Elevate the Customer Experience with AI: 5 Game-Changing Insights for Marketers

The idea that machines will one day overshadow marketers can be daunting. Surprisingly, 64% of marketers feel that decisions guided by instinct and past experiences outshine those made by AI.

However, instead of seeing AI a threat, marketers should embrace it as a game-changing ally. By leveraging AI’s capabilities, marketers can allocate more time to strategic, innovative, and creative work. The goal: to harness data-driven insights to marketer sharper, quicker decisions that resonate with customers and unlock true value.

To see the impact first-hand, here are the five aspects marketers should consider.

1. Who should we talk to?

At its core, AI serves as a tool to pinpoint and engage the right customers with the right piece of content and at the right time – once you identify who those targets are.

Historically, email campaigns have garnered response rates hovering around the 1% to 2% mark. The modest figure stems from a traditional approach where customers are bucketed into broad categories defined by basic demographics and geographical data (segmentation). This approach, however, often overlooks pivotal factors like recent purchasing behavior and brand loyalty, which can drastically influence a customer’s responsiveness.

The real magic lies in zeroing in on the who and what in your communication strategy—a topic we’ll dive into deeper shortly. To understand and identify your target audience, consider these three pivotal insights before rolling out AI as part of your strategy:

1. Consider the Product Facet. Think of this as a comprehensive lens that encapsulates engagement metrics, transaction histories, and profiles the AI model can access. It sketches an optimal picture of each customer and can serve as the foundation for purposeful discovery throughout the product catalog.
2. Find the Promotional Affinity of each customer. Consider this a promotional motivation scale, identifying which customers are more or less motivated by offers and determining how heavy they need to rely on them to drive a conversion.
3. Review the Customer Quality, which looks at the factors contributing to long-term value, understanding where customers are at in their lifecycle with the brand, ensuring that they’re balancing short vs. long-term value, engagement vs. selling, or nurturing to higher AOV vs. a one-off sale.

Once the marketer has a better grasp of who the customer is, they are more primed to leverage AI for the best results.

2. What should we talk to them about?

Knowing who you’re looking to connect with is the first step that informs all other decisions: the creative, frequency, and models that govern when and what content is presented. AI has the power to do all three for each customer – individually.

The marketer’s role is pivotal. They define the rules of engagement, distilling the vast categories the AI can pick from. By refining the target list, marketers can exclude irrelevant factors, like certain products or locations, empowering the AI to optimize the results.

For example, marketers can use product attributes to determine a customer’s preferences. They can evaluate promotional inclinations and assess customer value to pinpoint specific goals for each individual. Based on these insights, the model will select the best-suited content to match the objectives.

Imagine a scenario where a marketer provides an AI with 50 creative assets. Over time, the AI system observes how different content elements interact, understands how their placement in the email has an impact, and gauges their impact on overall performance. Harnessing this knowledge, AI can then craft hundreds of thousands of brand-consistent emails in a single day – a feat that’s impossible to do manually.

3. When should we send it?

In traditional marketing campaigns, marketers often stick to a fixed calendar, assigning a set number of emails to specific merchants or business units, with little to no room for flexibility, even for last-minute changes. For example, a retail marketer might arbitrarily dedicate 10 emails to men’s shoes at 6:00 a.m. and five emails for women’s handbags at 7:00 a.m.—without logic or real strategy. Such an inflexible approach not only consumes valuable resources but also often falls short in delivering an optimal customer experience.

Alternatively, instead of using one or two arbitrary distribution times on a given day, AI can determine the best time of day for everyone based on their likelihood to convert through “send time optimization.”

All the marketing team needs to do is set the beginning and end time, and the AI will do the rest. In the case of a retail marketer, if a store completes its inventory count by 4:30 p.m., the email blast can deploy once the stock numbers are updated. To stay ahead of the competition, if a rival brand typically sends their promotional emails at 5:00 p.m., the marketing team can strategically send theirs beforehand.

The outcome?  Enhanced performance. Leveraging AI, marketers have seen a 4% lift in click rates and 5.5% in conversions just from frequency alone, not including the double digit lifts they see when combining with content personalization.

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4. How frequently should we engage?

Frequency is a vital component to ensuring a campaign’s success.  Overcommunication is the top reason consumers unsubscribe from brand communications.

Marketers have two important frequency considerations when using AI for campaigns:

• Creative Frequency Rules: By limiting the total interactions within a set period, marketers can manage costs and mitigate risks. This ensures the AI doesn’t over-communicate, inadvertently overwhelming the recipient and depleting budgets.
• Creative Reuse Rules: It’s essential to regulate how often a particular message is shown based on a customer’s actions. This not only prevents redundancy but keeps the content relevant to the customer’s current position in their buying journey. For example, a majority of customers won’t see the email (10-20% open rates), therefore the model has a way of automatically resending the content in X days with a new subject line to try once again to get content in front of them.

Once the marketer puts these rules in place, AI can experiment with varying frequencies, evaluating how customer engagement changes along with changes in frequency volume to ultimately pinpoint the perfect engagement moment for each individual customer.

5. How can we optimize going forward?

While getting the correct message out is important, what really matters for brands is continuously improving their campaigns over time. That starts with recognizing that not all AI is created equal. There are two main approaches for applying AI that marketers can employ.

The first approach is Predictive Analytics, which depends on static models that require manual updates by data scientists. A limitation to this approach is in its ability to self-update in real time based on customer responses. Manual human intervention restricts true scalability.

Conversely, Machine Learning models continuously evolve. They learn and adapt with every response and then automatically update based on what’s effective and what’s not.

Even though these models self-optimize, their effectiveness is contingent on the variety and quality of email content that marketers provide. This is where the human touch—the marketer’s strategic and creative thinking—becomes invaluable. While the AI is doing the grunt work of sending emails, marketers will pivot to higher-level, more strategic initiatives, like coming up with new and innovative “creative input options” in addition to focusing on other strategic initiatives such as enhancing their cross channel strategy.

Auditing a brand’s creative library can also deliver crucial insights. By assessing the distribution across various categories, marketers can make informed decisions, balancing supply against demand. Take retail again for example: if a deep dive reveals that emails related to men’s clothing are being sent out disproportionately compared to their representation in the creative library, it signals higher demand. This insight triggers the marketers to reallocate creative resources appropriately. Beyond the benefits to the marketing strategy, these insights can help guide the creative and merchant teams in their planning, and aid in cross functional buy-in from key stakeholders given internal change management is a persistent issue.

Marketer and the Machine

As the age of AI-powered personalization takes off, the technology helps solve marketers’ most pressing issues and sets them up for long-term success. Marketers can streamline campaign workflows, skyrocket effectiveness, and autonomously deliver AI powered personalization that not only captivate customers but also underscore the brand’s value in a competitive landscape.

 

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