Deep personalization: The key to reaching the senior market


Learn how your company can create applications to automate tasks and generate further efficiencies through low-code/no-code tools on November 9 at the virtual Low-Code/No-Code Summit. Register here.


The aging adult consumer population offers boundless opportunities for tech companies. The number of people aged 60 and above is expected to double from 2019 to 2050. And in the U.S., the aging population is expected to become the primary driver of consumer spending growth in the coming years, with 70% of all available U.S. income owned by those over 55.

Yet many businesses struggle to reach this high-potential group, often taking a one-size-fits-all approach to an incredibly diverse population. My company, Honor Technology, works primarily with individuals over the age of 65. Since our founding nearly eight years ago, we’ve successfully tapped into the aging market to become the largest home care network.

So, what have we found to be the secret to successfully engaging aging adults? Providing deeply personalized experiences through the use of data.

What you need to know about the senior market 

Many companies have tried and failed to reach the aging adult population. That’s often because products, services and marketing tend to take a universal and often overly simplistic approach to engaging the senior market. Yet older adults are one of the most heterogeneous and complex groups out there. One 72-year-old might be retired, have dementia and reside in an assisted living facility. But another 72-year-old might work, run marathons and travel the world. If brands aren’t accounting for all the differences that exist within the aging adult population, many seniors will think, “This product isn’t meant for someone like me.”

Event

Low-Code/No-Code Summit

Join today’s leading executives at the Low-Code/No-Code Summit virtually on November 9. Register for your free pass today.


Register Here

Another nuance worth noting is that seniors have fairly established preferences. They know what they like, and don’t want to deviate from the experiences (and brands) that have worked for them in the past. Research on personality development has found that a person’s openness to changing their preferences increases in their 20s and steadily declines throughout aging. No wonder seniors tend to prefer shopping in person or talking to customer representatives over the phone — it allows them to find goods and specify services that meet their individual needs.

The crux of the challenge for brands engaging older adults is this: While there’s significant heterogeneity when it comes to what a “senior” looks like, the aging adult population also has deeply ingrained preferences. While audience segmentation might work, it’s simply not sustainable nor specific enough to succeed at scale. Somehow, brands must account for each senior’s individual preferences and meet a wide range of expectations.

So what does success with seniors look like?

To reach the aging adult population, business leaders need to invest in deeper data collection and management and can even use AI technologies to better understand people’s motivations and behavioral patterns. By embracing personalization, brands can overcome the challenge of catering to a diverse, yet very particular market by providing each senior with tailored recommendations, content, offers and experiences.

Better personalization is enabled by embracing data and learning technologies. These technologies can help businesses identify customer patterns and ultimately allow them to improve their products and services. Machine learning can observe a customer’s preferences over time while also tapping into similar user profiles to provide highly personal and unique experiences.

Advertising and marketing technology was one of the first sectors to apply personalization broadly by targeting ads to users who would most likely enjoy a product or service. Beyond marketing applications, personalization can be used to streamline or add value to many products and services. 

For example, consider a voice assistant device that can learn to recognize a senior’s voice, observe how long it takes for that individual to respond to the device, and remember their most commonly asked questions. Over time, the voice device can adjust to that senior’s habits — responding only to their voice, listening for as long as it takes them to respond and offering answers without being prompted (such as the daily weather forecast).

The dos (and don’ts) of personalization

Great products are defined by the impact they have on users’ lives, and this should be the North Star for any use of personalization. Once you’ve determined that personalization adds value to your product or service, identify the breadth and depth of data you’ll need to form AI-powered insights. These insights will never be perfect, but they can provide actionable recommendations for product optimization. Quick iteration testing and granular user research are particularly useful for collecting user data, and scalable data architecture can help extract dynamic insights for informing product adjustments. 

Personalization also requires a constant evaluation of “build vs. buy” when it comes to your data collection and management capabilities. Some brands choose to partner with a customer data platform (CDP) or data management platform (DMP) to secure customer information, but the value of outsourcing these capabilities is highly unique to each organization’s life cycle, industry and personalization use case. Though building certain features in-house can be costly and time-intensive, it may be worth it to ensure control over core components of your product and tech stack and protect sensitive user data. 

Continuous optimization and rigorous human oversight are central to ensuring you have the insights at your fingertips for making accurate customer recommendations. Let’s face it — there’s nothing more frustrating than being on the receiving end of incorrect personalization. Have you ever let someone use your Amazon account and afterwards received endless targeted recommendations for products you’re not interested in? If your personalization efforts aren’t 100% right, then they’re 100% wrong. That’s why personalization is extremely difficult to get right, so the key is to figure out how much you can get right and how much value it adds.

Above all else, be curious and investigate the “why.” Sure, personalization on its own is valuable, but taking these insights a step further is even more useful. Why do seniors have the preferences they do? Who else shares the same preferences, and what other commonalities do they have? How can I use this knowledge to improve the overall customer experience? Thinking critically about the “why” will help you evolve over time and stay agile in a constantly changing marketplace.

Reach new heights by engaging senior consumers

While many technology companies look to younger generations to fuel consumer growth, I urge you not to forget about our older adults and those soon to enter that demographic. This rapidly expanding group may be difficult to appeal to, but it pays back in dividends when done well. 

With personalization that’s powered by high-quality data, deep learning capabilities and human expertise, businesses can successfully tap into the aging adult population. We’ve done it — now it’s time for more organizations to accept the challenge.

Seth Sternberg is CEO of Honor Technology.

DataDecisionMakers

Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

You might even consider contributing an article of your own!

Read More From DataDecisionMakers



Source link

Leave a Comment