How AI allows intelligent marketers to market more intelligently

How AI allows intelligent marketers to market more intelligently Jennifer Steckel Elliot is vice president of sales and marketing for Flybits, a context-as-a-service company with offices in Toronto and Palo Alto, California. She has more than 20 years of experience in marketing strategy and communications. specializing in retail, technology, and sport. Jennifer honed her craft working with global brands such as IBM, Gap, Ogilvy & Mather, Golf Town, and Ryerson Futures. She holds an MBA from the Rotman School of Management at the University of Toronto.


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By now, it’s a familiar narrative: The advent of artificial intelligence, along with contextual computing, will transform entire industries and leave nearly everyone — including marketers — jobless

Well, maybe not.

The fact is that AI and CC simply provide new ways of doing what marketers have always done: Track, measure, assess, and learn from customer behavior to help companies tailor product offerings, prices, positioning, and messaging based on those insights.

AI helps machines learn from this data, delivering actionable insights to allow marketers to develop new ideas. A major benefit of AI is that once the context and actions of humans are understood, machine learning will derive new ways of improving knowledge discovery.

Meanwhile, CC helps machines collect data from several sources, including personal (which the user has agreed to share from his or her device), proprietary (brand’s business intelligence), and public (such as the weather). Marketers can use these sources of context to drive adoption and sales information such as location, gender, buying history, step count, and more. 

Through its partnership with IBM’s Watson, Under Armour uses a customer’s personal fitness information (e.g., age, location, health goals, etc.) to aggregate third-party data through its Record app. The consumer experience is personalised training and life cycle advice that helps customers attain their nutritional and fitness objectives. 

When used together, as the above example displays, AI and CC can transform a marketing strategy. The union allows marketers to more efficiently employ personalised, customer-centric tactics, making direct marketing easier to manage, react to, and monetise. The data itself is something of a gateway for marketers, giving them newer, more unique platforms from which to engage consumers and specifically tailor an experience for them. 

Question everything

The key to customer research and data analysis, whether you’re doing it manually or relying on technology, lies in asking the right questions. Using AI and CC can speed up the process of learning about your customers and help optimise your efforts.

But the onus will always be on the marketer to formulate the queries that lead to new insights. As more and more data is made available, expanding the horizons for how it will be used is an out-of-the-box way to open the doors to more conversion opportunities.

That’s my company’s motivation behind its work on the TD For Me modification on the TD Bank app. The upgrade creates and promotes content for users based on context such as location and personal interests. As a mobile “concierge” service, we’re able to help the bank send users real-time advice, information on nearby deals, and any other financial data or content participating users might find useful.

This ability to deliver personalised messages at the right place and time can transform a business. In fact, McKinsey and Company’s “Big Data, Analytics, and the Future of Marketing & Sales” e-book notes that personalized advertising results in eight times the ROI of non-personalized advertising and can lift sales by at least 10 percent. 

Moreover, marketers can gauge marketing ROI spend across each stage of the customer journey and gain insights into which channels customers use throughout that journey. The bottom line: Better data leads to better advertising and ultimately better results, which yields data-driven marketing. 

Data-driven marketing is a new phrase, but it’s a tactic 7-Eleven utilised more than 30 years ago. The chain took a lot of data, a lot of people, and a lot of time to uncover a remarkable insight — men who shopped for diapers on Friday evenings at 7-Eleven also picked up some beer. To capitalise, 7-Elevens moved their beer aisles closer to the diapers and, unsurprisingly, enjoyed a 35% increase in sales of both items. 

Of course, there’s a catch-22 associated with improved marketing capabilities. It conditions customers to expect immediate, personalized service regardless of which channel they use to engage a brand. Plus, marketers must constantly find new, creative ways to reach customers amidst a barrage of targeted messages and cluttered communication environments.

69% of Canadians start an activity on one digital device and finish it on another. Making a sale today often means marketers must win engagement on a digital — likely mobile — forum early in the customer journey. 

The changing role of marketers 

Better technology enables marketers to work closely with channel partners to build campaigns together based on location, product preferences, partnerships, or pricing. The result could be insights, engagements, and sales that benefit both marketers and partners.

Larger organizations can better position marketers to decide which partnerships make sense based on everything they know about the customer. Likewise, data will allow marketers to function more as product champions, enabling them to provide insights to product teams and to influence product development based on customer behavioural trends. 

Personalised service used to be for luxury brands. Now it’s available to any company willing to utilise it. Enhanced service, content, and experiences translate to higher retention, engagement, and evangelism among customers. This leads to more sales, higher margins upfront, lower customer churn, and reduced customer acquisition costs. 

For example, if you want to drive sales of a commodity or product, conceptualise each stage of a customer’s path to purchasing that product and ask what barriers to purchase exist at each stage. Then build a campaign that addresses those barriers and helps customers get past them (and closer to making a purchase).

There are thousands of companies sitting on a near-endless supply of customer data. Those that prevail will be the ones that clean up, sort through, ask the right questions, and leverage that data to develop sound strategies and realise business objectives. 

As a marketer, it’s your job to ask the right questions and evolve with the technology. Contextual computing, AI, and machine learning will give you more time to do the strategic and implementation part of your job better, while also creating a quicker, more customer-friendly process.

Machines aren’t a perfect substitute for traditional marketing, but their ability to streamline processes and information will continue to make them viable co-pilots as marketing soars toward the future.

Author

  • Jennifer Steckel Elliott

    Jennifer Steckel Elliot is vice president of sales and marketing for Flybits, a context-as-a-service company with offices in Toronto and Palo Alto, California. She has more than 20 years of experience in marketing strategy and communications. specializing in retail, technology, and sport. Jennifer honed her craft working with global brands such as IBM, Gap, Ogilvy & Mather, Golf Town, and Ryerson Futures. She holds an MBA from the Rotman School of Management at the University of Toronto.

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