As technologies advance, the way we market to customers changes, too. At this point in the game, customers expect personalization in marketing. Because if it’s not personable, it’s forgettable - and that’s exactly what you can’t be if you expect to be successful in direct-to-consumer ecommerce in 2024.
In this blog, we’ll outline some of the current trends in the ecommerce landscape, the growing importance of a personalized customer experience, and the increased integration of AI and machine learning. Also, we’ll discuss how using the correct AI-based tools can enhance your marketing efforts, because you should be working smarter and not harder!
First of all, it’s more than just using your customer’s first name in an email (but that’s a good step). Integrating a personalization strategy can hit many different marketing mediums, from email to social media and blogs to help customers feel seen. It also involves collecting data related to your customers and using that data to craft personalized marketing experiences. When you know more about your customers, you can reach them more effectively.
There are a few reasons why you might want to personalize your marketing. For one thing, 71% of consumers expect companies to deliver personalized interactions, and 76% get upset when it doesn’t happen. You’re in the business of having happy customers, right?
When you personalize your marketing, you can drive better performance and happier customer outcomes. Companies that grow faster tend to drive 40% more of their revenue through personalization than slower-growing companies, so personalization is definitely a factor!
The most important factor is delivering value. In today’s economy, customers expect more for less. If a brand can understand a customer’s path to purchase and deliver a hyper-relevant experience, that will increase engagement and loyalty. It’s the zero- and first-party data in combination with smart segmentation that will enable marketers to significantly increase their return on investment.
Before marketing went digital, personalization was manual and based on broad demographics, which lacked accuracy. In today’s digital age, brands have access to all kinds of consumer data, and AI and machine learning has made it possible for marketers to shift from broad categorizations to focusing on individual behaviors. This enabled a transition from reactive strategies to anticipatory ones.
Here are a few reasons why marketers should use AI in their personalized marketing strategies:
And, mainly: it saves marketers time and energy, so they can create more content more efficiently.
Consumers are distracted. The average time spent on a phone in non-voice applications is 4 hours and 30 minutes per day, which is expected to reach 4 hours and 39 minutes by 2024. When the average American checks their phone 144 times per day, and shrinking attention spans, it can be hard to keep customers engaged. If the average amount of time a customer spends on a site is 3 page views per session, you’ve got limited time to get them hooked and interested in the product.
Robert Lorenzen, Senior Director of Product Marketing at Attentive, says marketers can use AI to take over some of the tasks that marketers typically manage, especially to maximize the likelihood of engagement on mobile.
Attentive AI™ was born to help brands connect with the distracted mobile consumer. But this can be difficult because the hook needs to be personalized to each person. What works to pull-in any one consumer is going to be pretty personal to that individual. Marketers can set rules within a platform, but at the end of the day, it ends up working in a “1-to-Most” ratio (and speaking to a larger, broad audience). Personalizing this on a 1:1 basis would be very difficult for a singular marketing human.
With AI, however, we can use the data we have on consumers along with generative AI to speak to the consumers as individuals. When this is done correctly, the customer will see a message that’s relevant, helpful, and makes them feel known by the brand.
Some of the things Attentive has solved with AI may seem small, but they’re essential for building better messages. For example, with a message trigger for an abandoned cart, you could program some logic so the platform knows which product the customer was looking at. But in reality, the product itself has a lot of details in the string that are relevant to logistics, not the consumer.
With AI, Attentive can draw out which product the customer is looking at with a specific SKU; for example, a red swimsuit. It’s more meaningful to the customer to write content, using AI, in real-time, as part of the customer journey. It’s more meaningful to the customer to hear about the red swimsuit they were thinking about purchasing, rather than item 4958539205960.
One of the biggest concerns for marketers is whether AI can match the tone and voice of a brand, as it is very important to remain consistent. As models continue to evolve and learn, the ability to match a brand’s voice will be better and better. As of now, Attentive is able to take information about a brand’s voice and train the model to use the right voice so that messages are delivered using the right tone. By fine-tuning each message to reflect the distinct voice, tone, and style of your brand, you’ll have enhanced messaging performance with more meaningful messages.
Traditional segmentation can be time-consuming and often doesn't justify the effort. However, AI can automate this process, identifying and targeting segments with precision. For example, AI can identify customers who are likely to buy again and tailor messages to them, optimizing the use of marketing resources.
A real-world example Robert uses is when a menswear brand used an AI-driven SMS campaign during an unexpected event—Slack being down. The timely, personalized message resonated with customers and created a strong affinity for the brand. This example underscores the advantage of having AI handle routine tasks, allowing marketers to be more responsive and creative.
AI's ability to analyze vast amounts of data quickly is another significant benefit. John Coyle, Head of Professional Services at Triple Whale, highlights that AI can help marketers make informed decisions by providing valuable insights from data that would otherwise be challenging to visualize. For instance, AI can predict recurring revenue from new customers, helping brands manage their inventory more effectively and avoid stock issues.
According to insights from Attentive's customer advisory board, marketers have been collecting data for years, but the sheer volume often leads to “analysis paralysis.” AI excels at sifting through data, identifying patterns, and providing actionable insights. This capability allows marketers to make data-driven decisions more efficiently.
AI is revolutionizing marketing by streamlining processes and enhancing efficiency, but it is not replacing human marketers. Instead, AI acts as an assistant, handling routine tasks and providing valuable insights, allowing marketers to focus on creativity and strategic decision-making. By leveraging AI, marketers can connect with consumers on a personal level, manage campaigns more effectively, and make data-driven decisions that drive business growth. The future of marketing lies in the harmonious collaboration between AI and human expertise.
Ready to get started with AI? Book an Attentive AI™ demo here.
.png)
© Triple Whale Inc. 266 N 5th Street, Columbus OH 43209
.png)
