Personalization is a powerful technique for retaining customers and fostering loyalty. It’s no longer a trend. Today’s savvy customers expect it. In 2021, 45% of global consumers indicated a brand would lose their loyalty if it didn’t deliver a personalized experience. In 2022, that number jumped to 62%. But developing personalized content can be time consuming, and brands don’t necessarily have the creative talent resources to develop it. But there is a solution. Many businesses benefit from using Personalization AI to create collateral at scale. This can improve sales by delivering a custom experience throughout the buying journey.
Content personalization is a branding and marketing strategy that involves delivering tailored content to match the preferences or behaviors of individual customers. An application of targeted marketing, content personalization enhances a brand’s relationship with customers and promotes more repeat sales. But how can brands do it?
Brands gather a lot of information from prospects browsing a website. They can then analyze the data captured from browsing histories to make predictions about customer preferences using data analytics. Using these predictions, companies can leverage language Generative AI to personalize content based on the expressed interests and behaviors of visitors to the site. Instead of seeing the same generic message, consumers receive messaging tailored to their needs, concerns, and pain points.
Consider this basic example of content personalization: A furniture retailer uses a pop up questionnaire that asks new visitors to identify the category of furniture and interior design style they prefer. From there, appropriate content appears. Instead of suggesting a generic blog post on “Six Easy Ways to Update Your Home Style for Spring,” a homeowner sees an article on “Easy Design Updates for Your Cottage-Style Home.”
Consumers view this kind of content as valuable. When brands deliver a better experience like this, consumers respond positively—as long as the data informing the personalization comes from session data or first-party sources, not purchased from third parties.
Solutions like the Persado Motivation AI—a Generative AI solution that taps into customer motivations using language—automates some of the process of delivering content personalization. The 5 Capabilities of Persado Motivation AI include a customer knowledge base, language generation capabilities, and automated experimental design that allows brands to deploy AI-generated messages, measure their impact on different customers, and optimize the message based on real-time customer engagement.
Content personalization is centered around adding relevancy and value to the customer’s digital experience. However, many brands still put the customer’s name on an email or on the website and call it personalization. Or they send the customer a coupon code on their birthday and call it a personalized experience. While these are nice things to do, they aren’t actually content personalization. Brands provide content personalization by recommending products that fit the customer’s needs and lifestyle or using digital messaging that speaks to them and their buying motivations. That’s where AI comes in.
Today’s most effective personalization tools employ the latest AI-powered capabilities including Generative AI, machine learning, deep learning, and natural language processing (NLP). Together, these technologies work together to customize messaging, content, products, and services and reshape how brands interact with customers and promote more profitable customer journeys.
Customer data is the fuel that powers the personalization AI engines. Using AI, brands can extract insights on every visitor who lands on a website and predict what content will engage them best. As more data becomes available, AI improves its recommendations. Best of all, these actions occur in real time.
Uncovering the right language to inspire the consumer is the next step in personalization. With enterprise-grade personalization AI, brands can leverage language to boost engagement and conversions with messaging that’s proven to perform for each individual segment and channel.
Personalization drives marketing strategies throughout the customer journey. However, companies often face challenges in delivering compelling personalized experiences at different stages. AI comes to the rescue to improve personalization by delivering Generative AI content at scale and capturing insights that can reveal what messages are right for which customers.
Other benefits of personalization AI include:
AI and machine learning procure data from a multitude of sources and then analyze these seemingly disconnected sets of data deeply and quickly to drive personalization at scale. The process has the potential to tame human bias about the audience and what influences them, while identifying opportunities for increased conversions and revenue.
However, preventing bias in personalization AI is also a concern and is an evolving space. Marketers should take the time to revisit datasets to offer explainability.
There are also other factors that could help remove potential AI bias, such as robustness—meaning having multiple sources of data to limit the possibility that a biased sample skews the predictions—and maintaining data security and privacy. Remain vigilant to keep first-party data as free from as much bias as possible.
Few organizations have the in-house resources necessary to gather, analyze, and connect gigantic sets of data and explore advanced analysis on it. AI can help. Tasks that take humans months to complete may take AI and machine learning half a day.
In the case of delivering content personalization grounded in first-party data, Persado leverages the first-party data our clients collect to generate optimized content for different segments. User response data then provides another form of first-party data informed by customer engagement.
One example of this process comes from an airline customer of Persado that used a web banner ad to promote same-day, first-class seat upgrades to ticket holders. This campaign produced $8 million in revenue by leveraging language personalization AI across multiple channels. The scale, speed, and impact of this use case would be almost impossible to replicate using human agents.
Brands use AI and machine learning to identify the customers who generate the most revenue today and those with the potential to do so tomorrow. They use those insights to deliver more compelling loyalty experiences. Personalization AI also has a role to play in efficiently and effectively engaging lower-value customers to possibly transition them into a higher value bracket.
As a case in point: A top airline worked with Persado to encourage recent vacationers to book their next trip to earn extra bonus points. The campaign motivated a 97% increase in loyalty program use.
AI helps marketers run targeted brand campaigns, which over time, contribute to more revenue with less marketing spend. Research indicates that consumers enjoy targeted ads to improve the buying journey. Brands can not only leverage AI to sift through volumes of data to drive more relevant customer segmentation. Personalization AI can also create higher-impact ads using messages personalized for different segments across the brand’s channels.
Many AI-powered personalization reporting tools exist that collect, sort, and draw valuable insights from audience data. This provides a better understanding of your customer and their interaction with your content.
AI-powered personalized product recommendations make upselling easier. When customers visit a website, an algorithm can assess their buying intent. They can also add (in the case of repeat visitors) insights from previous transactions, demographic data, interests, and other pieces of information. Armed with these insights, the website can present visitors with relevant and product suggestions. When they marry the right product offer with optimized language, they can produce higher engagement and motivate action.
For example, a retailer well-known for its weekly coupon campaign leveraged first-party data from its customer data platform to segment customers. The brand then worked with Persado to create custom messages for each segment. For example, shoppers who didn’t need a coupon received a different message from those who wouldn’t shop without one. In addition, there were different kinds of coupon users: some like a percentage discount while others like buy-one-get-one-free offers. Using those insights and coupling it with language-based personalization AI, the brand delivered distinct coupon types based on customer behavior. The result was targeted engagement that produced an estimated $10 million in incremental revenue in the first year.
Personalization AI powers optimized searches by applying insights from previous activity in order to customize search results in real time. Optimized search also deploys natural language processing (NLP) from machine learning to display accurate results. For example, NLP understands that running shoes and runner’s shoes mean the same thing, so an optimized search recognizes both terms.
A search intent strategy can adjust the results as customer sentiments evolve. Returning to our running shoes example, product selection may differ for a customer in her 20s from a customer in his 60s. Or for a customer training for a marathon, who will need several pairs of running shoes, compared with a weekend warrior who jogs once a week.
One-size-fits-all messaging is a thing of the past. Personalization AI strategies that leverage Generative AI solutions can create messaging that delivers maximum engagement and conversion. Brands can:
The Persado Motivational AI Platform is purpose-built to deliver optimized language across every channel and customer journey stage. The computer manufacturer Dell, for example, leveraged Persado-generated language in its emails, digital ads, and even radio ads. Instead of serving the same content to each prospect, Dell delivered the right message at the right time, boosting conversions by 45%.
Personalization AI can help identify user sentiment for segments or even individuals. By learning personality quirks, systems observe behavior to determine satisfaction rather than guessing based on generic learned behavioral traits.
Websites that rely on big data and machine learning revise content for different visitors. Using a multitude of data points, including purchase data and other live or past behavior, they can change the game by dynamically changing content.
Brands achieve relevancy by showing customers content or products they want to see and curating unique shopping experiences. Relevancy creates distinction, which makes customers feel special. After all, shopping remains an emotional experience. AI personalization finds the right language that resonates with consumers that inspires action across every touchpoint in the sales process.
Brands don’t decide on the value of personalization; customers do. AI-powered personalization solutions sharpen your lens. In today’s competitive landscape, brands need to do more with the data they already own. Persado builds on customer segments brands already have and reinforces them with personalized language that drives engagement.
It’s time to transform your brand. See how Persado can deliver significant incremental growth for your business by requesting a demo.
The post Personalization AI: Driving Conversions Through Content Personalization appeared first on Persado.
Showing speed and precision, one of Google’s latest experimental models, Exp-1206, shows potential to alleviate…
You can get whole seconds back every morning by measuring your coffee beans in the…
The report The economic potential of generative AI: The next productivity frontier, published by McKinsey…
The new model shows open-source closing in on closed-source models, suggesting reduced chances of one…
Samsung’s celebrated flagship soundbar does just enough to beat out the rest of its Dolby…
Even highly realistic androids can cause unease when their facial expressions lack emotional consistency. Traditionally,…