Monetizing Data From the Digital Customer Journey
Today’s consumers interact with brands in a digitally fragmented omnichannel world. The pervasiveness of smartphones and tablets, for example, means these vital customer interactions occur anywhere and anytime — and data from the digital customer journey often are not collected in a consistent or uniform way. Monetizing data from that fragmented digital customer journey is essential to identifying new revenue streams.
Within this splintered world, innovative mobile, social and artificial intelligence systems empower brands to deliver always-on touch points that improve the customer journey. Brands now capture each customer engagement with sophisticated, but disparate, customer segmentation technologies that measure data in real time and provide a detailed mosaic of his or her lifestyle.
Since data is now the new currency, businesses that invest wisely in consolidating their fragmented customer data will gain a competitive advantage. Data management platforms (DMP) have emerged as tools for centralizing customer data and enabling businesses to monetize the information now buried in their databases.
These tools are purposely built for analytics-driven decision-making, to drive more effective marketing. Specifically, DMPs enable customer segmentation (the ability to identify customer groups), campaign management (customer targeting), an optimized marketing mix, and insights about offline marketing (advertising). These precise customer profiles are used in precision marketing to deliver highly relevant, timely, and personalized advertising and marketing messages across channels, delivered when the customer is most likely to engage or convert.
Customer Data Is Ubiquitous and Comes in Many Forms
Most businesses know they have tremendous amounts of customer data, but in addition to lacking the ability to unlock its inherent value, they don’t understand that while relationships with partners such as Facebook, Google, and Amazon can be beneficial, they can also add to their data fragmentation challenges. Traditionally, three types of data exist, each with its own value:
- First-party data is captured over the course of a direct relationship with a customer and is the most valuable of the three to a business.
- Second-party data is obtained through a direct relationship with a noncompetitive brand partner, such as Google. This is essentially someone else’s first-party data shared in an aggregated and anonymized format.
- Third-party data is off-the-shelf data that can be purchased from data aggregators such as credit agencies.
To develop a comprehensive view of the customer, a business must look at all three data types and combine them into a unified customer profile.
Besides these traditional data types, deterministic data has recently emerged as a highly accurate customer data methodology. Deterministic data, unlike the other types that are locked in silos, identifies a single user across silos, devices (tablet, desktop, and mobile) and environments (Web browser and apps) to make the customer experience frictionless.
The average business has yet to invest in capturing deterministic data; however, Google, Facebook and Amazon are rapidly consolidating their data control by owning the data and locking it within their “walled gardens.”
As Facebook and Google continue to expand their data reach and control, marketers are beginning to realize this data lives within the technology giants’ walled gardens and cannot be taken outside these platforms. Once in a garden, it becomes another data point in Facebook’s or Google’s massive customer database. With the growing dominance of these technology giants, businesses must take ownership of their data and carefully manage how and where it is used.
The benefits of robust customer data are significant, but few brands in the retail and consumer space excel in exploiting it. The explosion of new data-driven capabilities (including marketing and advertising technology) and the demand for first-party customer data offer businesses an opportunity for gaining a new competitive advantage — if they can figure out how to monetize all the data fragmented among their multiple databases, technologies, and platforms. The difficulty of this task continues to increase as the growth in devices, touch points, and tracking generates more and more data.
The solution begins with understanding that traditional CRM (customer relationship management) systems and data-rich but insight-poor businesses, such as retailers and consumer packaged goods companies, have a limited ability to provide a comprehensive customer experience and cannot build a complete view of the customer.
To develop these capabilities, businesses need to control their customer data and build the technology infrastructure that will enable them to consolidate it into a single environment. A central data repository is the first building block in generating customer insights and ultimately monetizing data and identifying potential new revenue streams.
Consumer insights from a DMP can be integrated with other analytics, planning tools, and processes to develop a bottom-up view into consumer buying trends and market-basket analyses. Companies that have already begun to deploy these new functions and technologies are seeing many benefits, including marketing return on investment (ROI) improvements of between 20 and 40 percent, doubling of email marketing effectiveness, and double-digit marketing spend improvements.
When companies consider embarking on new digital initiatives to keep up with customer expectations, they need to address five categories of questions:
- Digital touch points. Are we capturing content along every touch point of the customer journey? Do we have a strong social presence? Does our website offer a personalized shopping experience?
- In-store touch points. Is the store integrated with m-commerce and e-commerce? Is the shopping experience frictionless? Are we effective at exchanges and returns?
- Customer care. Should we move interactions from transactional to conversational? How have we integrated CRM in stores and online? How can we use chatbots to better serve our customers?
- Data and analytics. Can we use artificial intelligence to predict customer needs? Can we use customer data for marketing and personalized experiences?
- Tools and technology. Will our customers find value in the new technology? Have we considered the depth and complexity of our technology infrastructure? Do we build our technology infrastructure in-house or outsource it to a third party to manage it?
Every customer touchpoint as an opportunity to strengthen the brand relationship and meet customer expectations. The more accurately and consistently a company delivers relevant goods and services, the more likely the customer will trust the brand and have the confidence to return for additional purchases and, perhaps more importantly, to share personal information.
Innovation Is Not Standing Still
Futurists see a digital world where the pantry, closet, and car are all aware and make purchases on the consumer’s behalf. This vision is fast becoming a reality. Taking the consumer out of the equation by letting devices do the shopping is already happening with the Amazon Echo and Google Home. In addition, the in-store experience is evolving from transactional to experiential, and expectations for a high degree of personalization are becoming the norm.
As the consumer experience evolves and more connected consumer-facing devices emerge, consumer data will grow in depth and breadth. This growth offers a significant opportunity for businesses willing to invest in the technologies and processes required to capture, store, and monetize the data. Giving business users easy access to consolidated customer data and transforming it into practical insights will be vital for creating compelling personalized experiences, improving the customer experience, and optimizing marketing.
Isaac Krakovsky is a partner within A.T. Kearney’s Consumer Products and Retail Practice. Isaac works with his clients to deliver large technology transformations, digital and technology strategy initiatives, and due diligence and post-merger integration projects. His expertise includes retail business processes, leveraging technology to drive performance improvement, project and change management. He is based out of A.T. Kearney’s New York office.