Customer data is more valuable than ever before in our increasingly digital world. As consumers engage with businesses across more channels and devices, they leave behind traces of behavioral data gold. Smart companies are tapping into this trove of first-party data to better understand customers, create unified profiles, and deliver personalized experiences. Enter customer data platforms (CDPs).
CDPs are purpose-built to collect, unify, and activate customer data from all touchpoints. As adoption accelerates, CDPs are evolving into mission-critical tools for marketers. In this comprehensive guide, we’ll cover everything you need to know to harness the power of CDPs, including capabilities, use cases, benefits, challenges, the future outlook and more.
What is a Customer Data Platform?
Let‘s start by examining what comprises a customer data platform at a technical level. At the most basic level, CDPs ingest and consolidate customer data from source systems across the enterprise into a persistent, secure store that serves as a "single source of truth" for customer identities and interactions. But many components come together to make this possible:
Ingestion – APIs, containers, services collect batch or streaming data from CRMs, web/app analytics, email systems, loyalty databases point-of-sale and other channels.
Identity Resolution – As data flows in, probabilistic and deterministic matching algorithms associate behavioral events and attributes with unique customer identities across devices and sessions. Techniques range from rules-based matching to fuzzy logic to machine learning classifiers.
Profile Database – Billions of customer records with hundreds of fields are efficiently stored in specialized data warehouses or lakes purpose-built for analytics using cloud-native tech like Snowflake, Databricks, and BigQuery.
Transformations – Tools and scripting manipulate the raw data into analysis-ready structures indexed for interactivity. Typical transformations include aggregations, derived metrics, sessionization etc.
Privacy/Governance – Layered controls enforce data usage policies, manage consumer consent, and honor access requests in compliance with frameworks like CCPA and GDPR.
Activation – Real-time APIs, batch transfer, and integrated connectors syndicate the enriched profiles to downstream martech systems for analytics, personalization, and orchestration.
With the right architecture, a CDP ultimately funnels data from all customer interactions into a unified profile system ready for immediate analysis and activation. Now let‘s examine why this unification delivers so much value.
The Strategic Value of CDPs
Consumer behaviors and expectations have evolved faster than the marketing technology designed to track them…
Key CDP Benefits and Capabilities
CDPs pack a punch when it comes to marketing capabilities. Let’s explore the primary benefits driving adoption:
Unified Customer Profiles
At their core, CDPs create a “golden record” for every customer by resolving identities and aggregating behavior regardless of channel. These unified profiles reflect the full spectrum of customer interactions in a privacy-compliant manner. Marketers gain a single source of truth about customers to inform decision making.
From a technology perspective, accurate profile unification at scale requires sophisticated identity resolution capabilities. The various approaches carry distinct tradeoffs:
Rules-based – Match profiles using defined logic, e.g. on email address exact matches. Simple to implement but limited.
Probabilistic / ML models – Apply statistical models calculating confidence scores that two events represent the same person based on weighting multiple attributes and interactions. More accurate but complex to develop.
Deterministic / Graph databases – Construct profiles by connecting verified account-based IDs across datasets reflecting confirmed matches. Highly accurate but limited coverage.
Hybrid – Combine the above for optimal coverage, accuracy and scale. CDPs utilize parallel identity resolution pipelines to create complete, precise, and reliable profile foundations.
The identity challenge highlights why purpose-built customer data infrastructure delivers outsized value. When disparate sources reflect disconnected views of customers, unifying profiles becomes impossible. Only integrated, end-to-end profile architectures provide the foundation for true personalization.
Personalization
Granular customer insights allow brands to tailor messaging based on interests, behaviors, and attributes. CDPs define microsegments and power data-driven 1:1 personalization at scale across channels.
Advanced analytics take this to the next level…
CDP Use Cases and Industry Applications
The capabilities of CDPs lend themselves to a variety of common user stories. Here are some expanded examples with technical details:
Retail
For retailers with online stores, brick-and-mortar outlets, mobile apps, and more, CDPs empower data-driven customer engagement.
Loyalty and promotions – Retailers leverage purchase history and behaviors to define tiers and personalized promotions that increase share of wallet. Machine learning pipelines ingest granular behavioral data including browsing, cart additions, checkout success/failure events to model customer lifetime value and predict optimal incentive thresholds.
Lifecycle campaigns …
Financial Services
Banks, insurance providers, and other financial service companies manage highly regulated data across advisors, call centers, digital properties, and third-party integrations.
Omnichannel personalization – Tailor recommendations to customers based on financial activity, risk profile, lifetime stage etc. Enterprise integration patterns allow secure, governed data sharing from core systems like lending platforms, wealth management suites, and policy admin systems into analytics environments where data scientists can develop propensity models and segmentation to improve targeting.
Agent tools – Real-time APIs surface insights to advisors in real-time during customer service calls based on comprehensive profile analytics. Care agents equipped with lifetime engagement history and context convert at higher rates.
Compliance – Adhere to mandates around data handling with consent, access, and privacy controls. Granular permissions management ensures financial customer data follows restrictions prohibiting data sharing across regions, business lines, adherence to data retention limits, and other policies, with dashboard showing compliance coverage.
Media and Entertainment
CDPs help media publishers better monetize digital content while improving subscriber and advertiser experiences.
Churn prediction – Identify high-risk subscribers based on consumption metrics and take proactive retention measures. Apply survival analysis statistical modeling to streaming event logs over time as customers engage with platforms and content. Identify behavioral leading indicators predicting churn.
Programmatic advertising …
The CDP and Customer Intelligence Platform Landscape
Emerging Technology Trends
As CDPs continue maturing into indispensable customer intelligence hubs, several technology trends bear watching:
Customer journey analytics – Stitching cross-channel behaviors into attributed sequences and analyzing journeys end-to-end reveals why and where customers convert, struggle, or churn. Specialized journey visualization, segmentation, scoring, and modeling packages help marketers optimize paths. Integrating journey analytics with campaign data closes the loop for continuous optimization.
IoT integration – Connecting directly with connected products, wearables, smart home devices and industrial infrastructure allows capturing highly contextualized customer behaviors and moments. Retailers can detect when someone walks in store. Utilities monitor when appliance failure risks emerge. Automakers get telemetry if a car breaks down. Each event triggers real-time engagement opportunities.
Decentralized identity – Emergent blockchain-inspired protocols like Veramo and Hyperledger Indy allow consumers to securely prove identity, share validated attributes, and manage consent universally. This bypasses platform-dependent identity silos to give people perpetual ownership over their own profiles in a privacy-preserving manner. Early CDPs are piloting decentralized identity integration with promise to resolve profiles ubiquitously.
The Rise of Customer Intelligence Platforms
On the bleeding edge, a related technology promises to take personalization to the next level: the customer intelligence platform (CIP)…
Key capabilities include:
- Predictive analytics – Advanced machine learning for propensity modeling, churn prediction, personalized incentives etc.
- Next best action – Define optimal customer treatments and journeys tailored to sentiment, behaviors, and predictive profiles. Apply reinforcement learning algorithms trained off historic customer response data to optimize suggestions to complex objectives balancing short term conversions, long term value, and experience metrics.
- Experience decisioning – Apply intelligence to customize messaging, content, recommendations, and offers in real time. Contextual bandit algorithms continuously test variations to surrounding UI elements, editorial placements, promotions based on aggregated profile attributes and situational data.
- Auto optimization – Continuously test permutations of data inputs, algorithms, and experiences to maximize engagement. Adopt technology like H20 Driverless AI to automatically cycle through feature engineering, model selection, hyperparameter tuning modeling hundreds of ML pipelines to maximally predict KPIs.
CIPs herald an exciting new paradigm for customer intelligence. However, analysts agree that most brands have significant runway just optimizing CDPs first. Once unified, high quality data flows across channels, data science initiatives progress smoothly.
CDP Challenges and Considerations
While CDPs offer manifold benefits, they also come with limitations. Here are key challenges to factor from technical, data, and organizational perspectives when evaluating options:
Technology Challenges
Data integration – Connecting disparate data sources with differing formats, access protocols, and governance models poses technical and organizational challenges. Factor integration costs into planning. Want to learn more? See our in-depth guide to modern customer data integration.
Identity – Resolving customers across devices and channels presents statistical matching issues at population scale and sophistication requirements continue rising. Continual graph learning is critical. See benchmark results on leading identity vendor accuracy.
Overhead – CDPs require specialized personnel for implementation, maintenance, data modeling, and analytics. Our Decision Guide for Staffing Customer Data Teams provides role archetypes and sample organization structures to help assess internal capabilities for operating a customer data tech stack.
Speed – Latency needs to allow for real-time activation. Ensure performance testing against data volumes across customer tiers. Review sample SLAs and sizings.
Data Challenges
Compliance – Navigating global data privacy regulations creates complexities around data residency, access rights, and retention. Prioritize flexible policy controls and audit logging to track permissions, usage, and justify legitimate interest. See our Data Privacy Technology Primer for latest capabilities.
Provenance – With dozens of inbound data sources, documenting origin, transformations, quality checks, and usage rights throughout the pipeline stages poses challenges. Collaborative data catalogs with rich profiling help. See how leading financial services company achieved 98% automated metadata capture.
Organizational Challenges
Consensus – Earning shared vision across stakeholders plays a major role in maximizing ROI on foundational investments. Learn how to align executives on customer data strategy.
Agility – Transitioning to more nimble, data-driven ways of working requires shifts in processes, culture, and team dynamics. See our proven change management game plan.
Proof – Hard dollar ROI can be difficult to pinpoint, especially for enterprise-wide deployments. Set clear metrics and benchmarks based on scope. Telecom company tied $42M in lifetime revenue to CDP-powered campaigns.
The right strategies and vendors can help address these multifaceted concerns…
Key Steps for Harnessing CDPs
If reading this guide has sparked interest in exploring CDPs firsthand, here are recommended next steps:
Audit data – Map existing structured and unstructured customer data sources, quantify value, identify gaps.
Define use cases – Brainstorm high impact levers aligned to business goals based on capabilities discussed. See our starter kit to help build your business case.
Calculate ROI – Estimate expected lift across priority KPIs including conversion rates, revenue per customer, retention etc. based on precedents. CDP value calculator provides starter projections.
Issue RFP …
Govern closely – Manage consumer transparency, choice, access and data compliance from the outset. Designate domain experts for privacy and ethics oversight of data usage, machine learning, and experience delivery powered by the CDP.
Keep innovating – Continue to build towards true 1:1 personalization powered by CDP foundations. Maintain Sharp Focus on the Future with Customer Data.
With the right vision and preparation, CDPs can transform customer engagement throughout the lifecycle. Our team would be glad to offer additional guidance tailored to your organization as you explore harnessing customer data. Reach out if we can help further at any stage!