Obsession can mean many different things. It can describe a Taylor Swift superfan’s dedication to decoding hidden messages in her album covers or laser-focused attention to detail. But when it comes to customer satisfaction, obsession is exactly what’s required—in every experience, at every touchpoint and on everyone’s mind. For marketers, success isn’t just a moving target; it’s a swirling, whirling tornado of targets that are seemingly impossible to capture in addition with a perennial enhancement to the overall customer value. It’s no coincidence that brand marketers often use military terms to describe their work (campaigns, tactics, targets, etc.) because it’s a war out there—a war for attention, relevance and, above all, loyalty.
“Aim small, miss small” is a popular saying in marksmanship, a phrase meant to remind shooters to pick a specific target within a larger target. That way, if you miss, your level of focus will still result in finding at least a piece of the larger target. In marketing terms, it’d be the equivalent of narrowing in on a specific type of customer and creating personalized experiences, instead of broadly targeting an entire generation.
According to Forrester, 57% of B2C and 75% of B2B customers reported that a personalized experience would make them ‘much more likely’ or ‘significantly more likely’ to remain loyal to a brand.
Work Smarter—and Harder
Customers expect brands to keep a close pulse on their preferences. To truly understand your audience, you must examine their past behavior. Because while every person is unique, certain markers appear when multiple interactions are examined over time. Are they responsive to sales events? Do they make repeat purchases? And if so, at what time? These are all clues into how to better reach and relate to someone at (or preferably before) their decision moment. The more information a company collects about a customer, the more they can construct 1:1 personalized experiences.
The truth is, 1:1 personalization requires a lot of data, and even more resources to help sift, segment and analyze that data. Not every company has the budget to build its own bespoke data science programs, but there are other methods of mining these valuable insights. Here are three ways companies can create cost-effective personalization to enhance customer satisfaction:
- Double-Down on Data Analytics
The term “personalization” is a bit of a misnomer; it doesn’t mean randomly plucking out a single customer and obsessing over them individually. Rather, the concept emerged because digital marketing had been so impersonal for so long that customers got fed up with being treated like just another number in a spreadsheet.
Customers receive dozens of marketing emails every single day, but only a small fraction of those are actually opened. What makes a brand stand out and grab your customer attention is its personalized version of that email. Even simple things like greeting email recipients by name, offering rewards on their birthday or recommending products based on their purchase history can have a huge impact on loyalty. Organizations, such as Adobe, have created products that allow marketers to create, personalize and send email campaigns at scale, by leveraging customer data to craft highly personalized emails that resonate with individual recipients.
Amazon relies heavily on AI-driven hyper-personalization to drive conversions. In 2023, it added several new features to Prime Day like invite-only deals and “buy again 2.0,” which offered customers a chance to make repeat purchases at a discounted price. Both features rely heavily on customer data. The approach has been successful for Amazon, which boasts a 35% conversion rate directly attributable to its recommendation engine.
For companies on a tight budget, investing in partnerships with external vendors can be an affordable option to gain access to this valuable customer data. Businesses generate a TON of data, but it’s often siloed across an organization and (ironically) difficult to organize. By bringing in a data analytics team, companies can unlock the value of that data and extract intelligence that can lead to full journey maps of their customers, allowing brands to optimize outreach timing, monitor KPIs and adjust marketing strategies.
- Focus on Automation to Develop Scalable Personalization
Creativity is a key determinant of company resilience, but businesses have long struggled with how to combine creativity and strategy at scale. Historically, the process was long on research and development and short on ROI. Now, thanks to new tools like artificial intelligence (AI) and automation, companies can collate vast sets of audience data into immediate insights and build highly-targeted campaigns that can be rolled out across specific behavioral segments. In other words, the process is flipped—automation can handle the grunt work of distribution, while marketers can focus on the higher-value tasks.
Pioneers in personalization like Amazon and Netflix have paved the way for other industries, like banking, to adopt customization at scale—speeding up legacy processes and keeping customers happy. For example, financial institutions and fintechs are able to automate customer requests for credit limit increases. According to TechCrunch, deep learning recommendation systems can be used to understand the customer’s broader life experience and either recommend a credit increase or identify alternative opportunities for achieving the same outcome, like qualifying for a personal loan. Both are possible without speaking to a customer representative.
It’s important to remember though that automation doesn’t mean “set it and forget it,” rather it’s a machine that needs constant monitoring and fine-tuning to be effective at scale. Mass automation without strategic oversight is a recipe for disaster, and companies should invest in robust reporting to ensure their personalization is still personal.
- Create Compelling Content with Generative AI
The past year has been dominated by talk of generative AI technology, like ChatGPT, that can automatically create text, imagery and other forms of content. According to industry experts, generative AI “takes personalization beyond reactive adjustments and actions, enabling businesses to predict and generate content tailored to anticipate future customer behaviors and preferences.” Examples of this include: creating custom promotional offers, personalized shopping guides or unique user experiences.
Ecommerce marketplace eBay is experimenting with ways to create tailored content for regular users. By integrating AI into the platform, eBay taps into a growing demand for personalized shopping experiences. For instance, eBay’s “shop the look” feature is a sophisticated blend of AI and user engagement, designed to learn and adapt to the individual style preferences of its users. By analyzing shopping histories, this feature curate’s selections of items and outfits that align with the customer’s fashion sense, making personalized style widely accessible.
Trust the Personalization Process
Times change, behavior evolves, and marketing must stay agile to remain relevant. Agile thinking is “a way of working that seeks to harness the inevitability of change rather than resist it,” according to McKinsey. By maintaining agile feedback loops within teams, companies can adapt faster to customer needs, ideally before they know they need it.
As the economy strengthens, inflation cools and innovation continues at its accelerated pace, marketing teams are poised for yet another busy year obsessing over customers. The best kind of obsession is focused on continuous improvement—striving for better, not perfect. Enhancing customer experience needs to be viewed through the same lens, and personalization should get stronger as you begin to understand your customers better through data.
Boobesh Ramadurai is Marketing Leader at LatentView Analytics.
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