How Customer Data Will Define Competitive Strategies

A new book explores ways companies can view and nurture revenue-generating digital customers.

By Beth Stackpole, MIT Sloan

As companies reimagine products and services for the digital world, customer data is the linchpin for creating fresh revenue streams and architecting new offerings.

To attract and retain a new breed of digital customer, retailers are rethinking strategic priorities and developing new marketing, revenue, and profit-generation business models. But the traditional constructs of competitive strategy don’t hold up when building business models around data and digital ecosystems, said Mohan Subramaniam, author of the new book, “ The Future of Competitive Strategy: Unleashing the Power of Data and Digital Ecosystems.”

In a recent webinar hosted by MIT Sloan Management Review, Subramaniam outlined a digital model for competition where revenue comes not from products, but from data; business is organized around digital platforms, not value chains; and offerings aren’t amplified and advanced by industry structures, but rather by digital ecosystems.

While this transformative approach has been embraced by digital titans like Amazon and Google, it isn’t exclusive to new-era companies, said Subramaniam, a professor at IMD Business School in Lausanne, Switzerland.

With the help of modern digital technologies like artificial intelligence, sensors, and the Internet of Things, legacy firms too can harness the power of data and digital ecosystems.

“This is the future of competitive strategy for a whole host of legacy firms,” said Subramaniam, “The question is how do they shift focus from products to data without losing their traditional strengths.”

The four tiers of digital transformation

Companies don’t just flip a switch between old-style business models to data and digital ecosystems. Rather, Subramaniam defined four levels of digital transformation that, based on business strategy, require different levels of digital consumer engagement. He offered these specific examples:

Level one — Ford leverages augmented and virtual reality data to inspect paint jobs in its assembly lines, replacing visual inspection with interactive data emanating from its plant floor assets. The process replaces the need for human workers and results in more efficient operations and improved product quality.

Source: Auto Service World

Level two — Caterpillar collects telematics and sensor data from construction equipment used by thousands of customers at different construction sites. The aggregated data reveals that a particular piece of equipment isn’t being used the way it was intended, creating opportunity to develop a new, potentially less expensive and higher-margin product that’s better suited to customer needs.

Level three — GE collects real-time interactive data from pilot interaction with jet engines, delivering insights to customers on how to optimize flight patterns for greater fuel efficiency. The company monetizes this service, creating an additional revenue stream.

Level four — Peloton collects data on how users interact with its machines and shares that data with external, third-party entities and different user communities. It also connects users to trainers and others for complementary services supporting new business models and revenue streams. The result is a fully digital ecosystem.

Common to each of these levels of digital transformation is the need for interactive data.

Companies have typically relied on what Subramaniam calls episodic data emanating from discrete events — for example, data specific to buying or selling a product or service — that is aggregated and analyzed after the fact. In comparison, interactive data from sensors and online behavior requires participation from willing digital customers.

He cited a smart inhaler as an example. Such an inhaler collects interactive data based on customer usage that could help determine how many doses are left or remind a patient to take their medication, enabling better health outcomes. More advanced features, enabled through data collection from third-party entities tracking allergens or pollution, could level up the benefit, alerting patients to a specific danger based on locale or air quality conditions.

How to nurture a data-driven customer

Subramaniam outlined several steps for attracting and retaining this new class of digital customers:

Recognize customers’ new role. Companies must expand their strategic mindset beyond using data to support products. In the new paradigm, products support data, which opens the door to new functionality and business models.

“Start thinking differently about customers,” Subramaniam said. “They aren’t just people who buy your products, but are people who give you very valuable data, and you have to treat them like that.”

Consider a robot vacuum that not only navigates where to clean, but also determines if there are mouse droppings or mold and directly connects the consumer to relevant mitigation services.

Develop new value propositions based on data. Like popular digital platforms, much depends on the network effects of data, where value increases as more consumers connect to the product and generate data. Since the promised value won’t surface until the proper data thresholds are met, companies must adjust communications, marketing, and business plans to convince customers of data-driven features before they exist.

The way to achieve this goal, Subramaniam said, is to sell outcomes, not products.

Nurture digital ecosystems that span both production and consumption. On the production side, organizations need to strategically identify entities within their traditional value chain networks that will generate and share data to advance new revenue streams or business models. On the consumption side, they must identify and partner with external entities that will participate in leveraging that data to deliver new services.

Create new revenue and profit-generating business models. Don’t think in terms of traditional value chain-based pricing models based on parameters like raw material costs or margins. Consider new models that monetize some users, but subsidize others depending on their value, Subramaniam advised.

As legacy companies navigate new terrain, they must consider competitive risks and their strategic reasons for being either an early mover or a follower. At the same time, it’s important to address privacy and security concerns while incenting users to want to share their data. Most important: recognize that digital customer data holds the key to success for each stage of a company’s digital future.

“Understand the full scope of value that modern digital technologies can offer and start thinking based on your current resources and business models,” Subramaniam said. “Know the full scope of what’s possible, and then chart out your journey.”

Originally published at https://mitsloan.mit.edu on September 21, 2022.

For an in-depth look at the digital revolution in marketing, read the Special Report from the MIT IDE CMO Summit, Marketing Tech Revs Up.

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