Nearly two thirds of CMOs admit that “they have a long way to go in using big data properly,” according to The CMO Council.
Data will continue to play a pivotal role in delivering contextually relevant experiences to customers who are always on and readily addressable. But there remain significant opportunities to improve data-driven marketing to ultimately engage with customers in ways that meet their rising expectations.
Most companies are either overdelivering or underdelivering against customer expectations today. Overdelivering might mean using data in ways the customer doesn’t value or communicating too frequently. Underdelivering might mean not using data to provide relevant personalization or, worse, not using data at all. Success is about striking a balance between what customers need and what the business hopes to achieve.
Customer engagement optimization is the most efficient way to achieve that balance, and in doing so, cultivate new customers and retain existing customers. But engagement optimization requires a robust focus on data and on customer-centric, data-driven interactions and decisioning.
There are six ways marketers can improve their data-driven marketing acumen that will support their customer engagement optimization efforts—and the technologies that can help.
Poor data quality leads to analytics and insights that don’t accurately reflect customers, as well as to misaligned moments of engagement and negative brand experiences. Marketers can fix data-quality issues by exposing their root cause. One of the biggest challenges is correctly identifying customers that may have interacted across several channels and subsystems. There are other common culprits including data entry errors, discrepancies in similar data provided by different systems during data integration, erroneous data matches resulting in lost data, and data structure limitations and inconsistencies.
Remedying the data-quality issue starts with precisely resolving identities across customers, households, and devices along with all of their variations. These efforts are enhanced by fixing the data in the source system, as well as fixing the system itself. The newest generation of marketing technology offers a data layer to aggregate, augment, scrub, and transform customer data. It’s the fastest and easiest way to solve for data quality issues.
The ability to ingest data and connect with customers across an array of systems is a basic requirement for marketers today. Doing so is difficult to accomplish with disparate tools. There’s demonstrable value in open and connected marketing technology. The ability to leverage the best tools for a brand— from the newest channels to new innovations in AdTech and MarTech—in ways that also align the data from these tools and facilitate communications across all of these systems is critical to customer engagement optimization.
The fact is, not all companies are ready to rip out legacy technologies that still have strategic value. Additionally, there are best-of-breed tools and enabling technologies that marketers can implement not only to supplement and enhance their existing marketing stack, but also to differentiate the customer experience. These tools can provide the flexiblity marketers need to adapt quickly to customers’ ever-changing expectations and the agility they need to optimize the customer experience.
The concept of a “golden customer record” refers to a single source of truth for any and all customer interactions. Insights into the frequency of engagement, device use, household, purchase cycles, media mix, and conversion activity can inform all facets of customer engagement optimization. Marketers can translate these data points into listening activities, new segments, trigger-based campaigns, and paid media investments to micro-target customers with relevant messages.
Most brands attempt to solve the golden customer record challenge by creating a customer data warehouse or federated database to consolidate customer interactions from source systems. But connecting disparate data to a unique customer record (a CID, email, or fuzzy logic) only solves for half the equation; it’s also essential to use this data to improve the customer experience.
Legacy tools and lack of integration force marketers to personalize messaging using only basic customer profile data. The next generation of customer engagement platforms can ingest data from any source system and then put it into action via automated triggers, business logic, advanced modeling, and real-time personalization. Marketers can learn a great deal about individual customers during anonymous interactions if they have mechanisms to connect the activity to a known customer later, building a progressive profile as the customer engages over time.
Most personalization efforts involve manual intervention from marketers: contact lists have to be downloaded and uploaded from multiple systems; paid media campaigns have to be configured for display, search, and social; and channel-specific copy and creative must be created from scratch. This is less than ideal for customer engagement optimization.
The data-driven personalization needed for engagement optimization is real-time, contextual, and relevant. That means marketing technology must be capable of using first-, second-, and third-party data to inform the right messaging at the right time in the right channels. The new generation of engagement platforms use advanced computing, business intelligence, and marketing-friendly user interfaces to make data-driven personalization easy for marketers to manage and implement. These next-gen customer engagement tools offer assets such as three to 10 times faster processing than traditional campaign tools; triggered and transactional messages; and dynamic segmentation and suppression rules.
Marketing execution involves a complex tapestry of roles and responsibilities. Rarely are the reporting capabilities of most marketing technologies equally diverse. While there’s certainly no shortage of charts and reports from today’s marketing tools, many of them go unused by marketers. Dashboards and reporting are only valuable if they provide context that can inform a decision or action.
Different marketing stakeholders have very different requirements with respect to reporting. The CMO needs holistic visibility across performance, spend allocation, alignment with marketing targets, and back-office operational execution. A campaign manager needs detailed insights about the performance of in-flight campaigns and real-time insights about improving performance. The next generation of customer engagement platforms has invested heavily in intelligent reporting so marketers can easily translate relevant, role-based insights into actions that benefit customer engagement optimization.
Marketers are responsible for managing exponentially growing volumes of data that they’ve acquired via channels such as web analytics, social media monitoring, email, mobile, display, search, and third parties. The focus on extracting value from these large and ever-changing volumes of customer data has led to new roles and responsibilities such as data scientists, machine learning, and advanced predictive analytics. But extracting the insights needed to deliver real-time personalization at scale also requires analytics technologies that enable marketers to foster 1:1 relationships.
Today, advances in cloud computing, data access, and analytic models provide the power marketers need to hyper-personalize interactions. The next generation of customer engagement platforms allow marketers to drag-and-drop a library of analytic models on top of massive volumes of customer data. Modeling and operational execution happen from a single platform where marketers can apply models and real-time, trigger-based optimization to optimize offers, targeting, media mix investments, and messaging at the point of execution.
Customers’ appetite for relevant customer experiences has no bounds. Marketers must invest in customer engagement optimization—delivering contextually relevant experiences that are informed by data.
But being “data-driven” is about more than relying on data to inform customer strategy or operational execution. The future is about real-time marketing, personalization, and continuous optimization—and data is the means to this end.
What’s exciting for marketers is that the data challenges they have all faced for decades are being addressed in next generation engagement platforms. These systems allow marketers to connect and interact with existing marketing tools, build a single view of the customer; deliver real-time personalization; personalize dashboards by role; and unlock the potential of big data and analytics for operational execution.
It’s up to you to determine how quickly you’ll set off on the journey to hone your data-driven marketing acumen and succeed at customer engagement optimization. These six steps will certainly set you on the right path.