Using customer insight to innovate experiences, products, and services is simply good business. A whopping 88 percent of brand representatives polled agree that collaborating with their customers drives revenue, according to “The Power of Co-Creation” study by Bulbshare. But 77 percent of consumers polled for the study say that brands don’t listen to their feedback, ideas, and opinions.
There is a strong case that using a customer data platform (CDP) can help marketers drive revenue growth and improve operating margins, yet an even stronger case that CDPs are vital to achieving overall competitive advantage. CDPs enable marketers to get the customer insight they need to deliver relevant experiences and communications, which, in turn, makes customers feel listened to and appreciated. As a result, a CDP can help increase a company’s market value through customer-led innovation. It does so in three primary ways:
• Supporting breakthrough performance gains from machine learning and AI
• Increasing differentiation via unique, relevant customer experiences
• Launching lucrative new product and service offerings
Marketers and the martech professionals they work with can use a CDP to connect all data from across their company to enable the always-on, always-processing view of the customer they need to gain a unified and complete golden record — and make that data available to any application across the organization when needed.
Here’s how CDPs help you access and use that customer data to create breakthrough innovation: A robust CDP ingests all sources and types of customer data — batch and streaming, internal and external, structured and unstructured, transactional and demographic — and then provides an always-on, always-updating unified view of each customer. Because CDPs operate in real time, that golden record is continually available at low latency across all touchpoints and to all users at the customers’ moments of truth.
This immediate access to robust data lays the foundation for achieving performance gains from AI and machine learning, differentiating through customer experience, and launching new products and services.
Consider as examples of AI and machine learning innovations such tactics as advanced real-time personalization and next-best-action recommendations. These require machine learning to tap into real-time insights that become triggers for contextually relevant communications. This degree of relevance is only possible if it is derived from data that is complete, current, and accurate. The best part: It can now happen at scale. These on-target communications engage consumers who now feel listened to and valued, and as a result are more likely to buy more and more often. A relevant, high-impact recommendation is up to 50 times more likely to trigger a purchase than one that’s low impact, according to research from McKinsey.
These communications are one element of a uniquely personalized, innovative customer experience that spurs sales. A survey of U.S. internet users by consultancy Kelton Global and verification services firm SheerID found that two thirds of those polled say an offer specifically for them is more important than a promotion sent to everyone. And 78 percent of consumers say personally relevant content increases their purchase intent, according to a survey from Marketing Insider Group and OneSpot.
Additionally, using a CDP to track customers’ behavior and better understand their preferences can also help marketers ensure that communications, messaging, and offers are highly relevant. Plus, that insight will help uncover unmet needs that marketers can share with their company’s product teams to inform product development. If your company launches new products or services that address your customers’ unmet needs, those innovations will show customers that you’re listening to them and responding to even their unstated needs, which, in turn, further improves the customer experience and sales.
But none of this will happen without one essential element: high-quality, current customer data. Fortunately, CDPs produce and maintain complete, up-to-date customer records by pulling data from key systems across an organization.
That rich, clean, real-time data feeds AI and machine learning. Advanced algorithms require precise data to perform at optimal levels and deliver analyses that can lead to innovations in marketing, sales, service, and more. Conversely, poor data can stall innovation and reduce ROI. The average annual cost of poor data quality to large businesses is $15 million, according to Gartner’s Data Quality Market Survey.
As information increasingly becomes imbedded in products offered to consumers, CDPs provide limitless potential to fuel innovation. From loyalty programs offered through retailers, to IoT devices such as Amazon dash buttons that enable consumers to automatically reorder their favorite brands, to driver tracking data that enables insurers to offer unique policy discounts, products are increasingly infused with robust types of data. CDPs provide the single customer view required to enable these types of product extensions that yield new sources of revenue. IDC predicts that information-based products will become a significant source of revenue, based on its estimation that 180 zettabytes of data (or 180 trillion gigabytes) will be created across the globe in 2025.
Simply put, precise customer data drives better analytics results, which leads to better decision making and greater business performance. CDPs serve a broader role than maintaining data quality, they also bring data together from across an organization and help marketers know all that is knowable about their customers. In doing so, they help marketing and other customer-facing teams get the data they need to:
• Use AI and machine learning to drive innovation through more contextually relevant interactions,
• Deliver more engaging customer experiences across channels and interaction points at the speed of the customer, and
• Uncover unmet customer needs that could drive the launch of unique and profitable products and services.
Ultimately, when marketers use customer insight to drive innovation, everyone wins. Customers buy more when they feel understood and valued through distinctive experiences and interactions — leading to revenue growth for the companies that provide them.
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There are four primary ways marketers and martech professionals can use a CDP to drive immediate and long-term business value. One is innovation. The others are:
• Revenue lift – Increased revenue through improved customer experience
• Operational effectiveness and efficiency – Decreased costs through improved operations and customer understanding
• Risk avoidance – Decreased risk through a holistic view of data
We’ll cover these topics in upcoming posts.