When your data is ready across the enterprise for any use case that drives business value – AI, personalized CX, customer acquisition, paid media – what will you do? Is there a “perfect world” vision for what your business can accomplish when you have full faith and confidence in the accuracy, completeness, and timeliness of your enterprise data?
Even if a finish line is not yet in sight, the potential rewards are alluring enough to have likely brought your business to the starting block. Research from McKinsey shows that data-driven brands are 19x more likely to be profitable and successful, stating that improved analysis through technology is the key to gaining deeper insights into customer behaviors and preferences, improving personalized experiences, and incorporating tactics that feed into a long-term personalization strategy for growth. And Gartner says that organizations with the most mature marketing technology functions will achieve 75 percent greater marketing ROI.
Mature technology that provides deeper insights into customers, households, and other entities of importance to the business is centered on getting data ready for business use. Cleansed, accurate, and fit-for-purpose data is the common denominator that underlines enterprise use cases for extracting value from data to drive business outcomes.
Of All Stripes: Data Readiness at a Use Case Level
But unlocking data-driven personalization through having data continually ready for business use is not a uniform exercise; a business’s use cases will largely determine the depth of understanding needed from the customer data and the capabilities required to actualize value.
Whatever the initial use cases may be, technology centered on data readiness enables companies to progress on a personalization maturity roadmap – and expand their use cases – because it takes care of the hard part first. It clears a path for advancing with personalization use cases by continually improving upon the veracity of enterprise data – making no assumptions that data will be cleansed and made ready for business use somewhere downstream, or by a third-party vendor.
Success Through Data Readiness Builds Off Itself
One Redpoint customer – a travel and leisure company – started its personalization journey with a goal to create a single data repository for 45 federated clubs constituting 55+ million North American customers for a straightforward use case.
“We asked ourselves ‘what’s the first business problem we can solve?’ It was: ‘How can we help our clubs get accurate, up-to-date member lists for mailing, without waiting for their IT teams to do it?’ ” said the company’s director of marketing.
Yet with Redpoint customer data technology solving that problem by cleansing, normalizing, matching and otherwise making the company’s data ready for business use, the company found that accurate member lists for mailing was just the tip of the iceberg.
“We can only do effective analyses and create successful offers because we have strong confidence in our data. Redpoint gives us that confidence,” the director said. “We can take practically any incoming data, understand its health and align it to a member, past member, even someone who’s not a member yet. … We used to have teams that did nothing but manage data all day, using multiple platforms. Redpoint gave us a platform we could leverage across all our people and clubs.”
Advancing on the Personalization Maturity Curve
Boston Consulting Group maps the five stages of data-drive personalization capabilities (see Figure 1) to potential revenue gains, starting with audience suppression for paid media (Level 1: Starting) through omnichannel and real-time personalized engagement (Level 5: Excelling). The vertical axis shows potential revenue gains as organizations advance in their personalization capabilities.
Figure 1: The five stages of the data-driven personalization capability maturity model
Examining the horizontal line progression more closely, it becomes clear that moving from “starting” to “excelling” involves both data maturity and activation of a unified customer profile across all enterprise touchpoints. Next-level personalization starts with fully cleansed, accurate data, which opens the door to more impactful use cases and results in brands being able to fully operationalize that data effectively across the entire martech ecosystem – a single brand voice, a single set of decisions, and a single set of experiences optimized for individual customers at scale and the company’s goals.
Modern customer engagement technology makes simple to complex use cases possible by creating cascading value (See Figure 2). A unified profile that is accurate, up-to-date, and provides a contextual understanding of a customer (household, business, etc.) across an ongoing customer journey, resulting in more accurate and finely tuned segments, which then results in an ability to orchestrate next best actions (up to and including in real time) across the customer journey – any channel, any touchpoint.
Figure 2: The creation and building out of value in the context of personalized CX as data readiness capabilities expand.
Value Creation – a Breakdown
Companies can plot their personalization maturity by what their current engagement technology can support, i.e., what use cases they are capable of.
- Identity Resolution/Profile Unification
For organizations just starting a personalization build-out, it’s likely that customer data is siloed across the enterprise without data quality standards in place. Profile unification and identity resolution are on an ad-hoc basis, with one-time matching and a lack of persistent keys.
As they build out their capabilities, data quality becomes automated on an episodic basis. Perhaps they begin deterministic matching on an identifier, or start with black box probabilistic matching. For companies that excel at personalization, data quality is automated on a consistent basis during data ingestion. They never have to question whether or where it’s happening downstream. Identity resolution uses a combination of deterministic and probabilistic matching, and it is also tunable, transparent and flexible – optimized for any use case.
- Segmentation
A company’s status in building out a unified customer profile affects its ability to create dynamic segments that synchronize to a real time profile. At level one, siloed data and ad-hoc matching result in product-centric or organization-centric segmentation, a limitation that is forced on a company because brands at this level do not yet have a deep, contextual understanding of a customer.
As companies progress on the personalization maturity roadmap, they may start to create granular segments with some omnichannel activation. As segmentation capabilities advance, dynamic segmentation becomes possible where segments are automatically updated according to reflect and capture a customer within the context of a customer journey (segment of one).
More sophisticated personalization becomes possible when dynamic segmentation becomes reflective of response data, meaning that real time results are fed back into the system, opening the door for real time iterative improvements.
- Orchestration
The state of data readiness bleeds into orchestration. If a unified profile and dynamic segmentation are the foundational fuel for a smarter CX, orchestration lights the match, the transition from having the right data to making use of the right data. Just as with the steps required to getting data in the right place, orchestration follows a similar playbook. Basic personalization is limited to product-centric segmentation and audience building, which means static experiences when designing triggers and journeys themselves. (A static segment created off a list results in a static offer.) Instead of omnichannel personalization and execution, brands are limited to orchestrating experiences on a channel-by-channel basis.
Advancing on the personalization maturity curve is not an overnight transformation, it’s a strategic evolution that begins with data readiness. … With a unified customer profile, dynamic segmentation, and real-time decisioning in place, organizations can shift from fragmented, static experiences to truly orchestrated, omnichannel personalization. The ability to act on fresh, accurate data in real time means businesses can anticipate customer needs, optimize engagement across all touchpoints, and drive measurable growth.
At the mid-level of orchestration capabilities, more granular segments begin to unlock omnichannel activation. Dynamic segments open up the possibility of orchestrating next-best actions using rules based decisioning with selective outbound and inbound coordination.
Personalization maturity, as it relates to orchestration, entails intent-based decisions and customer-centric omnichannel execution, propelled by dynamic segments that are reflective of response data. This means that the enterprise is perpetually in synch with a customer (household, etc.) in real time as a customer journey unfolds. Aggregations are calculated on the fly, models scores are used on the fly, and customer intent is anticipated through data – all because the enterprise is in possession of an accurate, updated customer profile.
- Real Time
At the far end of the value chain, real-time interactions progress in a similar fashion. At a basic level, real time consists of simple, in-channel reactions based off basic PII personalization, such as welcoming a customer by name. At a more advanced level, a better understanding of a customer makes more contextual personalization possible, where personalization is responsive in the channel and there can even be a hierarchy of ranked actions, where a next best action is determined by what a customer does in real time. In healthcare, for instance, this might entail basic contextual suggestions related to searches and clicks.
The state of full data readiness, applied to real time interactions, means that an organization is capable of cross-channel, next-best actions across the enterprise. This means that decisions are responsible – or arbitrated – across all channels and enterprise functions, with context and decisions based on predictive journey details (e.g., aspirational journeys, holistic wellness, etc.).
The Path Forward: From Readiness to Real-Time Personalization
Advancing on the personalization maturity curve is not an overnight transformation, it’s a strategic evolution that begins with data readiness. As the example of the travel and leisure company demonstrates, solving one foundational data challenge can set the stage for broader personalization capabilities.
With a unified customer profile, dynamic segmentation, and real-time decisioning in place, organizations can shift from fragmented, static experiences to truly orchestrated, omnichannel personalization. The ability to act on fresh, accurate data in real time means businesses can anticipate customer needs, optimize engagement across all touchpoints, and drive measurable growth.
The question is no longer if your organization should invest in personalization maturity, it’s how far you can take it. With the right technology in place, the finish line isn’t a destination, but a continuously expanding horizon of possibility.
