Artificial intelligence took business and industry by storm for much of 2023. Its rapid growth dominated marketing headlines and showed no signs of falling out of favor as a multifaceted tool for productivity and automation in the workplace.
However, not all marketers fully embrace AI’s adoption as a retail tool and solution to improving the ever-changing customer experiences domain. Instead, they struggle with reactions wavering between AI panic and revenue elation.
Like it or not, most organizations find themselves unwillingly dragged into using AI. They might recognize the potential of AI to improve customer and employee experiences, yet they struggle with the challenges of integrating diverse AI technologies. Additionally, there are fears about how the new technology will impact human creativity and autonomy.
AI is not just an optional add-on for e-commerce. It is a game-changer, capable of driving significant customer engagement and revenue growth for those who dare to embrace it, according to Peter Isaacson, CMO at call tracking and analytics firm Invoca.
“In 2023, the e-commerce landscape saw teams exploring AI’s potential while still weighing and evaluating the inherent risks associated with a technology that has scaled faster than any before,” he told the E-Commerce Times.
Retailers and marketers must be concerned about negative results from the use of AI, cautioned Robb Wilson, the founder, lead designer, and chief technologist of AI-powered automated conversations platform OneReach.ai. Some of the AI solutions are deft at conversation but have severely limited problem-solving abilities.
“You have to know what you are doing and have the right tools. These types of systems are often misused or designed poorly. They essentially bar users from interacting with human agents, which can be incredibly frustrating, especially when people are trying to resolve complex issues,” he told the E-Commerce Times.
In separate interviews, both experts offered insights into how e-commerce adopters can embrace AI without fear.
Real Fears of AI Safety and Security
Fear of being left behind without AI’s benefits is a significant concern to some business leaders. A second major fear persists about how AI handles data. But that concern often loses in favor of better revenue gains AI results can generate.
As 2023 turned off its lights, Invoca released its “The State of AI in Digital Marketing” report to expose marketers’ optimism and apprehension about AI marketing technology in 2024. The study revealed a staggering 90% of marketers plan to increase their AI investment this year, making 2024 a defining year for marketing AI technology.
This rush to be at the forefront may be driving some unfounded confidence in their AI skills to justify the move: nearly all (93%) claim expert or advanced knowledge of marketing AI tech. However, respondents simultaneously indicated that a lack of AI knowledge is one of the top barriers to adoption.
Despite the mixed messages, overall, the report showed marketers ready to embrace AI. It also demonstrated fear of the high cost that comes with being late to adopt new AI technology, noted Isaacson.
AI Fear Blocks Faster Adoption
Invoca’s report found that data security was the largest adoption blocker for 2024. Isaacson noted that companies want to protect their proprietary data, and the black-box nature of many AI tools does not inspire confidence.
“They will place higher levels of scrutiny on the types of AI being used by their solutions, where their customer data goes, and how it’s used,” he offered.
2024 will be crucial in determining how this sentiment — and the reality — may shift, added Isaacson. As AI expands its presence in marketing departments, retailers are increasingly open to embracing risks that could lead to enhanced revenue.
Choose Long-Term Success, not Short-Term Cost Cutting
OneReach’s Wilson recommended marketers focus on using AI to improve e-commerce and CRM effectiveness over quick-fix profit-making. Short-term cost-cutting will not be a lasting result.
“The more important action at this moment is to establish a foundational ecosystem for AI to flourish across organizations. From a marketing perspective, this will likely include generated content, but only as one piece of the puzzle,” he advised.
Having conversational AI function as an interface layer on top of existing software and processes would have a much greater impact. Isaacson adds that even more crucial is understanding the reasons behind these actions.
For example, are you creating content for the sake of creating content, or do you have something valuable to say? A marketing team member might have an idea for a campaign tailored toward a specific demographic, such as middle-aged people who like art-house cinema.
Use Case Example
That approach could generate sample campaign copy and imagery, much like a digital assistant. The task is to estimate how many people in their customer case fit this description, explained Wilson.
He calls this use not a digital assistant but an intelligent digital worker or IDW. It uses relational databases to connect data stored in tables with nodes of information it can unearth in unstructured data, like emails and recorded calls.
The AI agent might also comb the social media content posted by customers. The marketer might even ask the IDW to generate personas within this demographic and run “user” testing with generative models.
This last marketing piece might not provide reliable information, though. But it is possible that models might be trained to provide useful feedback, he countered.
Gen AI Skills for Improved Personalization
Fear factors aside, marketers should focus on using AI to alter human perception of product purchases. To avoid unfavorable outcomes, however, cautioned Wilson, they must be vigilant about unintended consequences.
By combining generative AI tools with relational databases, organizations can mine unstructured data, such as recorded calls and emails, to create connections across departments and datasets. This integration enables them to offer levels of customer personalization previously unimaginable.
“In most cases, the goal would be to anticipate a customer’s needs, which, from a customer experience standpoint, seems like a major win,” Wilson noted.
Of course, there is also a litany of ways AI could be used deceptively at different stages of the purchase journey. So marketers need to pivot quickly when users are deceived unintentionally, he added.
Conversational AI To Enhance Consumer Engagement
Conversation intelligence AI can greatly enhance consumer engagement in e-commerce. Invoca’s Isaacson witnessed firsthand how it bolsters businesses’ revenue streams.
For example, this form of AI expertly automates and summarizes call transcripts. It also identifies spoken keywords or phrases and delivers additional context and insights.
According to Isaacson, businesses can use these skills to act on customer interactions. They can significantly enrich customer engagement for both sides.
This approach reinforces what he sees as crucial to moderating the use of generative AI, such as ChatGPT. While AI has numerous advantages, it is essential to implement a thoughtful strategy to ensure that it contributes positively to customer engagement rather than detracting from it or putting the business at risk.
“Unchecked, this can lead to a compromised customer engagement experience, which is a risk no business should take,” he said.
AI Can Link CX Online and Offline
Isaacson anticipates a shift where teams fully embrace AI to amplify their e-commerce and CRM effectiveness by linking the online and offline customer journey. The result will enable automating manual processes and seamlessly integrating first-party data into systems they already use today.
“AI holds the potential to revolutionize e-commerce by surfacing valuable insights from customer conversations that would otherwise fall into a black hole,” he predicted for 2024.
Isaacson also warned that AI apprehension could lead to missed opportunities, with competitors gaining an edge.
“With AI, businesses can provide a personalized experience that effectively merges the best of both digital and the human touch,” he said.
Impact Human Decision-Making Processes and Autonomy
According to Wilson, conversational AI can simplify customer interactions, reducing the friction most brands try to avoid. In call center scenarios, properly implemented automation can provide product information and update order status.
It is also possible to schedule appointments in ways that are intuitive to the way humans manage their time, he noted. For high-level problem-solving, human-in-the-loop allows bots to transfer calls to human agents.
“Conversational AI can equip agents with a summary of the call so far, prompting them with possible responses and follow-up information as necessary,” Wilson suggested.
This give-and-take approach to AI-powered marketing and CRM operations changes human decision-making processes and autonomy. To do this, AI should serve as a curator.
“As a teammate, an intelligent digital worker can summarize massive amounts of information and present humans with the best viable options,” Wilson insisted.
In an organizational setting, the IDW is connected to the company’s software solutions. The scope of the IDW is extensive, encompassing various knowledge forms, ranging from traditional databases to unstructured data such as emails and recorded conversations.
“This ecosystem approach lets AI work as a reliable ally to the humans making key decisions at every level of operations,” concluded Wilson.