Generative AI isn’t just a fun trend, it’s a powerful and proven marketing tool that can help companies increase revenue even during times of economic uncertainty. Recently, Persado Co-Founder and COO Assaf Baciu joined Deborah Weinswig, CEO and Founder of Coresight Research, to discuss retail challenges, the problem of digital noise, and how AI-generated personalized marketing can help businesses win the holiday season (and any season for that matter).
Here are the biggest takeaways from their conversation:
Retailers face macro and secular headwinds in 2023
2022 was a challenging year for businesses as they faced inflation and persistent supply chain issues, among other external factors. As we look to 2023, companies can expect more headwinds in the form of:
- Rising customer acquisition costs: A spike in the cost and decrease in effectiveness of social advertising are driving higher acquisition costs.
- Uncertain macro environment: High inflationary pressure will remain while the U.S. savings rate of 2.3 percent is the lowest since 2005—both could hamper consumer spending.
- Impending death of third-party cookies: Tighter privacy restrictions on consumer data will make it harder for retailers to provide customers with a tailored experience.
Retailers should prepare for a more volatile retail environment and a more cost-conscious customer heading into 2023. As the cost of incremental revenue rises, retailers must act to maintain growth in top and bottom line numbers.
Based on the retailers he’s working with at Persado, Assaf says he has noticed consumers re-evaluating their priorities. For example, items in online shopping carts sit there longer. E-commerce stores are also seeing slightly decreased average order values. And they’re experiencing fewer conversions (completed sales) than expected, which is likely to persist into 2023.
Personalized language can help retailers stand out amid the noise
During the pandemic, companies accelerated their efforts in using digital channels to reach customers. This, combined with the rise in popularity of e-commerce and of language generation technology, has created more “digital noise.”
To cut through the static, brands need to leverage AI-generated personalized marketing language—that is, messaging that is relevant and delivered in a way the customer prefers. Take Amazon, for example. The tech giant is a pioneer in relevancy, using past customer behaviors and order history on the website to make personalized recommendations. However, a relevant product recommendation is just the first step. To make sure recommendations truly land and lead to conversions, brands must also speak to customers as if they know them personally.
AI-generated marketing can help retailers drive better personalization and business impact
Personalization is a well known tactic for driving business impact. Global marketers cite personalization as having a direct and growing effect on driving customer engagement and revenue. Still, they fail to consistently deliver personalized experiences. Why? According to Assaf, many businesses actually invest in modeling or data.
“Consumers don’t experience data,” he says. “they experience content.”
Also, brands have a habit of mixing relevant, personalized content with irrelevant, non-personalized content. Doing so muddies the overall messaging with the customer, leading to subpar returns on the investment in personalization.
Assaf’s advice? Retailers should leverage artificial intelligence (AI) and machine learning (ML) along with first-party data to run multivariate experiments of a marketing message. Doing so will inform how to optimize AI-generated marketing language to personalize it and maximize engagement.
For mid-sized retailers, this can create $20 million to $80 million a year in incremental revenue. Consistently speaking to customers in a manner they prefer has a meaningful impact and, when done right, an immediate return.
Personalization at scale takes experimentation and time
But remember, language personalization requires some time and experimentation to get it right.
Luckily, AI crunches data fast, making it easy to change marketing language when something isn’t working. “It’s all about adjusting how you talk to customers continuously. And with generative AI and its capabilities, you can do that at scale,” Assaf says.
Not only that, retailers working with Persado can start benefiting from its generative capabilities and create better performing language within four to five weeks. But for this to happen at scale, Assaf recommends marketers have complete buy-in from executive leadership who can align the entire company on how personalization is key to executing the business’s growth strategy.
Actions for retailers to make their digital marketing more effective
It can be frustrating when the results of digital marketing campaigns don’t turn out as expected. But there are techniques marketers can implement to start getting a desired ROI. These include:
- Emphasize personalized language: Personalize language, not just the offer, to each individual to motivate action and optimize the moment of customer engagement.
- Automate the marketing process: Use AI to create a scalable and sustainable approach to marketing personalization. Leveraging AI/ML-enabled multivariate experiments instead of A/B tests can help in finding optimal messaging.
- Guide personalization with data: Leverage specialized AI platforms that augment first-party data and translate data into actionable marketing insights. Then, analyze KPIs in relation to personalization techniques to understand impacts and identify opportunities.
For retailers looking for something they can do right this moment to better optimize their site and persuade a customer to complete their order, Assaf advises to think of emotional words you can apply at the shopping cart rather than just “continue.” Perhaps, “You deserve the best, we think you made a great choice here.” Emotional words drive behavior and implementing them is very easy for any retailer to do.
Click to view the full discussion: How To Motivate Customer Action and Drive Revenue with Personalized, Generative-AI