Every so often there’s some blowback about the value of customer data technology from analysts who question the economic benefit. The “less is more” calculation holds that developing a unified customer profile to ultimately deliver personalized experiences is a flight of fancy, based on some marketers claiming that the more data they collect, the less benefit they see. A Gartner Marketing Symposium helped perpetuate the narrative by pushing back on the value of “customer obsession,” hinting that a Customer 360 is unattainable.
But that cost to benefit analysis minimizes the overall financial benefits of data-driven personalization. In addition, the ROI calculation is based on the activity of collecting data, not on the customer data technology itself. That is, there is no accounting for what the customer data technology does with the data.
Enterprise-grade customer data technology that makes customer data ready for business use – a solution that puts the “D” in a customer data platform (CDP) or any other related application – makes the collection of customer data and creation of a unified profile a competitive differentiator. A high ROI is measured through more loyal customers, greater lifetime value, higher average spend, less churn and other success metrics calculated from having more satisfied customers. All while decreasing costs through improved productivity of CX, marketing, IT and data staff, improving customer outcomes, lowering overall customer interaction costs and reducing technology stack costs.
A differentiated customer experience has never been about merely collecting data and connecting data points. It is about data readiness, fully preparing customer data for any CX or business use case.
Everyone can agree that collecting data with the thought that volume alone will provide more insight about your customers is neither smart nor efficient. A differentiated customer experience has never been about merely collecting data and connecting data points. It is about data readiness, fully preparing customer data for any CX or business use case.
Data Readiness and Trust
Clearly data is not ready for use in many cases, as evidenced by 87 percent of marketers making the claim that data is their most underutilized asset (See Figure 1). One way to tell if customer data technology prioritizes data readiness is whether marketers and business users trust the data. When a CDP focuses on data quality from ingestion through activation, a marketer or business user is confident that the customer, household or business entity they interact with is the right customer.
Figure 1: A lack of data quality and completeness is the biggest challenge to data-driven marketing, according to an Invesp survey.
Moreover, a hyper-focus on data quality does more than let a marketer recognize a specific customer, it provides a deep, contextual understanding of a customer and a customer’s omnichannel journey. This knowledge translates to consistently relevant experiences that align with a customer’s journey as it progresses, across all channels inbound and outbound.
This data quality issue is key, as 54 percent of marketers said the lack of data quality and completeness is the biggest challenge to data-driven CX. Giving data quality the utmost care and attention as soon as data is ingested is vital for interacting with a customer in the cadence of a customer journey, up to and including real time.
Data readiness unlocks the full potential of a unified customer profile; it is the key to recognition, to relevance and real time, the main ingredients in being able to profitably differentiate one customer from another.
Data readiness is a core customer data technology capability. The line between winning and losing in the experience economy will come down to the skillful application of data, and the better the customer understanding, the better the experience.
Reverse ETL is NOT Data Readiness
There are many reasons why data may not be ready for business use. Some ways in which customer data technology falls short include not updating data sources. Perhaps data is ingested in real time, but some of the primary data sources are on a nightly batch feed. Data readiness implies that all data reflects the absolute latest understanding of a customer, household or business entity.
Inferior identity resolution, i.e., basic matching, is another key roadblock preventing data from being ready for business use. Some technology that touts reverse ETL capabilities may claim to perform identity resolution, but really only perform a basic match of first-party data against a reference file that is gathered by a third-party organization and enhanced in some way. But this is incongruent with developing a deep customer understanding. Infrequent updates to a reference file mean that an ensuing match does not reflect the dynamic, real-time nature of a customer journey, resulting in a loss of trust in the accuracy and validity of a customer record.
Inferior or incomplete data quality processes impact everything that depends on having a complete understanding of the customer, including segmentation. Automated segmentation using a rules-based approach will update an audience based on any data change, i.e., a new purchase, a browsing session, a new email address, etc. To generate an audience that accurately reflects the latest customer understanding, it is critical that data quality processes are completed upstream.
Data Readiness Unlocks Innovation
Data quality is a foundational requirement to scale CX use cases, giving marketers and business users the ability to create and execute innovative experiences at scale without having to worry about the trustworthiness of customer data.
When it comes to providing a superlative customer experience, there are no small problems. The wrong email address, a mis-spelled name, a late response to an abandoned shopping cart, a misunderstanding of household dynamics – all are avoidable, and all have the potential to create friction in a customer journey.
By prioritizing data readiness, brands avoid the cost of bad data, e.g., fewer conversions and cross-sell opportunities, more attrition, etc. In addition to avoiding bad outcomes, having data ready for business use also ensures that the customer receiving a next best action is more likely to progress on the customer journey. The customer buys the product, signs up for the loyalty program, schedules the appointment. It’s one thing to send the right email to the right customer which obviously avoids creating friction, but consistently getting that right also leaves open the possibility of the customer taking the desired follow-up action, advancing the customer journey in a way that benefits both the customer and the brand.
Data Readiness: The Cornerstone of Success with Customer Data Technology
In a recent Gartner marketing technology survey, 67 percent of respondents said they had onboarded a CDP, yet of those only 17 percent reported “high utilization.” Some of this disparity can be chalked up to a lack of data readiness; if the CDP does not make data ready for business use, then users must rely on other applications to cleanse the data and make it ready for segmentation and activation. But this is untenable when customers expect a brand to instantly recognize who they are and deliver a personalized, omnichannel CX.
In contrast to most CDPs, enterprise customer data technology embraces data readiness as a core tenet, going beyond what a CDP typically does to liberate customer data across the enterprise. Composed of a customer data refinery, customer data activation, and customer data management throughout with built-in AI, a customer data hub turns raw, fragmented data into actionable insights that drive personalized, impactful customer experiences. Redpoint is built on this principle, delivering enterprise-grade data quality and real-time updates that provide a unified customer profile marketers and business users can trust.
As Gartner’s survey highlights, many organizations struggle to realize the full value of their CDP investment due to incomplete or untrustworthy data. Redpoint’s focus on data readiness ensures that every piece of customer data is prepared for immediate business use, eliminating the need for additional applications or manual interventions. This unlocks innovation at scale, enabling marketers to deliver seamless, relevant, and timely experiences across every touchpoint.
By prioritizing data readiness, Redpoint empowers brands to achieve higher ROI, improve customer loyalty, and differentiate themselves in competitive markets. The result? Not just better data, but better business outcomes – proof data readiness isn’t just a feature; it’s the foundation of exceptional customer engagement.
