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How Retailers Are (actually) Driving Revenues With Generative AI

Artificial Intelligence

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In 2023 we’ve seen the widespread emergence and adoption of generative AI across sectors. For retailers, there are many opportunities to leverage this technology to better understand and engage with customers through marketing strategies that will earn them higher revenue and stronger, more loyal customer relationships.

To explore this further, I turned to Alex Vratskides, CEO and co-founder of Persado, an enterprise generative AI company that’s been leading the charge for using AI in marketing for more than a decade.

Gary Drenik: What is Motivation AI? How does it differ from generative AI technology?

Alex Vratskides: Motivation AI is a class of enterprise generative AI technology that uses advanced machine learning (ML), natural language processing (NLP), and deep learning transformer models to understand intent and create emotion-informed messages that are quantifiably proven to motivate individuals to take action.

It differs from the many large language models (LLMs) that pull data from all over the Internet, such as ChatGPT. Motivation AI is instead trained on a specialized dataset of real interaction and transaction data from 150 million U.S. consumers—the equivalent of 645 years of A/B testing—to measure and refine motivation-focused language, emotional response, and engagement.

There are countless challenges generative AI can help retailers solve right now. Those challenges fall under two broad categories: efficiency and effectiveness. If a marketing team is looking for a productivity jumpstart and aiming for quantity, ChatGPT is a great way to begin. But as my Persado co-founder Assaf Baciu explained in this Forbes Tech Council column, effective applications of generative AI produce outputs that are better in terms of the results you’re trying to achieve. In marketing, for example, more ads or email messages can be counterproductive (or produce brand fatigue) if they’re irrelevant to a customer’s needs or speak to them too generically.

We developed Motivation AI because we know consumers’ decisions are deeply tied to emotion. The retailers that understand and lean into the distinct emotional drivers most likely to influence individuals to take action—like completing a purchase, learning more about a product, joining a loyalty program, and so on—have been significantly improving their customer experience and bottom line. They are using generative AI for effectiveness.

Drenik: What are some examples of emotional drivers or narratives that can motivate a customer to engage?

Vratskides: Just as consumers and their outlooks are constantly changing, so too are the emotions, personal narratives, and external factors that motivate or reinforce their shopping behaviors.

It’s important that brands continuously experiment with different languages that correlates to emotional drivers like these to reveal which work best in different seasons, with different segments, across marketing channels.

For example, one emotion that frequently drives engagement is Achievement. You can see language like this resonate in phrases like “we’re rewarding you with 20% off” or “you’ve earned this special offer.” As humans, we like to feel successful. We notice a little praise.

However, while this emotion tends to motivate customers, it won’t always work. You may have a segment of your audience that is better motivated by a Gratification. Language like “you’re getting 20% off” or “we’re treating you to this special offer” makes them feel valued. Many people like to receive special perks.

In Persado’s 10 years of testing the nuance of different words and phrases, the constant is that emotional language motivates action. The specific emotion, however, can vary based on the audience, campaign, channel, and seasonality, among other factors. While the examples above center around promotions, this holds true across different types of messaging.

On the shopping cart page of an ecommerce site, for example, one person might respond to Excitement in the headline “Awesome Finds!,” while another responds better to Encouragement in the headline “Almost Yours…”

Motivation AI combines emotions with other aspects of language to truly personalize every communication. We look at how product descriptions and offers are phrased, sentence structure, formatting, and the story of the campaign itself: the narrative. Every message a company sends out speaks to its brand values and customer values, including narratives like Prestige, Togetherness, Indulgence, or Timelessness, among many others.

It’s powerful for a retailer to learn that an email subject such as “Treat yourself: Emily, you’re invited to enjoy these GREAT deals!” taps into Indulgence, through the emotion of Exclusivity, with personalization, formatting emphasis, and a vague offer. Motivation AI writes it that way because all together, that subject line is predicted (based on learnings from a vast knowledge base) to greatly increase the odds that this Emily, having subscribed to this brand, or received this message as part of today’s fall email campaign, will open, click, and purchase.

Drenik: How are retailers using Motivation AI?

Vratskides: Some of the most well-known brands—including Coach, Kate Spade, Gap, and Marks & Spencer—use Motivation AI to ensure their marketing content on email, social, web, or SMS aligns with the emotions, narratives and other language elements that resonate best with each customer.

Implementations vary by brand, but we’ve seen retailers achieving strong ROI by first tackling cart abandonment rates with personalized language on the online cart and checkout pages. Next, they’ll deepen ROI and strengthen customer relationships, add-to-bag rates, and program acquisition by individualizing copy on web and mobile app product pages, email and SMS campaigns, and even social posts. Experimenting with language across these channels provides valuable customer insights as well, which brands then apply directly to their next campaign to realize stronger performance.

Our 30 largest customers have collectively achieved $1.5B in incremental revenue using Motivation AI during the past four years. On average, brands see a 41% conversion lift across channels. Many of our customers have used AI-generated language that applies emotion-aware drivers and motivators to encourage shoppers to convert without needing deeper discounts.

Marks & Spencer, for example, uses Motivation AI to unlock greater insights into how customers respond to certain languages. The UK retailer found their customers did not respond well to phrases mapping to regret (e.g., “Only two left” or “Buy quickly”), so they shifted their campaign. After removing “regretful” language from their messaging, average email conversion rates lifted by 20% over a six-month period. This is just one sample of how GenAI can drive sales.

Drenik: Those conversion rates are impressive. How might a solution like this impact digital marketers? Will they be out of a job?

Vratskides: Generative AI can significantly improve productivity, but it will never completely replace human marketers. It’s more of an extra team member, augmenting digital marketers’ expertise and empowering teams to scale their personalization strategies.

A recent Persado study found that while humans are essential for the creative process, when they rely solely on their intuition or experience, they can miss out on millions in revenue. The survey found marketing leaders chose the best-performing message only 30% of the time.

Adding the power of AI insights helps marketers better understand their customers and their emotional needs, maximizing resources. New easy, self-service Motivation AI technology leverages our deep knowledge base, encompassing a decade of machine learning from Fortune 500 and other large enterprises, to predict the highest-performing on-brand digital marketing message in real time.

That said, AI still has its limitations and just like its human counterparts, the tech needs to be held accountable. Human marketing teams must be involved to continuously test, analyze, and train these models to ensure their outputs remain on-brand, relevant, and effective. After all, we’ve seen that AI can sometimes produce bizarre or off-putting content, leading many customers, up to 74.9% according to a recent Prosper Insights & Analytics survey, to even be wary of interacting solely with AI for customer service.

Prosper – Prefer To Communicate With When Shopping Online

Prosper Insights & Analytics

Just as generative AI can supercharge productivity and Motivation AI achieves data-driven results, human marketing teams must always be there to guide and apply it. The power comes from people + AI — we will just go from producing to more directing.

Drenik: Beyond email subject lines or social media posts, how else can retailers use AI to impact their bottom line?

Vratskides: Retailers have made great strides in personalizing much of the online customer journey — up to the cart and checkout stage. No matter what brands know about their customers; their recent purchases, their order frequency, and so on, the cart experience has remained identical and static, catering to the lowest common denominator. Meanwhile, online cart abandonment rates remain high: at 70% average on desktop, and 85% on mobile, costing retailers billions in revenue.

Recent innovations in generative AI now offer a solution to this age-old ecommerce problem by enabling more personalized, dynamic online cart and checkout experiences — a powerful tool that diminishes cart abandonment. Motivation AI can now personalize the language on these pages in real time, based on browsing behavior, customer preferences, buying history, and the emotional drivers most likely to motivate each customer. This can have a massive impact on conversion. Retailers in the U.S. and Europe are achieving a 3-5% increase in online sales within a few weeks by applying Motivation AI at this critical stage in the customer journey. This seemingly modest uptick in sales equates to millions for some brands. It’s the epitome of applying generative AI for effectiveness.

Drenik: Alex, thank you for your thoughts and insights on such a timely topic. Although many retailers are already using generative AI to enhance their productivity and efficiency, there’s clearly still a lot of untapped potential for driving revenue and strengthening customer relationships. I’m looking forward to seeing how Persado continues to help retailers take advantage of these opportunities with Motivation AI.

Originally Appeared Here

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