Customer Data Integration: Best Practices and Tips for Business

Nowadays, B2B companies are well used to gathering colossal amounts of data through their various contact channels. However, possessing data doesn’t immediately translate into customer-oriented insights. That's where customer data integration (CDI) comes in.

Customer data continues to be the fuel that propels the engines of B2B companies around the globe. According to a ReportLinker analysis, the global data integration market reached the $12.14 billion mark in 2022, and it is expected to continue growing up to $19.09 billion in 2026.

A McKinsey report shows that B2B companies that effectively harness data analytics in service to marketing and sales performance are 1.5 times more likely to achieve above-average growth rates than their competitors.

That said, many B2B marketing teams still struggle to make the most out of their collected customer data. The Salesforce State of Sales Report claims that 72% of the surveyed B2B sales reps feel unable to extract meaning from data. A big reason behind this is related to the absence of a clear view of all the assembled customer-based information.

Customer data integration helps companies to create a single source of all the collected data, which can be filtered and accessed depending on the interest of each team member. Keep reading to learn more about the concept of CDI and the best practices to simplify it. 

What Is Customer Data Integration?

Customer data integration can be defined as the process of gathering, combining, and managing customer-based information from multiple data sources across all the organization's business systems into a single, unified view. 

This complete perspective of all the customer data owned by a certain company allows it to gain a deeper understanding of the customer experience inside its pipelines, which translates into valuable insights that can help each department make better decisions.

The CDI includes contact details, customer valuation data, information accessed through direct marketing interactions, and more. This unified view also helps businesses stay compliant with various data privacy regulations, such as GDPR and CCPA, as it ensures that customer data is securely stored.

The main objective of customer data integration is to provide companies with a 360-degree overview of all their customer-based data in a single screen. B2B sales and marketing teams can leverage this “golden record” to focus on the most profitable prospects, saving time, energy, and budget.

Customer Data Integration Benefits

The perks of deploying customer integration are numerous. By combining customer data from multiple sources, businesses can provide a better customer experience, as they can tailor their products, services, and marketing messages to the specific needs of their customers. 

Here are four top benefits of applying customer data integration strategies to your business:

1. Reduces data silos

A data silo can be understood as a conglomeration of data that is controlled by a specific department and becomes isolated from the rest of the company. In most cases, data silos occur unintentionally as departments leverage specialized tools, systems, and processes. Nevertheless, incompatible data sets may cause an internal disorder.

Through CDI good practices, B2B companies can access the complete view of all the data collected by every business unit. By matching data-based insights from all active departments, it is possible to learn what campaigns, messages, and triggers are luring the most profitable customers, and which efforts are failing to meet expectations.

2. Increases data security

The confidentiality of customer data is boosted when a single data access point is managed by decision-makers inside the company. While the totality of customer data is displayed in one place, a customer integration platform allows data managers to restrict the usage of information for each team member.

This way, you make sure all employees have access to only the data they need to perform their daily operations. Also, it becomes easier to grant or remove data-analytics faculties from workers that enter or exit the company without jeopardizing sensitive information.

3. Ensures data accuracy

Data freshness is vital for any successful data-based lead generation effort. CDI tactics help B2B marketing and sales teams conduct data segmentation effectively. This means that prospect records can be continuously updated, and traits such as industry, budget, location, and technology usage can be used to narrow down your target market.

Without a customer integration plan, companies may fall victim to data decay, which occurs when the quality of B2B databases deteriorates and sales development representatives (SDRs) are forced to work with inaccurate, incomplete, or outdated customer information, making their work a lot harder.

4. Predicts customer behavior

When a target audience is analyzed through an organized, solid data-based structure, marketers and sales representatives are able to identify new opportunities on how to engage prospects that are similar to other successful cases.  

CDI can help B2B companies by identifying their ideal customer profiles (ICPs), pinpointing target account lists out of prospect records, and forecasting a positive outcome if all the right ingredients are mixed in a prospecting campaign.

Types of Customer Data Integration

CDI can be achieved through a number of techniques. Deciding which one is the most adequate for your company depends on how much data has been collected over the years, how well-organized your databases are, and how many platforms are used to process different sets of data.

These are the three main types of data integrations that businesses can use to unify their data records:

1. Data consolidation

This is the most efficient type of data integration. Data consolidation takes in multiple sources of information and combines them into a centralized data warehouse. When performed through a CDI tool, it is possible to automate the extraction and placement of data from one platform to another. By standardizing data integration, its usefulness is maximized.

2. Data propagation

Data propagation is the process of creating a copy from a data set. This means that the same data will live in the original source but will also be available in a new destination. The system is useful when companies want two separate lead generation tools running on the same data but focusing on different aspects of the cycle. That said, this situation also fosters the creation of data silos that could negatively affect valuable insights.

3. Data federation

The technique is similar in appearance to data consolidation. Data federation allows the user to have a unified view of all the available data. The difference is that data federation keeps data sources segregated, making it harder to dissect, manage, and customize the information with total freedom. 

10 Customer Data Integration Best Practices

New customer data enters sales pipelines at every moment. For that reason, CDI must be considered an open-ended activity that requires a solid structure to correctly organize and display all the necessary data.

The following list of best practices for CDI will help your team get the most out of this methodology:

1. Identify your data sources.

Every single interaction with clients gives away a piece of the prospect-profiling puzzle. Email responses, transactions, content reviews, filled forms, and direct messages are great places to look for customer data. While not all data sources will be equally valuable, the sum of them can help marketers craft ICPs and buyer personas.

2. Define data-driven objectives.

Think of data as a wild beast that needs to be tamed. Without a clear idea of what your company expects to get out of CDI, the data exhaust will be too vast to provide practical results. Setting up the metrics for both short and long-term objectives is like building dams for your data stream to fill up.

3. Choose your implementation plan.

Processes and rules are key elements for successful CDI strategies. Selecting between data consolidation, propagation, or federation will have a major impact on how your data is distributed. Once a path is chosen, turning back is often an expensive and time-consuming alternative.

4. Select your data users.

Find out what team member needs to access what database. This step is crucial to narrow down how you want to structure your data. Once all customer data is inside your data warehouse, filters and categories need to be added so everyone can manage the data they want as effortlessly as possible.

5. Assign a data boss.

This is not necessarily a C-level, decision-maker. The data boss will be in charge of granting and denying access to your customer database and protecting it at all costs. This position involves an enormous level of responsibility and should be offered to someone with great data management skills but is also closely related to the company.

6. Future-proof your integration.

Program your CDI plan for the long haul. While short-term responses are important for fast-paced actions, the more data you integrate will lead your team to sound, profitable results. For this reason, it is wise to deploy advanced tools, rules, and locks that can be edited without a derailed amount of effort from the very beginning.

7. Confirm your security locks.

While CDI tools provide a single access point for all customer data, you will still need to program security locks during the implementation. Make sure that the most sensitive data remains only available to the people in charge of it using secure data containers. This way, you prevent any dangerous data breaches and leaks.

8. Audit your data routinely. 

Confirming the accuracy of your databases is vital to coming up with real insights. Running a constant analysis of the old and newly collected data allows your team to work with relevant information at all times. 

9. Generate practical reports.

Once all your customer data is set and active, it is time to make it work for you. Gather all the managers involved in pipeline growth and determine what types of reports they need to boost their strategies, uncover new market opportunities, and confirm what efforts are proving to be successful. 

10. Leverage customer data integration tools.

A CDI platform simplifies the collection, combination, and distribution of customer data. They can be automatized to perform constant audits for all data warehouses, scrubbing incomplete, outdated, and repeated records. They also optimize data management operations by categorizing the information required by each user, allowing them to have a clean view of all the customer data they need to perform their daily activities.

Customer Data Integration Tool: CIENCE GO Flow

CIENCE GO Flow is a customer data integration software designed for sophisticated, data-powered sales and marketing teams. The GO Flow tool can stream or send data in micro-batches (up to 1x per minute). Each data event related to all anonymous users can be updated in data warehouses with unique, individual user IDs.

By setting up pre-established rules in the platform, the CIENCE GO Flow streamer can deliver data batches to multiple destinations at the same time. All incoming events are automatically saved to JSON logs, either locally or to the cloud. This means that new destinations can be added and then loaded with replay data in a very simple manner.

Benefits of CIENCE GO Flow

GO Flow automatically resolves, identifies, and enriches your visitor-based event data and any contact data flowing to your downstream marketing and sales stack. All you have to do is to select your framework, add a few lines of code to your website or app, and then watch data being transferred between one source to your preferred destination.

The GO Flow engine automatically creates your sales and marketing data warehouse so your data can be queried instantly. Additionally, your data can flow to other services (HubSpot, Google Analytics, Amplitude), call any HTTP application programming interface (API), or integrate all the advertising pixels you need.

CIENCE GO Flow can enrich your data from over 140 external services, helping you to generate 100% accurate user profiles. CIENCE GO Show can also be integrated to determine the underlying online contacts visiting your website in real time.

CIENCE GO Flow key features: 

• Retroactive user recognition
• Automatic data replay
• Multiple destinations at the same time (multiplexing)
• Easy-to-use web interface
• Data-handling privacy compliance

Leverage CDI to Enhance Your Customer Experience

Customer data integration is an increasingly important process for B2B companies to stay competitive and compliant. The current state of the B2B buyer's journey demands marketers and SDRs to have a clear idea of their prospects' demands even before they are mentioned. And that is only possible through CDI analytics.

By owning a unified view of all the elements that integrate the clients' behavior, businesses deploying CDI practices have a greater opportunity to identify their prospect’s expectations and design engaging campaigns that may provide their target audience with exactly what they are looking for.