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The business world is fast-moving, and staying relevant is an unending challenge. To keep up, companies increasingly invoke AI in their marketing regardless of their true expertise in the area. As a result, the real promise of artificial intelligence is lost in the hype, and it sinks into a sci-fi version of snake oil.
The unfortunate outcome is companies that stand to benefit considerably from AI-driven solutions are becoming wary of the claims of vendors. At the same time, marketers looking to highlight the business utility of their AI products are struggling to sell to a disinterested or distrusting audience.
So, how do you sell AI without causing your audience to roll their eyes?
Textio, a predictive writing platform used in talent recruitment, continues to find success using conventional tactics like videos, case studies, and co-branded events with customers like Johnson & Johnson, Vodafone, and Nvidia to demonstrate its business value. However, this strategy is not universal. If a competing client views your solution as a true differentiator, they obviously won’t rush to share that information and might even ask for non-disclosure agreements (NDAs). A new startup may very well have exceptional technology, but without big-name clients willing to publicly tout its virtues, it will need to turn to new avenues.
To explore these avenues, we spoke with leading AI marketers and brand communicators to find out what unique strategies they employ to stand out in an already saturated marketplace.
1. Ditch the buzzwords
You might be a savvy techie who genuinely understands and uses words like “neural networks” or “deep learning” in everyday conversation, but some people — including Protagonist‘s early prospective customers — might find that uncool.
“Protagonist started by trying to hammer home their unique technology by pioneering the buzzword ‘narrative analytics’, but this just wasn’t resonating with customers,” recalled Damon Waldron, vice president of marketing.
A veteran B2B marketing expert, Waldron currently heads the team at Protagonist, a company that leverages AI to capture the stories and beliefs that drive people’s behavior. Fortune 500 companies like Wells Fargo, Starbucks, and Microsoft use the product to assess consumers’ true feelings about their brands to develop a more effective communication strategy. Asked to distill the biggest challenge in communicating AI innovation, Waldron responded, “The tech news cycles are overly saturated with frilly buzzwords. It’s been a challenge to truly communicate the significance of a product via pen and paper when competing against so much noise.”
When the phrase “narrative analytics” did not connect with buyers, Waldron decided instead to position Protagonist against well-known, commonly used marketing strategies that his customers did understand. In comparison to his company’s solution, traditional market surveys are limited in scope and introduce bias, whereas social media monitoring tools are often shallow and don’t extend beyond positive or negative sentiment analysis.
He also uses Protagonist to market Protagonist. “We recently did an analysis of Harley Davidson as an exercise in how to reinvigorate a stale brand. We did that in three days. What we want is for the CMO of Brooks Brothers or another brand in the same situation to think about how they could use Protagonist,” he said. Waldron and his team can quickly assemble educational content on any trending topic, such as whether traditional investment managers are under threat from robo-advisors. “We can easily host a webinar on the topic or throw together an infographic on how millennials are investing and insert them into our sales and marketing emails,” he added.
2. Demonstrate alternative approaches
Artificial intelligence is comprised of many technical approaches, only a few of which are currently overhyped in the media. You may have heard companies boast about their use of “machine learning” and its trendy sub-field “deep learning,” but how many can you name that use “evolutionary strategies”?
One is Sentient Technologies, a company with more than 40 patents in artificial intelligence. Sentient educates its customers about its unique approach to evolutionary computation for digital marketing, ecommerce, and finance. In evolutionary strategies (ES), a set of candidate solutions is provided for a given problem and evaluated according to a “fitness” function. The best performing solutions “survive” and the poorly performing ones “die,” resulting in solutions that improve with each generation. A key benefit to this strategy is that, unlike supervised machine learning, evolutionary strategies don’t require large volumes of clearly labeled data.
“Unlike with deep learning, people intuitively understand how evolution works,” says Jeremy Miller, Sentient’s director of marketing. The company uses ES in conversion optimization software that automates website testing with the goal of lifting conversion rates and driving revenue. Instead of using historical data, the product evolves designs based on live, real-time data.
3. Personify your platform
Understanding how enterprise software works is rarely achieved just by browsing screenshots or reading spec sheets. As an alternative, personifying your AI-driven software can demonstrate the interactivity of your platform in a clear but friendly way. Though extra branding effort may be required, it is worthwhile if it results in clients finally seeing the benefits of your product and understanding its operation.
Tradeshift is one company that did exactly that. Its customers are executives who work in the relatively humdrum worlds of supply chain management, procurement, and accounts payable. “There is a disconnect between supply chain and procurement professionals and IT,” explains CMO David Ahrens. “Since executives don’t work too much on the tech side, this starting gap makes it even harder for them to understand AI. Yet many of them realize that AI is a technology they must get their arms around quickly.”
To overcome this “familiarity gap,” as Ahrens put it, Tradeshift personified its AI platform with a human face — Ada — with whom customers could interact in a natural and intuitive way. Giving the technology a conversational persona enabled customers quickly grasp the business use cases. Customers can easily ask Ada for help when making bulk business purchases to ensure they find the best prices in a category or stay under their procurement limits. Ada also helps them analyze their spending behavior from past periods in a multi-dimensional way.
Named after Ada Lovelace, Ada was born from an internal company hackathon. While Tradeshift’s capabilities extend far beyond what Ada can do, Ahrens cautions that you must take your customers on a buyer’s journey step by step. “If you say you have AI in everything, customers won’t know what to do with that information. Instead, they’ll get confused and won’t return. We decided to start from a specific use case and build from there.”
4. Tout your hard science background
Of the many talented PhDs and postdocs working at promising AI startups, how many of them can say they’ve deployed their algorithms on Mars? Deep space is the most unforgiving environment, with zero fault tolerance, limited space for hardware, and a need for autonomous operations.
When Edward Yang, managing director at Firecracker PR, started working with Caltech startup Beyond Limits, it didn’t have any corporate use cases and struggled to communicate what it was the company did. “Very technical founders are not always the best at communication,” says Yang, who opted for a more compelling storytelling approach. “Beyond Limits is the only AI solution born in the labs of NASA and battle-tested in deep space missions, including on the Mars Rover,” he adds. “So we opted for the story angle of bringing the most powerful AI from Mars to Earth.”
Now Beyond Limits’ technology is ubiquitous, employed in sectors such as energy, finance, autonomous vehicles, health care, and the internet of things (IoT). While the NASA background certainly gives the company technical street cred, telling the story is not always easy. Few employees possess both the aptitude and desire to be good writers, so Yang and his team prioritize spending time talking to sources and flushing out their technical expertise.
“Our biggest challenge is time,” Yang explains. “The best thought leadership comes from the scientists and the technical founders, but in a startup everyone is running in different directions.”
Stop telling tall tales
The “familiarity gap” Ahrens defined makes it difficult for companies marketing AI solutions to communicate with its potential clients. Technical and marketing jargon is apt to confuse customers and can send them running the other way.
The unique marketing cases discussed above demonstrate that success is best achieved by developing creative solutions to close the gap. Tailor conversations to customers by invoking concepts they already understand like evolution or social monitoring or space exploration. Couple this with a friendly and approachable AI that encourages natural interaction, and back all claims with clear demonstrations of relevant use cases. These strategies ensure that the true value of the technology shines above the hype.
This story originally appeared on the Topbots blog. Copyright 2017.
Mariya Yao is the CTO and head of research and design at Topbots, a strategy and research firm in applied artificial intelligence and machine learning.
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