Let’s (not) get (too) physical, physical • 3
While the shift from products to services – often referred to as servitization – is far from new, it remains a powerful framework for manufacturing companies and digital-first startups looking to embrace customer-centric, service-dominant business models. In this blog post, I explore the Individualization Over Standardization strategy, one of seven ways to think services instead of products.
3. Individualization > Standardisation
The Individualization Over Standardization strategy is about tailoring content, products, services, and experiences to meet the unique needs of individuals, groups, and organizations. This approach recognizes varying levels of customer engagement, ranging from high-effort, hands-on participation to low-effort, consent-driven interaction. (Based on Bau, 2006, 2010, 2011, 2015; Wirtz & Lovelock, 2016.)
Note: The varying levels of engagement align well with Grönroos’ distinction between enabling and relieving services. Enabling services support customers by providing them with the necessary resources, tools, or knowledge, or resources to perform tasks independently. Relieving services take over tasks on behalf of the customer, thereby reducing their workload and responsibility. (Grönroos, 1990)
This blog post explores five overlapping schools of thought in individualization:
From passive consumption to active participation
From one-to-many to one-to-one marketing
From mass production to mass customization
From point-of-purchase to post-purchase customization
From rule-based to real-time personalization
Note: Unlike a product-centric approach that often treats services as an afterthought, a genuine service design mindset integrates product-service systems, value co-creation, platform thinking, end-to-end experiences, and a multi-actor perspective into the conversation on individualization.
From passive consumption to active participation
Rooted in the concept of value co-creation, active participation means engaging B2C and B2B customers in the creation, production, and delivery processes as co-researchers, co-innovators, co-designers, co-producers, and co-marketers.
Organizations employ strategies like co-creation, participatory design, crowdsourcing, and open design (to name just a few) to facilitate this level of participation and engagement. Customers are no longer treated as passive recipients but embraced as active collaborators or prosumers. Value is no longer embedded in static products but realized through dynamic customer-provider interactions. See my blog post Get the balance right! • 2 for a deeper dive into this topic.
The implications are twofold. First, organizations need to design systems, platforms, services, and processes that enable customers to realize value within their specific contexts. Second, traditional creators – such as innovators, designers, engineers, and developers – must evolve into platform builders, curators, coaches, and facilitators to inspire and empower active participation.
When customers contribute their time, effort, and expertise, they invest emotionally in both the process and outcome, fostering a sense of ownership and personal accomplishment. They may also gain tangible benefits, such as cost savings, performance improvements, financial rewards, or exclusive access.
(Toffler, 1980; Grönroos, 1990, 2011; Gummesson, 1999; Prahalad & Ramaswamy, 2004; van Abel et al., 2011)
Examples: IKEA enables customers to collect, transport, and assemble furniture themselves, combining flat-pack design with self-service to make home furnishing more affordable and accessible (1956–present). Build-A-Bear Workshop empowers parents and children to create personalised stuffed animals together, making the process fun and memorable (1997–present). MyStarbucks Idea crowdsourced suggestions for new products, store experiences, and community engagement models (2008–2018). LEGO Ideas (formerly LEGO CUUSOO) invites fans to co-create new LEGO sets through collaborative submissions and voting (2008–present). GE Aviation’s TrueChoice™ suite offers tailored maintenance and operational solutions designed to meet the unique needs of aviation clients (2016–present). SAP’s Co-Innovation Labs (COIL) facilitate collaboration between SAP, customers, technology providers, and startups to co-develop customized solutions for specific industry challenges (2007–present).
From 1:many to 1:1 marketing
One-to-one marketing centres on building personalised, long-term relationships with individual customers by (a) learning their unique preferences and needs through each interaction, and (b) continuously tailoring offerings to their evolving expectations (Peppers & Rogers, 1993; Pine, Peppers & Rogers, 1995).
1:1 marketing involves four critical steps (slightly adapted from Peppers & Rogers, 1993):
Identify: Understand who your customers are by gathering detailed insights into their preferences, behaviours, and needs. Create a living profile for each customer – a memory that grows and evolves with every interaction – ensuring a deeper understanding of their unique journey over time.
Differentiate: Segment customers based on their lifetime value, profitability, and specific needs. Prioritize high-value customers and identify underserved groups to focus resources strategically.
Interact: Develop meaningful, personalised, and cost-efficient interactions across channels (e.g., email, social media, or in-person). Treat each interaction as a learning opportunity to identify customer preferences, uncover unmet needs, and predict future behaviours.
Customize: Use the knowledge gained to tailor content, products, services, and experiences to meet the specific needs of individual customers, ensuring relevance and fostering loyalty.
Technology plays a pivotal role – not only in collecting and analysing customer data to enable personalisation at scale but also in facilitating meaningful, tailored interactions that foster deeper customer engagement.
Examples: Amazon leverages its recommendation engine to offer tailored product suggestions and promotions based on individual browsing history, purchasing behaviour, and preferences (1995–present). Stitch Fix combines human stylists with AI to deliver curated clothing selections, learning from customer feedback to refine future recommendations and deepen personalization (2011–present). Spotify uses machine learning to generate personalized playlists like ‘Discover Weekly’ and ‘Release Radar,’ adapting dynamically to user listening habits and introducing new music tailored to their tastes (2008–present).
From mass production to mass customization
Mass customization offers a scalable approach to addressing individual customer needs by blending the cost efficiency of mass production with the flexibility of bespoke solutions. This is achieved through customer insight (identifying segment needs and sacrifice gaps), unbundling (breaking products, processes, and experiences into configurable components), modular design (designing standardized components and platforms), operational flexibility (leveraging advanced manufacturing and JIT inventory), customer integration (utilizing configurators, algorithms, predictive analytics, recommendation engines, and feedback loops), and human intervention (providing curation, coaching, and creative problem-solving). (Based on Pine, 1993; Pine, Peppers & Rogers, 1995; Normann, 2001.)
The four faces of mass customization (Gilmore & Pine, 1997):
Collaborative customizers conduct a dialogue with individual customers to help them articulate their needs and make customized solutions that fulfill those needs.
Examples: Paris Miki’s Mikissimes Design System engages customers in a dialogue to create personalized eyewear tailored to their specific needs (1994–present). Nike By You (formerly NIKEiD) enables customers to design customizable footwear tailored to their preferences (1999–present).
Adaptive customizers offer standardized solutions that are modifiable by customers post-purchase for different purposes or occasions.
Examples: Lutron’s programmable lighting systems allow customers to modify lighting settings for different purposes or occasions (2010–present). Tesla offers over-the-air, pay-to-unlock upgrades that provide access to additional features and functionality post-purchase (2012–present). WikiHouse provides open-source architectural designs and resources, enabling individuals and communities to construct sustainable, low-cost housing customized to their needs (2011–present).
Cosmetic customizers present standard solutions differently to different customers.
Examples: Coca-Cola’s ‘Share a Coke’ campaign replaces its iconic logo on bottles with personalized names, adding a personal touch while maintaining brand recognition (2011–present). Glossier’s skincare products come with sticker sheets, allowing customers to personalize the packaging (2014–present).
Transparent customizers make adjustments for individual customers without their explicit involvement or approval.
Examples: Hoteliers tailor room experiences for high-value, repeat customers by adjusting pillow types, pre-setting room temperatures, or adding fresh flowers upon arrival. Retailers adjust store layouts and feature locally sourced products to reflect regional preferences and seasonal demand.
Technology plays an integral role in enhancing the efficiency, efficacy, and scalability of mass customization – for example, by dynamically suggesting customized products or configurations based on customer behaviours, preferences, and real-time interactions.
From point-of-purchase to post-purchase customization
Post-purchase customization involves customers and communities modifying or personalizing solutions after purchase to better suit their needs – often in ways not originally intended by the manufacturer or service provider. Depending on the context, it may also be referred to as user innovation, product hacking, or post-purchase personalization (see, e.g., von Hippel, 2005).
Some companies resist post-purchase customization, citing concerns over intellectual property, brand integrity, or product safety; others support and embrace it by providing inspiration, DIY guides, tools, templates, interchangeable components, and digital upgrades.
Examples: IKEA Hackers is a community where enthusiasts share ideas for modifying and repurposing IKEA furniture into custom configurations (2006–present). Bethesda Softworks empowers players to customize and expand games like Skyrim and Fallout through its Creation Kit, fostering a vibrant modding community and extending game lifecycles (2011–present). GoPro supports user-led innovation through modular accessories and a community where customers create and share customized camera setups for unique filming needs (2004–present). Casio G-Shock owners personalize their watches by swapping out straps, bezels, and faceplates to create bold, customized designs, with third-party sellers and DIY enthusiasts fueling the market for custom components (2019–present).
From rule-based to real-time personalization (a.k.a. hyper-personalization)
Powered by AI-driven systems, hyper-personalization delivers highly relevant, context-aware offerings, interactions, and experiences that adapt in real time to individual behaviours, contextual needs, and environmental factors. It achieves this by analyzing structured data (e.g., demographics, purchase history, location, time of day, weather conditions) and unstructured data (e.g., browsing patterns, social media activity, sensor data, emotional cues) both historically and in the moment. (Based on Hayes & Downie, n.d.; Jaffery, n.d.; Rusiñol, 2023.)
True personalization delivers on five implicit promises that shape customers’ expectations (slightly adapted from Abraham & Edelman, 2024):
Empower me. Provide intuitive tools and experiences that simplify tasks, support decision-making, and help me achieve my goals.
Know me. Leverage contextual, real-time data to understand my preferences, behaviours, and intent in the moment.
Reach me. Optimize communications by delivering the right message, through the right channel, at the right time.
Show me. Deliver tailored content and recommendations that align with my interests, needs, and preferences.
Delight me. Anticipate my needs and exceed expectations with unexpected, value-added solutions or experiences.
Advanced AI capabilities – such as predictive analytics, natural language processing, conversational AI, and recommendation algorithms – drive the precision, adaptiveness, and responsiveness of hyper-personalization (Hayes & Downie, n.d.; Jaffery, n.d.; Rusiñol, 2023).
Examples:
Peloton leverages real-time data and AI to deliver adaptive fitness experiences that evolve dynamically based on user performance, preferences, and feedback (2012–present). To illustrate: After a high-intensity interval session, Peloton uses wearable data and user activity to recommend recovery rides and adjust future workouts for optimal performance and recovery.
BMW integrates AI-powered features within its iDrive system to personalise in-car experiences based on driver habits, preferences, and real-time contextual factors (2018–present). To illustrate: Upon entry, iDrive adjusts seat position, climate, and lighting automatically, while dynamically suggesting alternate routes or activating rain-adaptive settings based on live traffic and weather data.
Sephora employs AI to analyze customer preferences, past purchases, and skin tones to deliver hyper-personalized beauty experiences through its Virtual Artist app (2016–present). To illustrate: The app examines a user’s photo to recommend foundation shades matched to their complexion, and leverages purchase history and browsing behavior to suggest complementary products like setting powders or brushes.
Note: Hyper-personalization exemplifies low-effort, consent-driven engagement. Ethical considerations, transparent data practices, and explicit user consent are essential for avoiding biases, protecting user data, and building trust.
Benefits:
Aligns offerings and experiences with customer needs, preferences, and priorities, ensuring relevance, meaning, and value
Fosters emotional connection by making customers feel uniquely understood and valued
Reduces effort by streamlining decision-making and offering solutions that adapt to evolving needs
Optimizes resource allocation by using customer data to target the right solutions at the right time
Builds strong, lasting relationships that foster brand loyalty, enhance NPS, and increase CLV
Enhances customer advocacy by staging experiences that motivate customers to share with others
Strengthens competitive advantage (over companies using traditional segmentation)
Drives continuous innovation by leveraging customer data, feedback, and modifications
Encourages innovation in value creation, value co-creation, and value facilitation (see my blog post Get the balance right! • 2)
See also:
Access > Ownership
Solutions > Products
Connection > Isolation
Experiences > Transactions
The Experiences Over Transactions strategy will be covered in the next blog post.
References
Abraham, M., & Edelman, D. C. (2024, November–December). Personalization done right: The five dimensions to consider – and how AI can help. Harvard Business Review.
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Bau, R. (2010, December). Ten strategy paradoxes in service Innovation and design. Paper presented at ServDes 2010 (Service Design and Innovation Conference), Linköping, Sweden.
Bau, R. (2011, December). Strategy paradoxes in service innovation and design. In: Cai et al. (Eds.), Design Management: Toward a new era of innovation. Proceedings from the 2011 Tsinghua-DMI International Design Management Symposium, Hong Kong, China. IDMA.
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