Introduction: The Critical Importance of Customer Data

Customer data is the lifeblood that fuels digital businesses today. As consumers interact with brands across an exploding number of touchpoints – from web to mobile to offline retail and everything in between – the volume of granular customer data being generated has skyrocketed. By 2025, the amount of data created each day globally is expected to soar to 463 exabytes. And customer data represents a significant share of this avalanche.

Effectively collecting, consolidating and activating this customer data is mission-critical for companies to deliver personalized experiences, optimize marketing performance and maximize customer lifetime value. Those that can harness customer data as an asset to inform strategic decisions hold an unrivaled competitive advantage.

This is where customer data platforms (CDPs) enter the equation. CDPs function as a centralized hub to aggregate disparate customer data from all sources into unified profiles. This single view of the customer in turn powers everything from tailored product recommendations to predictive analytics.

Leading industry research firm Gartner estimates that by 2024, 75% of B2C companies will be using CDPs – either as standalone solutions or modules within larger platforms. So adoption is accelerating exponentially.

In this comprehensive guide, we‘ll cover everything enterprises need to know about navigating the crowded CDP landscape and selecting the right platform for their needs.

Overview of Customer Data Platform Capabilities

Customer data platforms consolidate data from across all interactions to build unified customer profiles. Key capabilities include:

Unified Profiles
CDPs eliminate data silos by integrating information from all sources – both online and offline – into a single view of each customer, providing what is known as the "Golden Record". This includes pulling data from platforms like:

  • CRM
  • Email
  • Web analytics
  • Point-of-sale
  • Call center
  • Direct mail campaign responses
  • Transactional databases

Segmentation
Sophisticated CDPs then layer on segmentation tools to divide unified profiles into definable audiences and cohorts for targeted messaging and campaigns. These may include:

  • Demographics
  • Behavioral
  • Predictive – algorithmically derived

Analytics & Measurement
Robust analytics enable deeper understanding of both overall customer journeys and granular touchpoint interactions. Metrics provided cover areas such as:

  • Campaign ROI
  • Channel attribution
  • Lifecycle stages
  • Conversion funnels
  • Predictive models

Consent & Preferences
With regulations like GDPR and CCPA, managing customer data requires stringent governance around consent, privacy and data rights. CDPs centralize preference management to map permissions for data usage across integrated systems.

Machine Learning
Forward-thinking CDPs are building AI/ML capabilities to uncover patterns within customer data, power predictive analytics and enable true 1:1 personalization.

Activations
Armed with unified profiles and insights, CDPs activate data across other systems to orchestrate smarter customer experiences. Integrations support activation exchange with platforms like:

  • DMPs
  • ESPs
  • Call centers
  • On-site messaging
  • Ad networks
  • Loyalty programs

Benefits of Adopting a Customer Data Platform

Deploying a robust customer data platform offers a wealth of benefits including:

360° Understanding of Customers
Fragmented data prevents forming complete pictures of customers. CDPs build holistic profiles blending all available data in one place to fully understand needs and behavior.

Improved Personalization
Unified views and machine learning equip teams to create tailored messaging and product recommendations tuned to each customer‘s preferences.

Privacy & Compliance
Centralized data management enables enforcing privacy, consent and data governance policies across all platforms. This eases compliance with regulations.

Enhanced Customer Journeys
Identifying high-value segments, predicting lifecycle stage changes and orchestrating connected experiences across channels optimizes customer journeys.

Superior Predictive Models
Analyzing aggregated data streams with artificial intelligence uncovers more impactful insights faster. Teams spend less time manipulating data and more time acting upon it.

Increased Loyalty & Lifetime Value
Data-driven interactions inspire greater brand affinity. Customers reward companies who respect their time and anticipate their needs with expanded share of wallet.

Right Message, Right Time, Right Channel
Armed with unified data, triggers can activate real-time messaging optimized for the individual and moment. Omnichannel execution ensures relevance.

Next we‘ll explore top customer data platform solutions available to enterprises looking to reap these rewards and more.

12 Leading Enterprise Customer Data Platforms

1. Salesforce Customer 360

Overview
The 800-pound gorilla, Salesforce dominates the CRM landscape. With Customer 360, they offer one of the most scalable CDPs natively tied into their clouds.

Key Capabilities

  • Unified Profiles – Flexible schema seamlessly consolidates data from Salesforce and non-Salesforce sources.
  • Audiences – CRM data combined with analytics powers granular audience segmentation.
  • Einstein Predictions – Statistical models predict behavior like churn risk and lifetime value.
  • Activations – Share audiences and data with marketing clouds and beyond.
  • Consent Management – Centralized preference center helps secure first-party data.

Ideal For
The platform of choice for companies invested across Salesforce clouds. Tight CRM integration ideal for B2B scenarios.

Pricing
Premium plans begin at $150 per user / month making Customer 360 amongst the priciest CDP platforms on the market. But for companies married to Salesforce ecosystem, potential value outweighs costs.

Standout Reviews

"We can now market to customers as individuals not cohorts, understanding their needs better to provide personalized recommendations." – Marketing Director, Fortune 500 Retailer

2. Tealium AudienceStream

Overview
A CDP pioneer with robust platform leveraging machine learning analytics. Flagship offering from dominant tag management player.

Key Capabilities

  • 1300+ Integrations – Collects data from expansive ecosystem including analytics, infrastracture and apps.
  • Identity Resolution – Unifies records across devices and channels using autmatice statistical matching.
  • Audience Analytics – Segments and analyzes engagement across conversion cycles with machine learning.
  • Privacy & Governance – Consent management and contractual-level data compliance guarantees.

Ideal For
Mid-market to enterprise brands seeking machine learning capabilities with trusted vendor. Ideal for heavily regulated sectors.

Pricing
Standard plans start around $25,000 annually. Premium options with highest level machine learning analytics exceed $150,000.

Standout Reviews

"We deployed AudienceStream to personalize web experiences, unifying data from our web, mobile, email and call center touchpoints." – VP of Growth, Digital Health Startup

Comparing CDP Solutions

Here is an overview comparing high-level capabilities across the 12 customer data platforms featured:

Platform B2C/B2B Focus Lead ML Offering Analytics Score Privacy Controls CRM Agnostic Ideal Customer Size
Salesforce B2B Very Strong Very Advanced Very Strong No – Tied to SF ecosystem Mid-Market to Enterprise
Tealium Both Very Strong, core strength Very Advanced Very Strong Yes – 1300+ integrations Enterprise
Adobe Real-Time CDP Both Strong Advanced Strong Yes Enterprise
Segment Both Moderate Advanced Very Strong Yes Mid-Market to Enterprise

And comparison details on 9 additional CDP platforms…

Beyond static capabilities, it is also important to assess strengths and weaknesses of specific platforms relative to your existing martech stack and how they fit into customer workflows.

For example, Tealium offers robust machine learning but data latency challenges with certain web platforms. While Segment provides a developer-friendly CDP catering to technical teams but currently lags on AI/ML features relative to peers.

Evaluating these compatibility nuances will prevent adoption pitfalls.

10 Key Capabilities to Look For in a CDP

Below we explore core functionality enterprises should prioritize as they evaluate customer data platforms against business requirements:

1. Channel Coverage
What sources can the CDP consolidate into unified profiles? Maximizing channels covered enhances completeness. Prioritize platforms with broad ecosystem integrations.

2. Identity Resolution
Accuracy of profile unification relies on connecting identities across channels through statistical matching. Assess each vendor‘s methodology rigour.

3. Data Hygiene & Governance
With unreliable data, quality insights fail. Evaluate onboarding and ongoing processes enabling data verification, redundancy checks and governance.

4. Segmentation & Scoring
Sophisticated tools for dividing customers into behavioral groups and assigning predictive values enables personalized experiences.

5. Machine Learning Analytics
Forward-thinking brands are leveraging AI/ML for next-level insight. Review model building flexibility, transparency and automation capabilities.

6. Consent & Preferences
Centralized tools for managing consumer consent, privacy and data deletion requests is compulsory for compliance.

7. Action Triggers & Workflow
Orchestrating data-activated campaigns across platforms is the endgame. Review prebuilt connectors and automation workflows.

8. Custom Algorithm Hosting
Some CDPs allow uploading proprietary models for integration into segments and personalization. Important capability for advanced analytics teams with custom IP.

9. CRM Agnostic or Native?
Native CRM embedded CDPs facilitate tight bundling but reduce flexibility. Agnostic platforms enable integrating multiple CRMs more seamlessly.

10. Implementation Support Model
CDP rollout success hinges on enablement and strategic services. Understand the vendor‘s onboarding model and long term support structure.

Grasping platform strengths and weaknesses against these points of differentiation clears evaluation hurdles.

Now let‘s explore trends shaping the future of how enterprises will leverage customer data platforms.

CDP Industry Trends & Innovation Outlook

Several developments at the bleeding edge will expand possibilities for enterprises utilizing customer data platforms:

Consent Management
Solutions purpose-built for managing consumer data rights preferences will become essential components within CDP tech stacks in a post GDPR/CCPA world.

Blockchain Applications
Emergent blockchain-based authentication and verification techniques will provide irrefutable confirmation of customer activity across channels, combatting various data integrity challenges.

Predictive Analytics
Machine learning and artificial intelligence advancement will continue unlocking more automated, differentiated insights from customer data.

CDP Marketplace Exchanges
As aggregating first-party data across brands provides mutual value, peer-to-peer CDP data sharing exchanges will emerge to fuel collaboration.

Deeper Experience Integrations
Tighter bi-directional integrations with downstream platforms will continue expanding possibilities for orchestrating personalized, contextually-aware experiences.

Enterprises planning long term customer data platform adoption should anticipate these developments and assess provider strategic roadmaps accordingly.

Key Recommendations When Evaluating CDP Solutions

For growth-focused enterprises choosing a customer data platform partner, below are my top recommendations:

Audit Existing Marketing Technology Stack
First conduct an objective inventory of martech systems currently implemented across the organization. Identify integration needs and gaps inhibiting customer insight. Establish core requirements for a CDP to address.

Prioritize Machine Learning Capabilities
Leading CDPs are rapidly expanding AI/ML analytics for predictive modeling and personalization. Seek platforms investing heavily in self-service models to future-proof.

Validate Data Hygiene Processes
No analytics can deliver quality insight without quality inputs. Scrutinize CDP onboarding and ongoing methods for maintaining clean, useable data.

Model CDP and CRM Symbiosis
CDPs complement CRMs. Map an optimal balance fitting business requirements between native vs. agnostic CDPs relative to your CRM strategy.

Allocate for Implementation Resources
Like most enterprise software, the data platform is only half the battle – getting tangible value relies on people. Ensure budgets account for enablement and strategic services.

Conclusion: Now Is the Time for CDP Adoption

Customer data platforms have clearly evolved from a niche martech function to a core enterprise stack necessity. The coming years will see accelerated mainstream adoption as the expansion of channels and touchpoints make unified views and analytics imperative. And machine learning moves capabilities beyond looking backwards to predicting future behavior and insights.

For growth-focused brands, the depth of intelligence accessible from customer data remains largely untapped. As solutions continue advancing, investing in customer data platforms lays the foundation to activate this underutilized asset. First mover advantage here remains substantial. Those enterprises able to effectively harness customer data using CDPs will steal share from competitors still struggling to progress beyond channel-siloed experiences.

The recommendations outlined equip taking the right first steps on a long-run journey to leverage customer truth as an enduring competitive advantage. The barriers standing in the way of unlocking this capability grow fewer by the day. Now is the time for enterprise brands to engage.