From audience targeting, to content strategy, to SEO, media buying, email writing, and predicting conversions and churn, hundreds of activities marketers perform every day will be intelligently automated to some degree in the near future.
Billions of dollars are pouring into marketing technology companies intent on driving efficiencies in traditionally time-intensive, data-driven tasks across every marketing discipline.
While in most instances AI will augment, not replace, marketers, it will, nonetheless, have a disruptive effect on the industry. Career paths will be altered, and roles and responsibilities will evolve as businesses seek ways to drive costs down and performance up through AI-powered solutions.
The more you know, and the more proactive you are preparing for the change, the better positioned you’ll be to use AI to your advantage.
Using our AI Score for Marketers assessment tool, we’ve asked hundreds of professionals to rate the value of intelligently automating more than 60 common AI use cases within the 5Ps of AI framework:
Planning: Build intelligent strategies.
Production: Create intelligent content.
Personalization: Power intelligent consumer experiences.
Promotion: Manage intelligent cross-channel and cross-device promotions.
Performance: Turn data into intelligence.
All use cases are scored on a 1 - 5 scale based on the same question: “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?” Respondents are guided to consider the potential time and money saved, and the increased probability of achieving business goals.
An analysis of the average rating of 210 respondents, gave us the top 25 Marketing AI Use Cases below. As you'll see, the highest rated use cases were scored between 3 and 4, indicating they are of moderate-to-high value for marketers.
Analyze existing online content for gaps and opportunities. (3.88)
Choose keywords and topic clusters for content optimization. (3.72)
Construct buyer personas based on needs, goals, intent and behavior. (3.71)
Create data-driven content. (3.70)
Discover insights into top-performing content and campaigns. (3.64)
Measure return on investment (ROI) by channel, campaign and overall. (3.64)
Adapt audience targeting based on behavior and lookalike analysis. (3.64)
Optimize website content for search engines. (3.55)
Recommend highly targeted content to users in real-time. (3.52)
Assess and evolve creative (e.g. landing pages, email, CTAs) with A/B testing. (3.47)
Deliver individualized content experiences across channels. (3.44)
Define topics and titles for content marketing editorial calendars. (3.43)
Predict content performance before deployment. (3.41)
Forecast campaign results based on predictive analysis. (3.40)
Build media and influencer databases based on interests, audiences and intent. (3.37)
Prescribe strategies and tactics to achieve goals. (3.30)
Present individualized experiences on the web and/or in-app. (3.27)
Design websites, landing pages and calls-to-action. (3.26)
Map buyer journey stages based on historical lead and conversion data. (3.26)
Draft social media updates with copy, hashtags, links and images. (3.24)
Analyze and edit content for grammar, sentiment, tone and style. (3.24)
Determine goals based on historical data and forecasted performance. (3.23)
Score leads based on conversion probabilities. (3.23)
Curate content from multiple sources. (3.23)
Build dynamic charts and graphs to visualize performance data. (3.22)
Interested where we as an industry are with our understanding of AI?
Check out AI Score for Marketers to explore and rate dozens of AI use cases, and get personalized recommendations for AI-powered vendors.
And here’s a bit more detail on the 210 respondents in this preliminary report:
The average overall AI Score is 60.5%. This combines all use case ratings across the five sections of Planning (63.3%), Production (59.7%), Personalization (59.5%), Promotion (58.7%) and Performance (59.8%).
When asked, “How would you classify your understanding of artificial intelligence terminology and capabilities?,” Beginner (48.3%) was the most popular response, followed by Intermediate (40.2%) and Advanced (11.5)%.
When asked, “In which areas are you involved?,” Content Marketing (76.6%) was the top category, followed by Email Marketing (63.0%), Social Media Marketing (60.4%), Analytics (59.9%), Advertising (57.8%) and Search Engine Optimization (50.5%). Respondents may choose multiple choices from 14 marketing categories.
The majority are decision makers, with 75.8% identified as Manager (30%), VP/Director (19.5%) or C-Level/SVP (26.3%).
The size of the companies vary, with 64.1% being small businesses of $10M in revenue or less, and 35.9% being greater than $10M.
43.4% are B2B, 23.7% are B2C and 32.8% are both B2B and B2C.
58.7% have started researching and testing artificial intelligence technologies, while 41.3% have not.
If you’re looking to expand your understanding of AI, and pilot use cases within your organization, we invite you and your team to join us for the Marketing Artificial Intelligence Conference, July 16 - 18, 2019 at the Huntington Convention Center in Cleveland, Ohio.
MAICON brings together top authors, entrepreneurs, AI researchers, and executives to share case studies, strategies, and technologies that make AI approachable and actionable for marketers.
The event is designed for director-level and above marketers, and largely caters to non-technical audiences, meaning attendees do not need backgrounds in analytics, data science, or programming to understand and apply what they learn.
Visit www.MAICON.ai to learn more. Register by April 1, 2019 to save $600 off the full event price!
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