Marketing has become a data-driven discipline in recent years — so much so that some feel the human element has gotten lost in all the metrics. When you’re obsessed with increasing clickthroughs and conversions and proving marketing’s contribution to the pipeline, it’s easy to lose sight of the fact that your campaigns and ads are targeting people, not leads.
Ironically, it’s the data — and its analysis — that’s helping marketing teams humanize marketing again. AI and machine learning are enabling marketers to send highly personalized, targeted messages and content to people — increasing the effectiveness of campaigns through personalization and improving the customer experience in the process.
Getting Serious about Personalization
Over the past decade, we’ve become experts at list segmentation and mapping the buyer’s journey. We develop personas that help us understand specific messaging points for various audiences and sub-audiences, and we can version content deliverables to speak to the challenges and needs of very specific groups of people. But much of this effort has been hit or miss and very manual. We send out a campaign, collect the data and try to make sense of it ourselves. A/B testing helps quantify our best guesses, but it’s still a very subjective process.
AI removes the subjectivity. Using various machine learning algorithms and models, marketers can analyze millions of consumer data points to determine the best times to contact them, how often to contact them, and what content is most relevant. This can be accomplished on an individual basis, enabling marketers to connect one-to-one with each lead and engage with them in a very personalized way.
Here are five ways AI is helping marketing teams create more personal experiences for customers and prospects:
1. Precision Email Marketing
Email campaigns are the low-hanging fruit for AI, which can be used to drastically reduce the time needed to create, deploy, test and optimize email marketing efforts. Campaign effectiveness analytics help marketers analyze millions of data points about a lead or prospect to determine the optimal time and method to engage with them, as well as what’s likely to be them most impactful message based on the recipient’s needs and stage in the buyer’s journey. They can “learn” a consumer’s preferences and make predictions about buying decisions based on data around past behaviors and interests. When a lead takes action, that new information is added to the model, helping to optimize results further.
Content optimization algorithms can inform marketers what subject lines work best, optimal email length for different audiences, or what CTAs resonate with specific groups or audience segments. This information can be used to personalize email communications, building trust and helping marketers get closer to delivering the exact information recipients need.
Over time, AI models can make extremely accurate predictions about what next step a consumer will take after reading an email, when they will buy, what they will buy and what message or content will push them over the tipping point to a purchasing decision.
2. Personalized Website Experiences
In the past, website messaging and content had to be general, so it could appeal to a broad range of people. Marketers often use microsites with distinct URLs to curate content and deliver messages targeted toward specific audiences. Today, AI takes that further, with the ability to identify incoming traffic and dynamically serve up a personalized website experience based on attributes associated with the visitor. It enables retailers and other sales-driven businesses to deliver targeted recommendations on their websites as the visitor browses — as in the case of Amazon, Netflix, Spotify and others — and deliver the right content and offers to someone who’s ready to take action.
3. Ad Campaign Optimization
Applied to performance data from advertising campaigns, AI can be used to reveal patterns that simplify — and accelerate — ad campaign optimization. This is critical for paid advertising, which can be very expensive. Marketers can use AI to automatically update or change content depending on its effectiveness, and maximize ad spend by using insights from data across multiple channels to make decisions about what media to buy.
4. Dynamic Digital Signage
Digital signs have replaced billboards as a primary means of Out of Home (OOH) advertising — and AI is making them even more engaging and effective. Sound sensors and cameras can be placed on signage to collect real-time data and feed it through AI algorithms, enabling dynamic targeting with messages tailored to passers-by. They can identify demographic characteristics of groups of people, prompting signage to display more relevant messaging, or detect changes in the weather that triggers the delivery of ads for items like sunscreen or umbrellas. Marketers benefit from more conversions and additional data that can be used to further refine campaigns and spend.
5. One-to-one Omnichannel Experiences
Say you’ve recently performed a search on Google for cowboy boots, and Maps directs you to a western wear store nearby. On your way there, you receive an email with a QR code for a free pair of socks with boots purchase. You walk into the store and your phone alerts you to a text — it’s a discount on Laredos. You choose your pair and some socks and walk to the register. As you pass by a row of cowboy hats, digital signage beckons you by name to try one on. Your phone buzzes again, and you see you’ve received another coupon — 20% off hats — and you can’t resist. At the register, you don’t even have to enter those discount codes, because they’ve been added to your profile. You complete your purchase, and walk out happy, satisfied with your shopping experience.
That’s the potential of AI to transform customer experience and enable marketers to personalize it from start to finish.
Getting Started with AI
Research shows that top-performing companies are more than twice as likely as their peers to be using AI for marketing. Although 83% of businesses say AI is a strategic priority, 63% of B2B marketers are not using AI in their tech stack and only 13% are very confident with their knowledge of AI.
Artificial intelligence is becoming much more prevalent as a component of marketing and there is a wide variety of marketing technology solutions out there aimed at helping marketers incorporate AI into their business strategies. Are you leveraging AI for marketing?