AI Primer for B-to-B Marketers

Understanding the basics of applying artificial intelligence to marketing

By Erik Sherman



Jim D'Arcangelo, VP of marketing at the employee management platform, relies on artificial intelligence (AI) to help fuel the company's B-to-B marketing efforts. By using AI technology to test new marketing offers and create predictive modeling to improve segmentation efforts, the company has made great strides reaching prospects and driving revenue.

"We were able to almost double our revenue and sales opportunity, [quadruple] leads with better lead quality, and more than double sales productivity, all while cutting our cost of acquisition by 60 percent," D'Arcangelo says.

Despite these eye-opening results, most B-to-B companies have yet to jump on the AI bandwagon. Many cite a general lack of awareness of what AI is, how it can benefit marketing and the business as a whole, and the mistakes to avoid. The good news is that once companies understand the real options and learn to use them effectively and profitably, they can gain a distinct competitive advantage.


Defining AI

In simplest terms, AI is a collection of technologies that includes data analysis, predictive modeling, pattern matching, machine learning, and adaptive systems. Automation — running processes at speeds that humans could never duplicate — is at the heart of AI and key to quickly developing new business opportunities and landing new customers.

Success with AI, experts say, depends on how the tools are applied to various strategic marketing initiatives. The benefits can include:

  • Performing tasks that would be too time-consuming or tedious to do by hand.
  • Automating many marketing and communications activities, which frees staff for more valuable work.
  • Better targeting customers in real time.
  • Using software to handle large-scale marketing projects.
  • Tackling operational challenges in ways never before thought possible.
  • Using data to make better decisions.

Fifty-nine percent of respondents to a Narrative Science study who use AI and big data technologies together said they are measurably better at turning data into information that can be used to solve business problems.

AI has been around for decades, but it's just now starting to penetrate the business arena. Forrester and Gartner peg AI as one of the top emerging technologies to watch in 2017. Moreover, the AI market is projected to be worth $16 billion by 2022, growing at a compound annual growth rate of 62.9 percent, according to the market research firm MarketsandMarkets.

B-to-B companies have been slower than their B-to-C counterparts in adopting AI tools for marketing purposes, says Kimberly Nevala, director of business strategies for SAS Best Practices at SAS. She points to the fact that most consumer brands market their products via mass media outlets, while B-to-B engagement generally happens through relationships salespeople cultivate with buyers and influencers at client and prospect companies.

That said, because B-to-B target markets are generally smaller than those in the B-to-C space, marketers could more easily implement AI to help them identify people interested in their products and services and figure out how to reach them.


Score the Right AI Mix

Determining which AI tools to use and where to use them is no easy task. "With 15 to 20 tools, you can build in predictive capabilities, targeting capabilities, optimizing capabilities," D'Arcangelo says.

While that may be true in a perfect world, each B-to-B brand must choose its own path, says Aman Naimat, SVP of technology at the business marketing cloud vendor Demandbase, noting that the decision depends on the audience and the particular campaign.

"You don't want to apply AI everywhere because it takes investment and can waste money if used too broadly," he notes. "You want to apply it at the place where you have the maximum waste in the system and could get the maximum benefit if it works, and where you actually have data that could be brought to bear to solve the problem."

Eric Lewis, VP of demand generation at RingCentral, a communication and collaboration systems vendor, says he works with "a lot of disparate technologies," such as Marketo and Salesforce, for closed-loop ROI reporting. "A lot of people talk about it [AI], but I can tell you the exact return on investment for every dollar I'm spending," he says.

To take full advantage of AI, Lewis warns, B-to-B marketers must have a high threshold for preparatory work. "At a minimum, you need three to six different data sources to be successful — and it may be more like 10 to 12," he says. "Trying to get all of that data normalized and into a single repository or data warehouse is ultimately one of the biggest challenges."

"You want to apply [AI] at the place where you have the maximum waste in the system and could get the maximum benefit if it works."
— Aman Naimat, SVP of technology at Demandbase


Avoid the Mistakes

For all the benefits AI can provide, it's not the be-all-end-all of marketing. "You still need to understand the persona of your buyer," D'Arcangelo says.

As an example, D'Arcangelo points to a cable company that wants to impose a rate hike on heavy-usage customers. Using AI, the company identifies the customer segment that watches the most television per day. "The people in the boardroom say, 'AI is amazing,'" D'Arcangelo says. "Then they come to realize after doing qualitative analysis that those people are unemployed."

Understanding prospect and customer psychology is also important because AI can amplify bad assumptions or practices. "It's the model of compounded interest, that data owns you and you've fallen into a terrific trap," D'Arcangelo says.

Another challenge is that AI technology can't automatically pivot fast enough to keep up with the speed of change in the business world. For example, AI machine learning uses unstructured data, or written human communication. It requires people to manipulate the software to interpret specific content, such as slang, humor, and sarcasm. But language is not static and can alter quickly. "What happens when the nature of the input changes?" asks Anthony Scriffignano, Ph.D., SVP and chief data scientist at Dun & Bradstreet. "You have to retrain the software. But how do I know [when I need to]?"

What's more, companies must integrate all AI tools they acquire into a single set of workflows and processes. The biggest mistake some business marketers make is to "buy a software package that's sold to them as Skynet [from the Terminator movies] and they think they can plug it in and it works," only it doesn't, says Trae Clevenger, chief strategy officer at the marketing agency Ansira.

Business marketers may also underestimate the complexity of AI, the budgeting requirements, or the type of staff needed to effectively use the technology. That makes the company vulnerable on a number of levels.

Despite these caveats, AI capabilities are remarkable and, as marketers like D'Arcangelo have found, the results can be staggering. By quickly adopting AI tools and technologies — and integrating them correctly — B-to-B companies can begin to build a significant competitive advantage.



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