Data has been called the “new oil” of our economies, or “a currency that customers and firms might use to trade off costs and benefits in their interactions.” Gathering valuable data from consumers can now be as important to a firm in beating out competitors as superior products and services. And with the rise of social media and widespread internet access, more consumer data is being generated than ever before.
At the same time, most consumers feel that firms collecting their personal data poses more risks than benefits and are wary of certain data-gathering techniques. For example, over 25% of consumers use technologies that block personalized ads on their devices. Thus, obtaining data in a way that consumers approve is a major challenge for retailers.
In their article “Insight is power: Understanding the terms of the consumer-firm data exchange,” Manfred Krafft, V. Kumar, Colleen Harmeling, Siddarth Singh, Ting Zhu, Jialie Chen, Tom Duncan, Whitney Fortin and Erin Moody explore the factors that influence these data exchanges between firms and consumers. The authors (1) identify the ways consumers share data with firms and how they affect consumer expectations, (2) examine how consumers’ evaluations of the terms of data exchange affect their perception of retailers, (3) identify factors that increase a retailer’s ability to gain a competitive advantage from the data they gather, and (4) identify conditions that amplify a firm’s risk of violating the terms of customer data exchange.
The Customer-firm Data Exchange
The authors identify three primary ways consumer data is disclosed: retailer-requested, customer-initiated, and passive data disclosure.
Retailer-requested Data Disclosure
The primary way consumer data is exchanged is by retailers directly requesting it from consumers. Firms often use incentives to get consumers to disclose this data, such as monetary payment or exclusive access to products. However, these incentivized responses may be less informative than responses from consumers who are truly invested in the firm. Instead, offering personally relevant content to consumers, such as personalized ads, has been shown to increase consumer willingness to disclose valuable information.
Consumer-initiated Data Disclosure
Consumers also disclose their personal information and product use to retailers voluntarily. With the emergence of social media, the volume of this volunteered data has increased significantly. Sites like and Facebook and Twitter have enabled visibility to data such as likes, shares, and comments, all of which can provide valuable information to retailers on where they stand against competitors and how their products are performing. In turn, firms can improve their offerings, marketing strategies, and customer-targeting strategies.
Passive Date Disclosure
Lots of consumer data is also collected passively as a result of consumers’ interactions with a retailer, oftentimes without consumers’ knowledge. This includes data on consumer searches, clicks and page views, which can be used to create predictive models and enhance the customer experience. For example, by tracking consumers’ online browsing behavior, retailers can tailor website content to that user.
Consumer Expectations of the Terms of Data Exchange
“In all types of data disclosures, consumers form expectations regarding the nature of the data collected and evaluate these expectations based on how it is used by the company.” Each method of data disclosure produces different consumer expectations along four dimensions: data ownership, data intimacy, data permanence, and data value. Consumers then determine whether retailers are meeting these expectations in using their data, which in turn influences consumer evaluations.
Data Ownership Expectations
“Consumers have expectations of who ‘owns’ their personal information that reflect where they expect their personal data to be stored and who they anticipate using it.” While ownership is explicitly stated in firm-requested data disclosure, the content that consumers create through consumer-initiated content (e.g., likes, comments) is typically meant for someone else, not the firm. As such, consumers may not expect the retailer to have “rights” to this personal information. It is therefore important for retailers to adequately disclose how they collect consumer data. Openly informing consumers of the data collection process makes consumers perceive personalized content as more useful, and customers are more likely to reject personalized ads when not informed that their data is being collected.
Data Intimacy Expectations
Consumers also develop expectations of the depth and detail of the data retailers have of them. In retailer-requested data disclosures, consumers have control over what information they share with retailers. In consumer-initiated data disclosures, consumers may disclose sensitive information about themselves on social media. However, their privacy expectations are often based on the intended audience for what they’re sharing, (e.g., their followers) rather than the platform they’re using. This “privacy paradox,” where consumers express concern about potential misuse of their data yet continue share highly sensitive information on social media, is a growing concern for consumers, firms, and governments.
Data Permanence Expectations
How long collected data lasts affects consumer evaluations as well. Data that is disclosed by the consumer may be seen as lasting only until the consumer retracts it from the public sphere (e.g., social media posts). Consumers may react negatively if their data is being kept longer than expected, and many companies have responded with policies that better align with consumer expectations. For example, Telegram allows users to delete messages at any time, giving them full control over the permanence of their data.
Data Value Expectations
Customer willingness to disclose data is also based on an expectation that their data has economic value that can better their user experience. For example, consumers believe their data should be used to enhance the information displayed on a retailer’s website, reducing their search efforts. Consumers may also expect retailers to provide free services or access to restricted information in exchange for their online browsing data.
What Happens When Firms Do (And Don’t) Meet Consumers’ Expectations
When done properly, firms can use data exchanges to enhance the consumer experience. For example, effectively customizing consumers’ social media feeds based on their interests can motivate customers to provide additional information to the firm, signaling that consumer expectations of data ownership, intimacy, permanence and value were upheld. At the same time, because consumers are wary of how retailers gather and use their personal information, retailers that fail to meet consumers’ data exchange expectations can face detrimental outcomes such as defection, ill repute, or even legal action. For example, a Target data breach that compromised 40 million credit and debit cards led to a $292 million legal settlement for the company in 2016. Additionally, personalization technology used in public spaces, such as personal recommendations customers receive while shopping in-store, are often responded to negatively.
Factors Affecting a Retailer’s Ability to Gain a Competitive Advantage From Consumer Data
While collecting plenty of high-quality data is necessary for retailers, it doesn’t guarantee success. “To leverage the value of consumer data, companies rather need to develop and follow a systemic customer strategy,” allocating their skills and resources to acquire and maintain valuable customer relationships.
Factors Increasing Firm Data-leveraging and Resilience
First, firms must disseminate data within their own company so that insights can be understood and implemented. “Even the highest quality of consumer data and the most sophisticated marketing analytics tool would be of no value if the resulting insights are neither shared nor used.” Disseminating intelligence in a way that is understood and used within the organization remains a challenge for firms. As such, firms that are agile and can quickly share important data with the appropriate departments are mostly likely to benefit from their insights.
Retailers must also have strong analytical capabilities, separating the meaningful insights from the raw data they gather to achieve competitive advantages. “Customer relationship management technologies and big data analytics are major elements that help firms translate data into insights, firm action, and customer benefits.” These technologies combine data collected from multiple touchpoints with the consumer, providing a real-time view of the customer and helping firms improve their experience.
Firms also benefit from interfirm data collaboration. For example, Google and Facebook allow API logins on different websites, letting them link consumer data from sources outside of their own channels. “This benefits consumers through improved personalization, and fewer logins leading to a richer and more satisfying consumer experience.”
Factors Increasing Risks of Violating the (implied) Terms of Data Exchange
Firms can also unintentionally violate the implied terms of data exchange with consumers. Data breaches are an explicit violation of these terms and can have long-term consequences for retailers. Privacy governs consumer decisions, and privacy concerns have been shown to restrict customers’ clicking behaviors and their purchase intent.
Incentives being misaligned with consumers’ expectations of the value of their data can lead to detrimental outcomes. Customers are not necessarily more willing to grant permission to their data if they get incentivized, and even if they do, the incentives may encourage consumers to provide lots of data, but not necessarily a lot of high quality data.
Prolonged data storage can increase the likelihood that consumers feel their data permanence is being violated. “Firms storing and using data after this perceived expiration date will probably face less satisfied or loyal customers, who opt out earlier or spread bad word-of-mouth.”
Lastly, while consumer profiling can be beneficial, it can also trigger unease with consumers. “Highly precise consumer profiles often come from combining data from seemingly unrelated entities, and can lead to consumer misconceptions of how well a retailer knows the consumer.” For example, many consumers likely don’t know that Facebook owns WhatsApp and Instagram and can combine consumer data across these platforms to make detailed profiles. These profiles may violate consumer expectations of how well firms should know them, because they view each of these social media platforms, and the data they share on each of them, as separate.
“Data is power, given the advent and use of new technologies, especially in retailing.” This data manifests itself in many ways (firm-requested, consumer-initiated, passive), and each of these forms leads to varying consumer expectations of the data exchange (e.g., intimacy, permanence). If firms can extract valuable insights from their data, enhancing the consumer experience while also ensuring the terms of customer-firm data exchange aren’t violated, they can gain an increasingly valuable edge over the competition.