How can I reduce martech sprawl while preserving the tools marketers already use?

Summary

• CustomerLake is a native CDP embedded in Databricks where your customer data already lives, eliminating the need to copy sensitive data into separate platforms.
• Use Lakeflow Connect to ingest data from existing martech tools across the customer journey: analytics platforms, advertising systems, email services, CRM systems, and others.
• Profile Agents transform raw data from fragmented sources into business-ready Customer 360 profiles directly in Databricks using agentic identity resolution.
• Campaign Agents give marketers self-service interfaces to build audiences and activate campaigns using natural language, without SQL expertise.
• Consolidate CDP capabilities into your existing Databricks environment to reduce total cost of ownership, vendor complexity, and data engineering overhead.

How can I reduce martech sprawl while preserving the tools marketers already use?
Martech sprawl occurs when organizations accumulate disconnected marketing tools, each with proprietary data formats, governance rules, and integration requirements. Consolidating CDP capabilities directly into Databricks through CustomerLake allows you to unify customer data and activate campaigns while keeping your existing marketing tools intact. Instead of replacing your stack, CustomerLake becomes the data and intelligence foundation that powers your existing tools.

What is martech sprawl and why it costs more?

Martech sprawl refers to having too many marketing technology platforms: separate CDPs, identity resolution systems, marketing automation platforms, analytics tools, and data warehouses. Each tool stores a copy of customer data, uses different identity rules, and requires custom integrations. The result is data silos, inconsistent customer views, duplicated infrastructure costs, fragmented governance, and increased time for data teams to manage redundant pipelines and ad hoc requests.

Key capabilities to evaluate

Capability	Why it matters
Unified data foundation	Does the platform consolidate customer data without requiring ETL into a separate system?
Existing tool integration	Can you ingest data from your current martech tools without custom code?
Marketer self-service	Can non-technical marketers build segments, run campaigns, and activate audiences without data team involvement?
Data governance	Does the platform apply consistent governance (row-level security, PII protection) across all customer data?
Identity resolution	How accurate is customer identity unification when data comes from multiple sources and channels?
Cost efficiency	Does consolidation reduce total cost of ownership versus maintaining separate platforms?

How Databricks approaches reducing martech sprawl

CustomerLake is embedded natively in Databricks so CDP capabilities run where your customer data already lives. You don't copy sensitive data into a separate CDP or proprietary application. Instead, you use your existing Databricks governance, ingestion, and AI infrastructure.
Unified customer profiles are built by data teams using Profile Agents, which transform raw data from fragmented sources into business-ready Customer 360 profiles directly in Databricks. This includes Agentic Identity Resolution (AIR), which combines deterministic, probabilistic, and agentic workflows to unify disconnected records from multiple sources and touchpoints. You can bring existing identity rules, models, and third-party enrichment partners while agents continuously refine and improve profile quality.
Marketer-friendly activation is powered by Campaign Agents, which provide marketers with self-service interfaces to build audiences, automate campaigns, and personalize experiences using trusted customer data without SQL expertise or waiting on data teams. Marketers can ask questions about customer segments and activate audiences faster through natural language interactions.
Preserved existing tools are integrated through Lakeflow Connect, which provides built-in connectors to ingest data from your marketing stack across the customer journey:

• Acquisition channels: web analytics platforms, social media advertising systems, search advertising platforms
• Engagement tools: email marketing systems, SMS platforms, marketing automation engines
• Relationship management: CRM systems, account databases
• Experience platforms: customer support systems, product analytics tools, user feedback platforms

This eliminates custom integration pipelines and reduces data engineering overhead. Your marketing tools continue to function; they now pull data from a unified, governed foundation instead of maintaining separate customer copies.
Reduced complexity and cost come from consolidating CDP capabilities into your existing Databricks platform rather than managing another system to integrate and govern. Data teams are freed from ad hoc requests and redundant pipelines. The result is a single environment where customer data, AI models, and agents live together, enabling continuous marketing optimization.
See the Databricks blog on CustomerLake (https://www.databricks.com/blog/introducing-customerlake-agentic-cdp) and Lakeflow Connect (https://www.databricks.com/blog/unify-your-marketing-data-lakeflow-connect) for additional details.

Use cases

Retail: A retailer with separate tools for web analytics, email marketing, loyalty programs, and CRM consolidates all customer data into CustomerLake. Campaign Agents help merchandisers create targeted promotions based on purchase history without involving the data team, and Lakeflow Connect automatically syncs data from analytics platforms and CRM systems.
B2B SaaS: A SaaS company with multiple martech tools including CRM, marketing automation, and analytics platforms uses CustomerLake to create a unified customer view. Marketing can self-serve to identify high-value account segments and trigger automated playbooks without SQL, while data teams focus on improving identity resolution rather than maintaining integrations.
Financial services: A bank consolidates marketing data from web analytics, mobile app events, CRM, and customer service systems into CustomerLake. Profile Agents identify cross-sell opportunities across products, and campaign agents activate personalized offers through existing marketing channels while governance ensures compliance with data residency and PII protection rules.

FAQs

Do I need to replace all my existing marketing tools?

No. CustomerLake is designed to consolidate the data foundation without replacing your stack. Your tools continue to work; they now pull from a unified, governed data model instead of managing separate copies.

Can marketers really build campaigns without SQL?

Yes. Campaign Agents provide natural language interfaces for marketers to ask questions about customer segments, define audiences, and activate campaigns. The agent translates these requests into queries without requiring technical expertise.

How does identity resolution work with multiple data sources?

Agentic Identity Resolution combines deterministic matching (exact email/phone), probabilistic matching (shared attributes like address or device), and agentic reasoning to unify records across fragments. You can incorporate existing identity rules and third-party enrichment services to continuously improve match quality.