In today’s highly competitive market, simply delivering the products and services customers need isn’t enough to make a lasting impact. The companies that truly stand out are the ones able to foster an authentic connection to their brand based upon trust and loyalty. Creating that sense of loyalty is one of the great challenges facing organizations looking to differentiate themselves from their competitors.
The type of personalization needed to build those connections is only possible with hyper-personalized messaging and experiences, which help customers feel like they’re supporting brands that align with their values and understand them as individuals. By engaging on this personal level, companies can drive both ongoing customer advocacy and incredible revenue impact.
Personalized messaging is a powerful tool for building genuine relationships with potential customers, but few companies are able to maximize its full value. That’s often because they’re taking a purchase-focused approach that is constantly prompting people to buy something in order to drive short-term revenue goals.
Rather than seeking to understand what actually motivates customers and why, they frequently take what little information they have and try to make a quick sale. Anyone who has received a flurry of promotional messages after making a similar purchase can attest to how ineffective this strategy can be. The main problem is that it puts the revenue needs of the business ahead of what the customer might actually want, which should be the real focus of personalization.
But these efforts are also complicated by incomplete data. For some marketers, personalization can amount to little more than using purchase history and demographics to segment people into one of several categories of potential buyers. The problem with this thinking, however, is that it gets customer motivations all wrong. Knowing who purchased something doesn’t provide much insight into why they purchased it, which makes it almost impossible to know what they might need or want next. This approach is akin to driving down the street, noting which houses are red, and then sending the owners promotions to buy more red paint.
Effective personalization leverages artificial intelligence to analyze every available customer interaction and touchpoint to develop a more nuanced understanding of what motivates decisions and behavior at the individual level. With AI technology, it’s possible to achieve this form of hyper-personalization at the scale and velocity necessary to create what feels like segments of one.
But gathering that information is just one part of the puzzle. It still needs to be deployed in strategies that customers don’t find intrusive or irrelevant. Research conducted by Forrester has found that there are a few basic rules to follow when it comes to responsible and respectful use of personalization.
Effective personalization builds relationships over time. Like any healthy relationship, it shouldn’t be exclusively transactional. Customers aren’t always going to be interested in buying the latest products or services from a company (in fact, they usually won’t be). But they will want to hear about things that are important to them or interest them. Providing that utility builds trust and makes customers more likely to stay engaged with a brand, which leaves the door open for potential purchases in the future.
Customers form the strongest bonds with companies that are able to engage with them on a personal level. Even the most cynical consumer often finds themselves favoring a particular brand simply because they feel like the company understands people like them and presents itself in an authentic fashion. In order to make that connection, personalization efforts have to focus on who customers are rather than what they buy or what demographic they belong to.
A good personalization strategy engages on an individual level in ways that make people feel appreciated and valued. Without the right information, however, this approach can come across as forced and superficial, so having robust data insights about what motivates someone is essential for delivering a genuine message. Given the amount of data required to create a detailed picture of customer motivations, only AI is capable of providing these insights.
In a crowded, multichannel media landscape, there is a tendency among marketers to engage with customers as much as possible to remain top of mind. But piling on often has the opposite effect, turning even the most well-crafted marketing effort into annoying background noise that’s ignored or discarded. As personalization strategies become more common, it’s also important to avoid coming across as too intrusive. Allowing customers to set the terms of communication by setting how and when they’re contacted, can help to reinforce a sense of trust and respect that is essential for building a lasting relationship.
The need to implement personalized interactions is growing fast. A recent McKinsey report found that 71% of consumers expect some form of personalization and, more importantly, 76% are frustrated when they receive more generalized messaging. Although most companies recognize the tremendous value of personalization strategies informed by AI-driven insights, they don’t always know where to start. Rather than beginning with the difficult challenge of building loyalty with infrequent or lapsed customers, they can instead refine their strategies by focusing on their best customers.
Companies are already quite good at engaging with their most engaged customers through things like loyalty programs, membership incentives, and less sophisticated forms of personalization. These people usually have some measure of loyalty to the brand and are more likely to be forgiving of messaging missteps than the average customer. They also typically provide much more data to work with, which makes it easier for AI platforms to identify trends and motivations in their behavior. Loyalty programs and memberships can encourage people to share more about themselves by asking questions to complete their profiles or inviting them to provide feedback on their experiences.
By analyzing these direct interactions with customers and data points from other sources, language-driven AI models can go far deeper than purchase history to develop a unique profile of an ideal customer based on their actual motivations. Machine learning then generates unique narratives and continuously refines its language to develop predictive responses that are most likely to inspire individuals to engage with the brand.
This precise, hyper-personalized form of messaging can then evolve with consumers as their motivations and needs change over time, allowing companies to always meet them with the right content at the right time. The lessons learned from these initial efforts can then be used to build relationships with a broader group of current and potential customers, who will become easier to understand and predict as AI messaging becomes more refined.
Effective personalization strategies rely on massive troves of unstructured data that can only be processed by powerful AI tools. By analyzing millions of customer interactions, it’s possible to develop a nuanced understanding of what messages are effective under different conditions. But this is only the beginning of a much more transformative approach to personalization, one that can help organizations transition from broad, profile-based marketing to a truly individualized approach that treats each and every customer as a unique individual.
Motivation AI can distinguish the preferences of individual customers and generate content that is most likely to resonate with them on a personal level. This revolutionary technology is already allowing organizations to scale their personalization strategies and create genuine connections with customers like never before. By strengthening these relationships, forward-thinking companies will be able to deepen brand loyalty and deliver greater value to their customers over time.