In the first post in our series “Artificial Intelligence for Technology Marketers,” we introduced the concept of artificial intelligence. This second post delves into AI’s specific marketing use cases, particularly as they relate to data.
One of the great benefits to marketers from Internet, mobile, and IoT is the massive amounts of customer and prospect data generated from online activity, such as intent, behavior, search terms, and much more. But this data can also be completely overwhelming to analyze for actionable insights. In fact, according to the 2017 State of Marketing survey of 3,500 marketers by Salesforce Research, “Marketers at all performance levels struggle to leverage data from different sources in their quest to execute a connected customer experience.”1 But that’s exactly where artificial intelligence can be most useful.
“Artificial intelligence uses machine learning to identify areas for improvements in existing processes and adapt current workflows without the need for human intervention. For you as a marketer, technology that employs machine learning can mean the automation of repetitive tasks, faster and more accurate calculations and data analysis, and an investment that will ultimately pay for itself.”2 With the automation of repetitive data-driven tasks, some major AI-driven use cases immediately come to light:
- Analytics – Analyze past user behavior to predict future behavior, analyze current campaign results, and crunch data to forecast results. This alleviates an enormous amount of time from marketer’s already-full plates tracking down data, normalizing data sets, and figuring out what all the numbers mean.
- Personalization – Leverage the data to build accurate, relevant customer segments that are most meaningful to the business and customize content and experiences on the fly to engage and retain customers.
- Content Creation – Based on structured data inputs, AI can now write articles, such as sports results, weather, and financial summaries. In this way, AI can now take data from marketing campaigns and build performance reports, relieving marketers of hours of tedious work.
- Lead Engagement – Think chatbots, e-mail marketing, and text messaging to help marketers guide prospects through the funnel. By intelligently automating lead engagement, sales reps can re-focus their time on large deals or those most likely to close.
These are just a few of the marketing uses cases for AI, and there are already many companies offering ready-to-go solutions. In fact, the number of active U.S. start-ups developing AI systems has increased 1400% since 2000, according to the AI Index. You may already be using AI without even knowing it’s built into your marketing stack!
Next up in this series will be a post on how to leverage AI in B2B technology marketing.
About the author
Kim Ann King is the author of “The Complete Guide to B2B Marketing: New Tools, Tactics, and Techniques to Succeed in the Digital Economy.” She has helped launch and build several pioneering Internet companies and writes frequently about artificial intelligence, marketing technology, e-commerce, and cybersecurity.
- Fourth Annual State of Marketing report, Salesforce Research, April 2017. http://www.salesforce.com/assets/pdf/datasheets/salesforce-research-fourth-annual-state-of-marketing.pdf
- Nicole Williams, “A Marketer’s Guide to AI and 45 AI Marketing Tools to Get Started With,” Capterra, August 17, 2017. https://blog.capterra.com/a-marketers-guide-to-ai-and-45-ai-marketing-tools-to-get-started-with/
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