Hyper-personalization is often considered to be the ultimate ambition for brands and businesses. However, providing extraordinary levels of personalization to each individual as they interact with marketing, retail, or in the wider realms of customer experience, assumes a level of prior knowledge that is extremely challenging to achieve, even with today’s big data capabilities. A powerful alternative, mass personalization, or mass customization as it’s also commonly known, is a more achievable strategy that brings its own rewards. What sets these two similar-sounding concepts apart?
Let’s start with hyper-personalization. Go back a hundred years and imagine being a fly on the wall in the village stores. The local storekeepers would probably greet everyone in the village by name. They would know where they lived, their family history, their station in life. A customer coming through the door might see the storekeeper readying their regular purchases before they’d even got as far as the counter. Once there, the storekeeper might ask after a new baby or aging relative and suggest appropriate goods. It wouldn’t have been considered anything other than normal at the time, but this intimate relationship exemplifies hyper-personalization: deep knowledge, built up gradually, with an awareness of their customer’s situation and likely state of mind and able to anticipate the right solutions.
In today’s digital world, a new kind of hyper-personalization has become possible and is already in use by industry giants like Amazon, Netflix and Starbucks to provide unique experiences at scale. They are leveraging artificial intelligence, algorithms and real-time data to provide highly relevant, curated content or communications that anticipate the needs of every individual user at the perfect moment for them.
Product recommendations are most common – for example, Netflix employs machine learning to create unique show recommendations for every user. For their hit series Stranger Things, the company designed multiple thumbnails to appeal to different users based on their likes and dislikes, highlighting different aspects of the show from specific actors to horror and sci-fi, children’s adventure, even romance1. Starbucks utilizes data from their long-running loyalty app to send their customers emails featuring individualized offers, based on their previous buying behavior and known preferences2. Customers are happy to share data, knowing that it means they will receive offers that resonate with their needs.
But the truth is that hyper-personalization is still an extraordinary challenge. In a metaverse, almost everything is virtual, making it possible for people to use multiple log-ins, or alternatively share a log-in with several members of the family. This presents a problem for any AI or machine learning-based engine: who is the person interacting and what exactly are they looking for? Netflix asks people to self-identify when they arrive on the site, but it may not always solve the issue.
Hyper-personalization can also run the risk of seeming like a ‘blunt instrument’ if used without subtlety or high-quality data. Levels of sophistication are growing but it will take time before all brands and businesses can anticipate needs in a way that feels like beautiful serendipity, rather than sometimes coming across as intrusive or ‘creepy’. But it’s not the only method of delivering targeted, individualized goods and services that make people feel special.
For many years, consumer brands sold their products via resellers. The brands focused on what was core to them: innovation and manufacturing good products. As they relied on the retailers to sell their merchandise to consumers via stores, brands did not gather data on the consumers, their retailers did. With the ubiquitous reach of the Internet, brands can now access consumers directly, a strategy referred to as D2C or Direct to Consumer. But what if they do not know enough about these consumers to give them a personalized experience in the first instance?
Enter mass customization. This is another way to cater to the growing demand for focus on individual needs. Thinking back to our local storekeeper, the advent of the industrial revolution meant that the old-fashioned hyper-personalized approach largely dwindled in favor of chain stores and the mass-produced goods which have dominated the marketplace for more than a century. Now there are new ways to combine mass production’s economies of scale with digital technologies that allow individual customers to make a number of choices about their goods or services which are then designed to order. By orchestrating modular designs, online configurators, 3D scanners and flexible production systems everything from eyewear to houses can be customized, and though customers are often charged a premium for the service to make it viable financially, they’re happy to do so3. It’s a powerful response to the increased desire for personalization, for people to feel that their products have been made especially for them.
For Dell the ability to customize desktop models has been fundamental to its strategy since it was founded in the 1980s, allowing customers to choose the appropriate processor, memory capability and screen type for their particular needs and budget4. In the automotive industry, mass customization has been the norm for some years, with customers able to make a number of decisions – engine, gearbox, style package, paint color – in order to configure their perfect model. In 1999 Nike made it possible to customize their sneakers, and many customers have been only too delighted to pay a premium for doing so, given the kudos that their unique new footwear brought them5.
In comparison to hyper-personalization, mass customization creates its own benefits. A business may know nothing about the potential customer who has landed on their site, but as the customer interacts with their product offering, they will gradually learn more and more. Best of all it won’t feel intrusive, or like an off-putting ‘data grab’; instead, it’s part of a natural process towards giving the customer exactly what they want. Moreover, for existing brands, mass customization offers an opportunity for a revenue stream with increased profits, selling direct to the consumer, without the additional costs retailer and wholesaler relationships entail.
Take OREO for example. Owned by multinational Mondelez, this iconic brand sells ‘the world’s top selling cookie’ through wholesalers and retailers, the result being that they had a limited direct relationship with their customers. BORN worked with them to create a new flagship digital experience, OREOiD. On the website www.oreo.com, users are empowered to customize their OREO cookies, designing their own unique, authentic cookies that can be boxed and sent as gifts. They can choose different flavors, dips and colored sprinkles, even add photos and messages.
The site won four Webby awards and is now widely admired. The experience on the site is not just a delight for the user, who can enjoy the playful, process of interacting with the brand alongside treating a loved one or celebrating a special occasion with their gift. It’s also incredibly useful for the brand in their bid to develop a holistic view of their customers. When a user decides to go ahead with their purchase, they will necessarily need to submit practical details like their name, physical address and email address, what we might call ‘longitudes’, and they will be happy to do so. But they will also reveal their emotional sensibilities and relationships, their ‘latitudes’. For instance, we might learn that they like celebrating birthdays, that they have a sister whose favourite color is purple and lives in Chicago. Or that they work for a corporation who regularly have events for a large number of people and whose brand colors are red and white. Through playful interactions OREO can be privy to a whole sphere of information created almost effortlessly from the customization journey.
Not only did OREO enjoy record sales from their new venture, in addition they are gathering the building blocks for hyper-personalization, in the form of customer information, should they desire to go down that route in the future.
Of course, people may behave differently on a website from how they do in a store, or on the phone to a call center. By adding in details gained from interactions in other channels to the data gathered from mass customization, brands can build their view of each individual customer until it gradually come into sharper and sharper focus.
Whichever route they choose to go down, the potential rewards for companies who can successfully implement hyper-personalization or mass customization are great. Furthermore, while businesses are boosting sales by providing highly relevant product recommendations or creating new revenue and data streams by empowering users to customize their products, consumers are winning too. They’re happy to pay a premium to gain access to the targeted and customized experiences that they desire, and still finding added value.
For more information on BORN’s work with OREO, please visit here.
- 3 Examples Of Hyper Personalized Marketing Campaigns, Wedia, https://www.wedia-group.com/brand-content/3-examples-of-hyper-personalized-marketing-campaigns/
- Why Hyper-Personalization Is The Future Of Marketing (And How To Do It), WebEngage, https://webengage.com/blog/hyper-personalization-marketing-future/
- How Technology Can Drive The Next Wave Of Mass Customization, McKinsey & Company, https://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/bto/pdf/mobt32_02-09_masscustom_r4.ashx
- 3 Success Stories Of Mass Customization, TopMostBlog, https://www.topmostblog.com/3-success-stories-of-mass-customization/
- Nike’s Online Customers Can Step Into Designer’s Shoes, Los Angeles Times, https://www.latimes.com/archives/la-xpm-1999-nov-23-fi-36665-story.html