5 Best Practices for Customer Data Integration

In today’s digital world, data integration is essential to make different data sets work together smoothly and efficiently. It creates a ‘single source of truth (SSOT)’ by combining data from multiple sources, all the while breaking company-wide data silos. If performed correctly, it ensures that all business divisions have continuous access to the most up-to-date data. Customer data integration takes this a step further by specifically focusing on harmonizing and streamlining customer information from various touchpoints.

But what exactly is customer data integration?

This blog explores this concept in detail and further examines its key benefits and challenges. Moreover, it lists a few best practices to help you simplify customer data integration.

What is Customer Data Integration?

Customer data integration is combining and managing customer data from many places in a single location. This data may include contact information, customer financial data, data collected via marketing activities, etc.

Customer data integration helps provide a holistic view of all customer data. The process also includes validating and enriching customer information to provide better insights.

CDI gives you a 360-degree view of customers, including a complete picture of their buying preferences, location, and other details. This view is helpful for both marketing and sales teams, as it helps them relocate their efforts to the most profitable area.

Why is Customer Integration Important?

Here’s how customer data integration can benefit your business:

·       Identify New Opportunities

You can identify opportunities to launch new products or modify existing ones by analyzing customer data. For instance, you want to sell your existing product to prospective consumers with lower disposable income. CDI can help you pinpoint the marketing leads within that specific budget range. This way, you can decide if it is favorable to make a lower-cost product.

·       Reach Out to a Targeted Audience

Customer data integration helps you improve your sales and customer experience by helping you analyze customer preferences and behavior patterns and marketing your product(s) accordingly. This saves you from the time-consuming process of targeting customers based on guesswork.

·       Forecast Prospective Sales and Industry Trends

By getting in-depth customer insights, you can forecast future sales trends. By analyzing past and existing customer information, you can stay ahead of the industry trends and plan for consumer demands ahead of time.

Challenges in Integrating Customer Data

Collecting information from disparate sources and transforming it into a simple, unified format is one of the biggest challenges in CDI.

Here are some other challenges you might encounter during the customer data integration process:

·       Developing a Robust Integration Plan

When implementing a customer data integration strategy, the main challenge is integrating data from different customer channels. Given that it is in different formats, standardizing it becomes a challenge. An integration platform that offers built-in connectors for disparate source systems can streamline this task.

Salesforce is considered one of the best Customer Relationship Management (CRM) software. But to extract insights from your customer data from Salesforce, you will need to visualize it. Learn how to create a 360-degree view of customer data using the Salesforce connector.

·       Handling Large Data Volume

Businesses must manage large volumes of customer information to make critical data readily available to decision-makers whenever needed. However, accumulating, managing, and creating value from large data volumes is challenging.

Also, the growing number of devices and platforms and the constantly declining storage cost have made it trickier to manage and remove historical data from legacy systems. As a result, there’s an unexpected need for high performance and storage capacity.

To tackle this challenge, you’ll have to anticipate the extent of your business growth and the customer information that must be integrated.

·       Protecting Customer Data

Maintaining the privacy of sensitive customer data is challenging. Identifying and avoiding data breaches and recovering lost data yields huge costs. Plus, the loss of critical data can devastate businesses. This can bring about several other challenges, like losing customer trust and funds due to plummeting sales. It may also tarnish the reputation of your business.

So, focusing on averting cyber-attacks ensures the safety of customers’ personal information by implementing data security measures. You can use one of the best data integration platforms to make your work easier. These data integration tools have the right features to make integrations easier by cleansing and transforming data in a staging area.

Application of Customer Integration

Customer integration can benefit various business departments, such as:

• Marketing: 360 customer integration can help the marketing department push relevant content and advertising to targeted segments.
• Sales: The sales department can benefit from customer integration by improving lead conversion and reducing the time spent on poor prospects.
• Production: Production can benefit from vendor-customer integration by tailoring the production to demand and minimizing wastage.
• Logistics: Logistics department can take advantage of customer integration by improving the delivery and fulfillment services according to real-time feedback.
• Finance and Accounting: 360 customer integration can help the finance and accounting department minimize spending on less effective front-end processes.

Best Practices for Integrating Customer Data

Here are four best practices that’ll help you steer clear of the challenges associated with customer data integration:

1. Identify the Source Points

The first best practice is identifying the source systems from which you need to extract data and finding a solution that supports those sources. You can use an enterprise-grade tool, preferably one with built-in connectors that also allows you to build no-code data pipelines, to extract your customer data without writing any code.

2. Outline Data Categories and Allocate Access

Classify who can access your customer information and why. Particularly, recognize who will be responsible for the integration process and their job. Will it be IT experts, business users, or a completely different team? This will help protect the sanctity of integrated customer data.

3. Define Integration Goals

Outline your organization’s motives for integrating consumer information, and establish metrics to monitor and measure whether your business is meeting those objectives.

4. Decide an Implementation Plan and Timeline

Decide the processes and rules to be used in your CDI strategy. This will include data governance, quality, and protection.

The timeline will depend on the kind of tools you use. An advanced tool will help you restructure the timeline, and the integration technique you choose will command the order followed by the process.

Commonly used data integration types include data consolidation, data propagation, data federation, and data warehousing.

5. Continuous Monitoring and Improvement

Once a plan is implemented, continuously evaluate data integration processes and outcomes. Monitor performance metrics, identify areas for improvement, and implement enhancements to optimize workflows.

Solicit feedback from data analysts, measure the impact of data integration, and iterate on the processes to drive continuous improvement.

Ready to Start Customer Data Integration?

With an improved understanding of customer data integration’s advantages, challenges, and best practices, you can choose a data integration tool and get a clearer view of your consumers.

Astera Centerprise is an enterprise-ready, end-to-end data management software that allows you to integrate, clean, and transform your data – all without coding. It has all the essential features you need to kick-start your CDI project, combine heterogeneous data sources, and produce a 360-degree view of your customer data.