and physical touchpoints.

Debarbieri says that another recent survey illustrated the importance of cognitive computing tools for CMOs: 75 percent of companies today struggle with 25 percent of their available data, and worse still, they have virtually no access at all to the remaining 75 percent of their unstructured data.

“We know that all CMOs have problems dealing with data,” Debarbieri says. “We have so many dashboards and so much information, but most of the information is not real-time, and a vast amount of data is being created in multiple forms. There is the data that a company will create or acquire and will know well, but the unstructured data—which comes from comments on social media, different channels of communication like video, audio, email, instant messaging, etc.—represents an immense amount of information that we can’t grasp without cognitive capabilities. For the most part, marketers only understand the impact of that data in past tense and have to develop their own conclusions and decisions based on the information that they receive. On rare occasions, conventional data tools will also give you real-time information that helps you to make rapid decisions. But what you cannot do—which AI allows you to do—is actually predict events with intelligence embedded so that you have a sense of future outcomes as well.”

 

Machines Are a Marketer’s Best Friends

 

Most companies have reached a point at which the sheer amount of data coming in and the ability to process, interpret and act upon those insights are beyond what humans have the capacity to do. According to a 2016 CMO Council study, only 3 percent of marketers’ data sources are delivering a comprehensive view of their customer that would enable personalization.

However, the digital transformation that marketers today are seeking most certainly entails the ability to mass-personalize content and communications at scale and to an audience of one. With machine learning helping companies to gain a better understanding of customer behavior and more accurately predict the next action, AI holds a great deal of promise when it comes to the ability to deliver a comprehensive view of the customer and personalize at scale.

Carl Landers, Chief Marketing Officer for Conversica—an AI solutions provider—explains that when it comes to personalization, the possibilities are really endless.

“AI is going to give us the ability to automate things that we’re already doing and free us up to focus on things that we’ve never been able to do before,” he explains. “This includes personalization at mass scale. With machine learning and natural language processing, the machine is going to be able to extract insights from all of the internal and external data that we have about customers and make the right decisions in terms of what an individual should receive, what that next offer should be, what a web page should look like, etc. in order to best fulfill their needs. As a marketer, this mass personalization has not been humanly possible, but the machine is going do it for us, and it’s going to be a win-win for the marketer and consumer.”

Using AI, Landers points to the Los Angeles Film School, which was able to increase lead engagement by more than 33 percent due to the implementation of an AI assistant, which followed up with prospective students to set up appointments for them with admissions consultants.

“When you have 10,000 leads coming in every month, it doesn’t make economic sense to have a human try 12 times to reach someone when there are constantly new people coming in, so you might try two or three times and move on,” he explains. “However, research shows that to reach people, it can take up to 12 attempts to get their attention, so think of all the money they’re spending on advertising to drive that interest and not reaching people. With the AI assistant, the school generated a 1/3 increase in sales pipeline, which wouldn’t have been humanly possible otherwise.”

 

The ROI of AI

 

When it comes to measuring the real value of AI, there are two types of AI that must be viewed in much different ways. According to Landers, autonomous AI—which processes information and automatically serves up the next offer or content based on data, thus requiring a much higher level of trust—makes it easy to determine ROI because the numbers are direct correlations to the implementation of AI technology. However, advisory AI—which provides intelligence but ultimately allows the marketer to make a final decision before implementation—is much more difficult to justify because the technology enables better decision-making, but at the end of the day, the marketer still makes the decision, and it is difficult to place a dollar amount on a better decision.

For Kathryn Morrill—former Inside Sales and Marketing Manager for CoolFront Technologies—the AI assistant that her company implemented was viewed as a true extension of the marketing and sales teams as it managed all of the leads that came in. When a potential prospect viewed a piece of content, they entered the top of the funnel, and the first point of contact to those at the top of the funnel occurs through their AI. The AI then did lead qualification, which made the role of sales much easier and the entire sales process much more effective, so the most obvious initial value from AI was qualitative.

“Before we could really put a quantitative value on our AI, we knew the amount of time that it was saving and that it was providing a lot better quality of life for our marketing and sales teams because we didn’t feel like we were drowning in things that we couldn’t get done,” she explains. “Quantitatively, there was initial savings because we didn’t have to hire another employee, but when we started comparing the conversion rate of those who engaged with our AI to those who did not, we were able to see a 10-percent increase in conversion, and we attribute that to the fact that the AI is better at gauging who is a true, ready-to-go customer.”

 

Before Taking the Leap

 

As with any new strategy, it is important to understand the complexities involved in AI implementation upfront and to have a plan in place to streamline the process as much as possible. Landers emphasizes that while AI will ultimately make it much easier to streamline communications between buyers and sellers as much of this process will one day occur automatically through bots, the responsibility of the marketer will be in packaging and articulating the brand’s value as commerce moves beyond self-service and toward auto-service.

“Today, AI is really about empowering humans to do better work,” Landers says. “Tomorrow, it’s going to be about the AI interacting and taking a lot of things off our plate so that we can live better lives. It may seem far off to have a company bot interacting with a personal bot in order to make decisions, but I believe that is what we are moving toward.”

As companies move forward in this new world of AI, Debarbieri says that regardless of the implementation choice, it is important that companies retain ownership over their own data. While he says that conventional data analytics software can offer important value for CMOs, he believes the increasing prevalence of unstructured data and the importance of real-time campaign recommendations will make AI platforms indispensable for CMOs.

In addition, Morrill explains that both the greatest benefit and greatest challenge of what AI can do is that the possibilities are endless, which can be enlightening but intimidating as well.

“If you don’t limit yourself to what you’re accustomed to doing traditionally, you’ll be able to see greater results just pushing by yourself a little bit outside your comfort zone,” she says. “The opportunities are endless, which can be very daunting because it’s very time-consuming to implement an entirely new strategy, and it requires a huge transition. But even if you’re a little hesitant, implementing AI will not be something that marketers will regret.”

 

Dario Debarbieri

Chief Marketing Officer, IBM Watson Customer Engagement–North America

Dario Debarbieri began his marketing career in 1990. He studied law and economics at the Universidad de Buenos Aires. Throughout his career, he has held several leadership positions, starting as a Marketing and Communications Manager for what became the largest private pension funds company of Argentina. When he joined IBM in 1997, he was responsible for several strategic projects, including the IBM Argentina image recovery plan as Marketing Manager, and later become Manager of e-Business Marketing for Latin America. In 2001, while in New York, he managed the largest web-based collateral project while working with the Corporate Marketing Identity and Design team. He managed the One Voice Marketing project that expanded IBM’s marketing into 25 countries, including the first investment plan for IBM China and India. The project later became the Marketing Management System for all growth markets. In 2003, Debarbieri joined the IBM SWG Team, where he held leadership positions in IBM USA, IBM Spain, IBM Middle East and Africa, and SWG Marketing in Somers, New York. He now serves as CMO for IBM Watson Customer Engagement in North America.

 

Carl Landers

Chief Marketing Officer, Conversica

Carl Landers has been Chief Marketing Officer and Senior Vice President at Conversica LLC since March 2015. He oversees all strategic, operational and financial aspects of Conversica’s marketing efforts, including corporate marketing, demand generation, communications and events. Prior to joining Conversica, he served as Chief Marketing Officer at Serena Software, beginning in 2000. He joined Serena as Vice President of Product Marketing and Demand Generation after serving in a similar role at CA Technologies in its portfolio management business unit. His previous experience includes senior marketing, product management and product development roles at Niku Corporation, Tyco International and Raychem Corporation, as well as startups Perfect Commerce and Zoho Corporation. He holds a bachelor’s degree from Stanford University.

 

Kathryn Morrill

Former Inside Sales and Marketing Manager, CoolFront Technologies

Kathryn Morrill is a former Inside Sales and Marketing Manager for CoolFront Technologies. She is a results-driven professional business manager with key management skills and expertise in business development, comparative growth sales, trade marketing and CRM. Prior to CoolFront, she worked as a Trade Marketing Manager for EC Scott Group, a training, service, and sales company that focuses on building strong partnerships with prestige beauty brands and independent retailers. Previously, she worked as a business teacher for Williamson Central Schools in Buffalo, New York. He earned her master’s degree in business, management, marketing and related support services.

 

This blog post originally appeared on PeerSphere and was reprinted with permission.

 

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