See Your Customers Clearly: A Guide to Customer Data Integration
Customer Data Integration (CDI) refers to the process of consolidating customer information from multiple sources so it can be managed in a central application, providing a single, comprehensive view of customer data.
CDI is useful for several reasons. It lets sales and marketing teams better understand their audiences, helps break down data silos, empowers customer service agents to provide a better customer experience, and can be used as a part of data-driven decision-making strategies.
Customer Data Integration is particularly important today, where multichannel marketing is common and consumers can interact with brands via many different systems. According to a customer research report published by Dovetail, CDI enables teams to get higher-quality insights into customer behavior, preferences, and buying patterns, helping improve both marketing and the overall customer experience.
Here, I’ll explore the benefits of CDI, examine some best practices, and discuss some useful tools for effective customer data management.
6 Benefits of Customer Data Integration
Customer Data Integration offers several benefits for organizations.
1. Dismantles Data Silos
By bringing data from multiple different sources into one central view, CDI eliminates data silos and helps improve communication between departments. This ensures sales, marketing, retention, and customer service teams all have access to current, accurate customer profiles.
2. Enhances Segmentation and Customer Insights
Integrating data helps your marketing team segment customers more accurately so it can get deeper and more accurate insights into customer needs and preferences. With access to a higher quality of data, it becomes possible to design more impactful marketing campaigns.
3. Improves Personalization
Having a single source of truth for customer-related issues can greatly improve the customer experience at all stages of their lifecycle. From more personalized marketing to a tailored sales strategy to better customer service.
Today’s complex multichannel marketing systems, combined with options for email, telephone, and social media support, can create challenges for your employees when they’re dealing with customers. An effective CDI strategy brings together data from all those sources so your team members can feel confident they’re always dealing with the most current, accurate data relating to that customer.
4. Enables Customer Journey Analytics
Tracking a customer journey with multiple touchpoints spread across many different channels isn’t easy. CDI tools combine customer data from messaging systems, emails, your Customer Relationship Management (CRM) platform, and other tools into a single customer data platform for analytics and marketing automation.
5. Supports Easier Compliance and Data Governance
CDI can help with data governance by enabling better access control measures, change management processes, data security precautions (such as encryption), and clearly documented processes. Because everything is handled in one central database, data protection measures are easier to implement.
6. Provides a Foundation for Cross-Channel Marketing
The idea of using multichannel or cross-channel marketing is not new, but CDI can make the practice much more effective and increase the ROI on such marketing campaigns. By taking advantage of data available on other platforms, CDI can improve the efficiency of your marketing strategies and give you a view of your customers’ engagement across all the apps and social media platforms they’re using.
The Biggest Challenges of Data Integration
Customer Data Integration presents several challenges, both in terms of data warehousing and collecting and maintaining data accuracy.
Navigating Data Compatibility
The idea of bringing all your data together into one holistic view may seem appealing, but many practical challenges are associated with collecting data from several source systems and displaying it in one dashboard.
While most popular platforms provide APIs for extracting data, configuring these and parsing the exports isn’t always easy. The data must be sanitized and standardized to ensure the central database is accurate. It’s easy to overlook issues such as different numerical formats or even field names that could cause conflicts.
Managing Large Data Volumes
Today, around 60% of corporate data is stored in the cloud. This presents a challenge when planning your customer data integration strategy, as creating the customer database could involve importing huge volumes of data.
To reduce data storage costs, organizations may need to engage in aggressive optimization practices, eliminating redundancies while confirming the accuracy of the data. It’s also crucial to ensure the data is stored and processed in a way that respects GDPR and other data privacy regulations.
Siloed Data's Impact on Business Operations
Data silos can create blind spots where departments are unaware of the bigger picture and, therefore, unable to make accurate decisions. In this respect, CDI has a long-term benefit on an organization’s efficiency and their decision-making ability. However, some stakeholders may be resistant to the idea of data integration out of fear of the short-term impact it could have on business processes. Addressing these concerns prior to starting the data consolidation process is essential.
Overcoming Integration Complexity
Data integration presents several technical challenges, including:
- Limited data availability: For example, an API may only allow a set number of records to be retrieved at once.
- Varying data formats: Different data sources may use different formats or structures for their data.
- Varying data quality: As part of the integration process, your team must determine which data sources are considered most accurate and how to handle conflicting information.
- Mapping data: Maintaining data consistency could be challenging. Mapping data from multiple sources to customer accounts may be an error-prone process.
- Data storage: How much of the data you’re importing do you want to keep? Importing data from multiple sources could consume a significant amount of cloud storage resources.
Ensuring Data Quality and Consistency
Most social media, CRM, and analytics platforms offer an API to help with data exports and processing. However, cleaning and standardizing the data from these platforms can be a time-consuming process.
Some challenges include:
- Differing data formats and structures
- Data quality issues
- Difficulty mapping data across different sources
- Duplicate records
Using data integration tools, it’s possible to automate many aspects of standardizing and cleansing data, removing duplicates, and ensuring information is in a consistent format. This job is made much easier if the original data sources are of a high quality. However, data from mailing list sign-ups, surveys, or other sources that rely heavily on user-provided information could contain many errors or duplicates.
Deciding how to handle conflicts and duplicates is an important part of setting up your CDI systems.
Best Practices for Customer Data Integration
Customer Data Integration is a powerful tool, but it must be used responsibly. When planning your CDI strategy, consider the following:
Establishing a Clear Data Governance Framework
If your organization doesn’t already have a clear data governance framework in place, establish one. If you do currently have a set of rules and responsibilities for data management, review it to ensure it covers your CDI system.
A data governance framework should lay out a set of standardized definitions, guidelines, and best practices for handling data. It should contain rules and procedures to ensure customer data is properly protected, employees take consistent and correct approaches to handling data issues, and data processing is efficient, reliable, and transparent.
Many standard frameworks are available to help organizations define their data governance frameworks, as well as useful data governance tools to help manage your data lifecycle.
Implementing Effective Data Quality Management
Consider the 6 Cs of data quality. Data must be:
- Current
- Complete
- Clean
- Consistent
- Credible
- Compliant
When you’re importing data from multiple sources, much of which was collected by a third party, you may need to perform some sanitization and optimization as part of the integration process. With your own internal databases, you have more control over the data collection process, but with third-party databases, you don’t have this luxury, so you’ll need to evaluate the data closely, consider how to map it, and carefully test any automation systems you plan to use for ongoing data imports.
Types of Data Integration Tools
Data integration platforms can offer great value by streamlining integration workflows and helping you maintain the integrity of your databases.
Some of the top data integration tools include:
- Informatica Cloud: This powerful data integration system with AI-driven features for data quality purposes offers easy cloud integration.
- MuleSoft Anypoint Platform: Easily use real-time data thanks to MuleSoft Anytime’s API integrations. Automate repetitive processes and improve the customer experience for your organization.
- Oracle Data Integrator: A useful tool for organizations already invested in the Oracle ecosystem, ODI offers many easy integrations for popular platforms, such as Salesforce, SAP, Snowflake, Workday, and Shopify.
- IBM DataStage: Another AI-powered data integration platform, IBM DataStage provides distributed data processing and can integrate with IBM QualityStage to resolve quality issues. This tool is ideal for organizations that process huge volumes of data on a regular basis.
- Dell Boomi: This low-code solution makes data integration accessible to a wider audience. The platform supports several popular CRM, sales, messaging, ERP, and other apps out of the box.
Open Source vs. Commercial Solutions
In addition to the solutions listed above, many open-source solutions are available. One popular example is Pentaho Data Integration and Analytics, which offers powerful and scalable data integration features, including tools to automate the process.
Open-source solutions vary from small, independent projects with limited development resources that are available free of charge to larger projects with customer service teams and premium packages available for organizations that want to guarantee support and service level agreements.
If you’re considering using an open-source solution, it’s a good idea to review the project carefully. Confirm that the code has been audited by an independent third party and the project is under active development. Depending on your industry and the type of data you handle, you may need to confirm that the project’s code is compliant with certain data processing and security regulations.
Even smaller open-source projects often have active communities that can assist with bugs and feature requests, and this level of support may be sufficient for a small organization with an IT team familiar enough with that project to handle small issues themselves.
However, commercial solutions also have their place for companies that want a steady update schedule and guaranteed support.
Want More?
CDI has been called “the new CRM” thanks to its numerous benefits. It brings in data from multiple disparate sources and offers a single source of truth for key decision-makers, your sales and marketing teams, and your customer service agents.
When done right, CDI can improve the customer experience and help drive better decision-making within your organization. However, tech leaders must consider many issues as part of a CDI implementation. From planning the integration process to maintaining the security of the database to getting key stakeholders on board, leadership must take a thoughtful yet proactive approach to data integration.
A smooth rollout of the project will make the benefits of data integration clear and help foster a data-centric culture within your teams.
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