2023 was undoubtedly the year of generative AI, thanks largely to the widespread adoption of platforms like ChatGPT and the excitement that followed. In a survey published in August, McKinsey & Company shared that one-third of respondents were using generative AI regularly in at least one business function within their organization, and 40% confirmed they would increase their overall investment due to advances in this technology.
Considering that most generative AI tools debuted less than a year ago, and many businesses have to navigate layers of corporate red tape to adopt new technologies, these statistics are remarkable. Such a sharp lift in interest and adoption has led to three major shifts in marketing automation:
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Sense of Urgency
Marketers do not like to be left behind. The buzz around AI has created an urgent need to build strategies around AI adoption. Marketing automation presents itself as the natural place to start.
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SaaS Investments
Any doubt surrounding AI becoming a part of our daily lives was essentially eradicated when the world at large tried out generative AI tools. This shift meant that SaaS companies no longer had to argue for investing time, money, and resources into AI—it transformed from a nice-to-have to a must-have almost overnight.
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Emerging Use Cases
AI is akin to its own growth loop. With increased use comes increased intelligence, both on the AI’s part and in marketers' understanding of AI. This leads to the discovery of new use cases, and over time, AI and automation become increasingly prevalent in marketers' day-to-day lives.
The shifts observed in 2023 have set the stage for 2024, when AI will truly start to feel like a colleague—one that marketers can successfully work with to achieve things they never dreamed possible.
Why AI-Powered Chatbots are a Game-Changer
Not so long ago, marketers debated the merits of live chat versus chatbots. Live chat was generally preferred by businesses that wanted to guarantee accurate information but required a large, global support team for 24/7 service. Chatbots, on the other hand, could answer simple questions around the clock but lacked the human touch needed to build relationships with leads and customers.
Today, a new option has presented itself: AI-powered live chat. It's essentially the best of both worlds—AI can help human support agents find the necessary information, answer simple questions accurately, or escalate conversations to the right people with full context.
This welcomed evolution has led to several major improvements and new use cases in chatbots.
Using NLP for Conversational AI
Counterintuitive as it may seem, the increased adoption of AI in marketing could make a company’s interactions with customers more human.
Advanced natural language processing (NLP) models use neural networks to train themselves on information and the conversations they have with people. Sophisticated chatbots can discern meaning from language to respond more naturally. Over time, they learn more about human speech patterns, colloquialisms, and tone to humanize their voice.
Although true emotional intelligence is still a ways off, these chatbots can detect sentiments in conversation and react accordingly, providing a more personalized and empathetic customer experience.
AI Sentiment Analysis and Customer Insights
In addition to making conversations feel more human, sentiment analysis can fuel greater reporting and insights.
Understanding how customers feel about their interactions with a brand—and how that sentiment changes when interacting with a human versus a bot—can help improve customer relationships.
AI’s ability to process vast amounts of data is one of its greatest strengths, and live chat generates heaps of individual data points around sentiment analysis. This data can be used to assess sentiment, drill down to identify why customers feel a certain way, and develop a data-driven strategy around customer happiness—acting on it with the help of AI.
The Rise of AI-Powered Voice Assistants
Live chat became an important marketing channel partly because consumers using messaging services like Slack, WhatsApp, and Messenger grew comfortable with this style of communication. They wanted the same convenience when interacting with businesses. Voice assistants are heading in the same direction.
Currently, voice search is the area with the most growth, especially for local businesses aiming to be the answer when a potential customer asks for the nearest gas station or grocery store.
In 2024, businesses could start to build custom voice assistants, enabling users to find help while they work and have the voice assistant walk them through instructions step by step. Anyone who has asked their smart speaker to share a recipe knows just how useful this is when focusing on a task.
Like chatbots before them, voice assistants will learn to sound more human as they interact with real people. They'll learn to pause, emphasize, and adjust their tone—using different accents and phrases—to provide a more natural user experience.
AI-Powered Chatbots in Companies
Support teams using AI-powered live chat and businesses with internal messaging bots are already accessing company information from chatbots. In 2024, as more companies adopt and use AI-powered live chat tools for marketing, sales, and customer support, businesses will find ways to use them for internal education purposes.
Imagine an onboarding experience led by a chatbot. A new user starts and interacts with a bot that guides them through the onboarding process, elevating questions to the right team members as required. This approach streamlines onboarding and ensures new employees have immediate access to the information they need.
Part of this will be opportunity spotting for businesses—refining repetitive tasks—and part will be the desire to maximize the value of their tools. As a bonus, a chatbot trained to internally answer questions about products, services, and the brand will be better suited to answer questions from leads and customers.
An Adopt-or-Fail Mentality
In 2024, customers will expect all businesses to offer some kind of chat experience. Those seeking assistance are already looking for a chat bubble on websites or apps. By the time we're ringing in 2025, they'll be frustrated if it's not there.
Adopting AI-powered live chat now doesn't just mean meeting future customer expectations; it means your AI model will have learned more about your brand, products, and services. This familiarity enables it to communicate with customers more accurately and with a human touch.
The Promise of AI Predictive Analytics is Finally Delivered
Perhaps the most transformative application of AI in marketing automation is predictive analytics.
When data can be used to predict future outcomes, AI-powered marketing automation platforms can make data-driven decisions autonomously. It's a dream for marketers who want to set up reliable, set-and-forget automated journeys.
Applications of predictive analytics are already part of daily life, from weather forecasts to behavioral targeting in advertising. However, these predictions are still imperfect, especially when looking far into the future.
Given rapid technological advancements, we're nearing a world where predictive analytics could forecast inventory requirements, revenue, and staffing needs with precision—accessible to businesses of all sizes.
The potential is immense. Here are a few use cases that could emerge in 2024.
Forecasting Performance
Email subject line performance is one area where AI excels. Accurate predictions on open rates, along with suggestions for higher-performing alternatives, are already available.
In time, marketers could use automation platforms to predict metrics with higher stakes. Imagine predicting the ROI of a campaign before it goes live. This could become a reality as predictive analytics analyze similar campaigns, audiences, and objectives to accurately forecast performance.
Lead Scoring
Lead scoring has improved thanks to sophisticated models and algorithms but often relies on human input to determine the attributes or behaviors that define lead quality.
Advancements in predictive analytics could enable marketing automation platforms to assess lead quality based on available data points without manual modeling. AI could automate the entire lead scoring process.
For instance, AI might identify top-performing customers to establish attributes or behaviors indicating a lead's potential value. With this information, AI could automatically qualify leads and route them to the appropriate sales representative.
Retention and Churn Prevention
Retention and churn prevention are hot topics in marketing. Customer acquisition costs are rising, increasing the need to maintain a loyal, high-value customer base.
Currently, marketers identify behaviors that may indicate churn—like viewing cancellation terms—and set up automation journeys to alert support teams for intervention.
In the future, predictive analytics could eliminate the manual identification step. AI could analyze data, spot at-risk customers, and automatically initiate personalized retention journeys or escalate them to a team member for human intervention.
Pricing Management
Dynamic pricing models, like surge pricing in ride-sharing apps, demonstrate AI's potential in pricing strategies. Increased demand leads to higher prices—a straightforward concept.
AI-enabled pricing management tools can predict optimal pricing based on inventory levels, competitor pricing, and customer responses to price changes.
In complex pricing scenarios, such as SaaS and B2B subscription tiers, predictive price optimization could become invaluable. By considering customer behaviors, market trends, competitor pricing models, and global financial conditions, AI can forecast the success of pricing strategies.
Personalization Using AI in Marketing Automation
Marketing automation has enabled marketers to scale personalization. Without it, sending millions of individually crafted emails daily would be impossible.
With AI, personalization at scale reaches new heights. Omnichannel messages can feel truly one-to-one, with every element—from tone to content, recommendations to calls-to-action—tailored based on individual attributes and behaviors.
As exciting as this is, marketers must address privacy concerns. 2024 may be a year of reckoning regarding data collection and usage. The impending removal of third-party cookies from browsers underscores the need for transparency.
A renewed focus on first-party and zero-party data collection could empower AI-powered marketing automation platforms to create genuinely personalized experiences while respecting user privacy.
AI-Generated Personal Emails and SMS
AI already crafts emails, subject lines, SMS, and push notifications in brand voices, incorporating personalized elements like merge tags.
Looking ahead, marketing automation platforms underpinned by AI could write emails and SMS messages for specific audience segments or individuals.
AI would analyze data to determine the subject lines, tone, format, and calls-to-action most likely to resonate, then compose the message accordingly.
This evolution means personalization will transcend basic merge tags, focusing instead on nuanced tone adjustments and message composition tailored to each recipient.
Enhanced AI Recommendation Engines
Recommendation engines leverage AI to suggest products or content based on user behavior. In marketing automation tools, these engines help re-engage lapsed customers or upsell active ones.
With AI's growing capabilities, recommendations could become even more individualized. AI could learn each user's interests and disinterests, refining future suggestions for greater relevance—a prime example of advanced predictive analytics in action.
AI-Powered Automation for Personalized Next Steps
Marketing automation simplifies customer lifecycle marketing. Marketers can create omnichannel campaigns guiding leads and customers through their journey.
Success hinges on identifying the next best action at each stage, traditionally using data analysis.
Predictive analytics could enable marketing automation platforms to forecast future steps without human input, delivering personalized guidance to each customer. Technology might also optimize message timing based on previous user behavior.
In essence, AI could eliminate guesswork and manual intervention throughout the customer journey.
Embracing AI: The Time is Now
The sooner marketing teams adopt automation and AI, the more both the AI and the team will learn.
With accumulated experience and knowledge, AI will deliver better outcomes, and marketers will discover innovative use cases to distinguish themselves from competitors.
In a rapidly evolving landscape, being an early adopter has never been more crucial. The integration of AI into marketing automation is not just a trend—it's the future of how businesses will engage with their customers, optimize operations, and drive growth in the years to come.