Are you engaging with your customers in ways that create loyalty and increase lifetime value (LTV)?
Most companies can increase growth by keeping existing customers happy and expanding the number of services or offerings sold to them. Of course, you can also attract lots of new customers, but it’s often easier and cheaper to retain existing customers (and sell more to them) than find new ones.
If creating happy customers is important to you (and your growth strategy), it’s time to explore advances in customer personalization. Here’s why. Consumers see marketing messages across multiple channels almost nonstop these days. As a result, they tend to ignore most of it.
The thing is, consumers want customized experiences. They respond really well to brands and companies that create a personal connection. When such customization and personalization is missing, customers lose interest.
In today’s digital economy, a lack of personalization can have the following negative consequences.
In this blog post, you will learn:
Marketing often involves communicating with customers in a “one-to-many” fashion. Customer personalization makes those mass messages feel more unique to each individual consumer (think of an email blast addressed to each customer by first name). But there are more sophisticated approaches that can drive engagement, loyalty and lifetime value.
However, while personalization creates unique journeys for each customer, it can be challenging to operate at scale. To solve this, organizations are implementing artificial intelligence (AI) and machine learning (ML) solutions designed to increase engagement. These solutions analyze a large number of different data points and create actionable insights to construct individual journeys for each customer, a technique called hyper personalization.
The world’s most successful companies use technology to create highly personalized customer experiences. Below are examples of two household-name brands that built their success leveraging personalization.
Amazon is a pioneer of the digital personalization experience. Amazon began their personalization journey by offering product recommendations through its “customer who bought” widget. According to McKinsey, suggesting other products purchased by similar customers generates 35% of Amazon’s revenue.
Today, Amazon uses deep learning (neural networks) to encourage the discovery of products similar or related to items customers have viewed or purchased. Additionally, they personalize the website extensively for each visitor, displaying product categories and offers they are most likely to enjoy.
The Netflix approach to personalization is founded on A/B tests. The company is constantly testing variations to its UI and customer journeys, using at least 100,000 customers to test each hypothesis.
One of the elements Netflix especially focused on was visual “landing cards” representing videos a user might want to watch. They experimented extensively with layout and visuals with its landing cards, arriving at the format that was most compelling for its viewers. Based on this extensive data, Netflix can show the card format that is the most appropriate for each group of users.
Also, Netflix uses AI algorithms to dynamically create “altgenres”, or groupings of videos that might appeal to specific users. These personalized groupings provide targeted recommendations for users and encourage them to come back for more.
These global brands have invested millions of dollars in personalization. However, personalization can be valuable to marketing programs of any size. Here’s how you can leverage customer personalization.
Here are three basic ways you can leverage personalization to drive growth and retention and improve the customer experience.
Most companies are Stage 1 of personalization, which we define as macrosegmention. This is the simplest form of personalization (5- 10 segments) that falls short of customers’ expectations.
When brands are sending emails with the recipients’ first name or segmenting the audience using basic demographics, such as gender or age, it is considered macrosegmentation.
This attempt to customize is not true personalization because it involves grouping customers into subgroups to identify certain similarities, whereas personalization is tailored to suit individuals.
For example, a common market segmentation is categorizing people by generation – Millennial, Gen X, Gen Z. But since the age ranges are so broad, this limits what marketers can know about them. Consequently, each segment receives a promotional message with only very general offers that may be irrelevant.
As companies move past basic macrosegmentation, they enter stage 2, in which they begin to use data analytics to create “microsegments.”
These microsegments are based on attributes like lifestyle, interests, attitudes, purchase behavior, search behavior, buyer stage and other factors. Drilling into more specific details means marketers can design promotions that are more relevant to customers in each microsegment.
The number of segments a brand can effectively manage is often limited to between 10 and 30 because each segment added creates greater complexity to an already unwieldy manual process of building and sending promotions.
Today’s savvy consumers expect personalized journeys, and companies that deliver the best personalized offers will be rewarded with long-term loyalty. In fact, a recent Adobe study found that 40% of retail revenue comes from returning or existing customers, which make up 8% of all visitors. As you improve the overall customer journey and personalization is key to your success. And the next step is 1:1 personalization.
Stage 3 of personalization is where companies reach brand nirvana: true 1:1 personalization. To personalize at scale, marketers need to access and process large amounts of disparate data—including customer, transaction, and third-party data. This gives brands the opportunity to understand each customer more fully and deeply than ever before. But, as noted in Stage 2, this cannot be done manually.
To achieve this 1:1 relationship with customers, marketers need access to technology that leverages artificial intelligence (AI) and machine learning (ML) algorithms to constantly analyze an audience and tune promotions.
By integrating advanced digital technologies and proprietary data, companies can deliver offers that their customers care about and engage with. Not only are they improving their customers’ experience, companies also are seeing revenue growth of 6% to 10% resulting from 1:1 personalization — two to three times higher than those that do not.
Formation’s solution drives business results by building and deepening a brands’ relationship with its customers. We do this by delivering insights to form offers that are individually tailored for greater engagement. Formation uses artificial intelligence (AI) and machine learning (ML) algorithms to constantly analyze the audience and tune offers. This approach enables offers to become smarter and more effective with each customer interaction, resulting in a better experience, while driving significant increases in incremental revenue and customer lifetime value.
Formation empowers companies to achieve true 1:1 marketing at enterprise scale. It automates offer development and execution, enabling marketing teams to be more efficient and effective in engaging and retaining customers. Use of Formation's AI-powered solution has resulted in 3x incremental revenue and 2x increase in marketing efficiency.