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Customer Data Management
Your business relies on data, but not all data is the same. The true competitive edge lies with how you manage customer data. Customer data management (CDM) will not just store customer data effectively and enable customers to find what they need; it will be a source of insights, trust, and improved customer relationships.
If you’re really trying to scale and personalize at the same time, CDM will underpin innovation and growth. In this blog we will explore what customer data management means, why it matters, and how a structured approach will help you future-proof your organization.
Meaning of Customer Data Management
Customer Data Management (CDM) is the process of collecting, organizing, protecting, and managing customer data across a variety of touchpoints. Think about it as building a single, reliable, actionable version of the truth about your customers.
CDM includes more than storing customer records; it includes:
- Gathering your data together under multiple data sources (sales, marketing, support, commerce, etc.)
- Setting accuracy, privacy compliance, and consistent functionality
- Building your data into a state of use for decision making, using for personalization, and adoption of AI
In essence, CDM is taking raw customer information and using it to support customer intelligence.
Why Businesses Need a Strong CDM Strategy
Properly managing customer data makes a measurable difference. Here is how:
- You make decisions faster and better - When you have a unified view of the customer, you make fact-based decisions versus assumption-based ones.
- You encourage personalization - Your marketing teams can provide moments and experiences that are relevant, increasing conversion, and loyalty.
- There is increased compliance & trust - A structured Customer Data Management (CDM) developed to ensure your organization complies (e.g. GDPR/CCPA) provides customers with assurance and trust.
- Your AI & analytics readiness are improved - Clean, governed data is the only way to responsibly drive advanced analytics and/or AI.
- Your operational efficiency is improved - Your teams across the organization are working from the same reliable source of data and timings, decreasing duplication, and misalignment.
In essence, CDM is taking raw customer information and using it to support customer intelligence.
Core Pillars of Customer Data Management
1. Data Collection & Integration
The first step is to collect data of every type from all touchpoints. From websites and apps, to call centers, to retail and other in-store transactions or social media posts on your channels – there is data all around you and the first step is figuring out how to collect it all. But collecting raw data isn’t enough. You must integrate that data! Once you have these data inputs integrated, you can create a full 360-degree customer profile.
2. Data Quality & Accuracy
Duplicate data, incomplete records, or stale data increases the chances your customer data has next to no value. By introducing processes such as data cleansing/de-duplication and validation, you can ensure you have data that you can trust. When the data you have is accurate, the decision you make to leverage data will have an increased likelihood of being the correct decision.
3. Data Governance & Security
Governance specifies how your data should be used, who can use it, and the purpose for which data is used. Governance can take the form of:
- Role-based access controls
- Data usage policies
- Privacy Policy controls
- Security measures - encryption, etc.
Good governance identifies risk and affords good customer transparency.
4. Data Analysis & Insights
Customer data is only usable if it creates actionable insights. If you segment customers in ways that demonstrate trends or allow for predictive models, you can identify behavior, needs, and opportunities that may be overlooked when reviewing the data manually.
5. Data Activation
This last step connects customer insights into driving better business outcomes. This could include:
- More personalized campaigns in marketing
- More meaningful product recommendations
- Faster resolutions to service requests in support
- Better tailored rewards value in loyalty programs
Best Practices for Effective CDM
Define your Objectives
What do you want your customer data to do? More retention? More speed of acquisition? More compliance?
Utilize automation & AI
Automate common practices such as cleansing & enrichment as much and leverage AI to uncover deeper insights.
Measure, Refine, Reassess
Treat CDM as a continually evolving discipline, continually correlated to your business and customers.
Use a centralized data system
Use technologies that run all customer information into one channel.
Focus on data quality from day 1
Construct processes to continuously monitor and enhance data accuracy.
Embed governance into the culture
Make data management integral to the workday.
Customer Data Management Platforms
To effectively manage customer data, it needs to be paired with the right set of tools that will support data collection, integration, governance, and analysis at scale. Generally speaking, these tools will fall into categories that pertain to specific parts of the data lifecycle so that information can flow seamlessly across systems while preserving accuracy and compliance.
1. Data Integration and ETL Platforms
A core category is data integration and ETL platforms that support the unification of customer information across numerous touchpoints (websites, CRM systems, call centers, and external applications). Data integration and ETL platforms automate the extraction, transformation, and load processes to ensure the data is presented in a clean standardized format. Below are some examples of data integration and ETL platforms:
- Fivetran – Helps streamline data ingestion via pre-built connectors that automatically extract data from hundreds of sources.
- Informatica Cloud Data Integration (CDI) – Supports more advanced transformation capabilities in large enterprise environments that ensure high quality and consistent data pipelines.
- dbt – Enables analytics engineers to transform and model data within a data warehouse to make it more reliable and ready for analytics.
2. Master Data Management (MDM) Systems
A key sub-category is Master Data Management (MDM) systems, which establish a single source of truth for each customer. These platforms clarify discrepancies by identifying and merging records across the organization.
Informatica MDM – Provides a single customer view through a comprehensive record of billing, purchase, and servicing into a single, comprehensive profile of the customer. A strong baseline for personalization, targeted marketing and customer service.
3. Data Governance and Compliance Solutions
Compliance and data governance solutions make up the third pillar of CDM tools. As organizations operate under increasing scrutiny because of regulations in the marketplace, these systems help automate enforcement of data policies, tracking of data lineage and the documentation of audit trails.
- Informatica Axon Data Governance – Provides organizations visibility into data lineage and data ownership, while aligning their data to privacy regulations such as GDPR, personal data protection laws (CCPA).
- Snowflake’s governance features – Dynamic data masking and role-based access control empower secure policy driven data sharing across teams and partners.
4. Analytics and AI-Driven Platforms
Lastly, analytics and AI-enabled platforms take the value of a CDM to another level by translating structured and governed data into predictive insights. They can identify patterns in customer behavior, churn predictions, as well as cross-selling opportunities.
- Snowflake – Acts as a scalable data cloud which helps companies harmonize in real-time and analyzes customer data at scale and utilizes governed data and data analytics which turns large datasets into actionable insights.
- Databricks – Unifies data engineering, machine learning, and AI in one platform, to run advanced analytics such as predictive modeling and personalization at scale.
Rather than the benefits stemming from utilizing a specific tool, the efficiency of a CDM lies in merging into a connected ecosystem. Together, integrations, MDM, governance, and analytics platforms can recreate the true value from customer data.
How LumenData Helps Organizations with CDM
Our specialty is in implementing modern data architectures that help businesses protect, trust, and use customer data. This is how we deliver services to our clients:
- Incorporation & Integration: Building all the pipelines to view online, offline, structured and unstructured data in one place.
- Data Governance Frameworks: Establishing policies, controls, and workflows to achieve compliance without sacrificing access.
- Quality: Establishing processes for accuracy, completeness, and timely data.
- Analytics Enablement: Making data useful through insight that evaluates campaigns, journeys, and experiences.
- AI Ready: Preparing customer data for safe, ethical, legal implementation of AI.
- Technology Implementation: Implementing modern customer data platforms such as Informatica SaaS MDM, Snowflake, Fivetran, Databricks etc.
Wrapping Up
Privacy rules are changing, and customers expect more transparency, leading to a shift in enterprise customer data management (CDM. You’ll be able to prioritize CDM by:
- Treating data as an asset that belongs to the customer, not just to the enterprise.
- Investing in real-time capabilities that adjust based on customer activity in the moment.
- Finding the right balance between personalization and privacy to develop long-term trust.
- Adopting CDM as a basis for developing AI-driven business models.
Are you ready to modernize your approach? We can help. Reach out.
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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