Everything you need to know about customer data integration (CDI)
With so much customer data available in modern, tech-driven industries, it can feel overwhelming to properly assess and analyze which information provides value and which can be discarded.
Organizations today struggle to justify data retention for information that doesn’t have a current use but which might be needed in the future. The higher cost of storage and investment of time required to sort that data before it can add value are reasonable justifications for deletion over retention.
Customer data integration (CDI) works to help organize and sort gathered customer data into a usable infrastructure. It also helps make use cases clearer and the data easier to use when they arise.
In this guide, we’ll cover:
- What customer data integration is
- Types of customer data integration
- Best practices
- How to get started
What is customer data integration?
Before we discuss details and best practices in more detail, we must define customer data integration and acknowledge the wide variety of sources that provide customer data.
Modern enterprises gather consumer data from:
- Email engagement
- Website visits
- Page behavior
- Time to purchase
- Purchase per click
- App downloads, behavior, and usage
- Push notification settings
- Purchase details
Consumer data integration is a series of protocols and processes that combine and organize customer data from multiple sources. CDI connects with multiple databases and imports the information into a single silo.
Information gathered in one place is easier to manage, access, and secure. Even more importantly, customer data gathered in one place enhances the organization’s ability to analyze and visualize the data — and do so in minimal time.
CDI is a crucial component of any business strategy that seeks to make decisions based on consumer behavior. Without CDI, it’s nearly impossible to build an overall data management strategy. Fragmented information gathering that operates across silos and servers causes business leaders to make decisions based on incomplete data.
Instead, leaders can make more informed decisions since CDI provides them with every piece of relevant information the company has gathered. The company can then operate with increased business intelligence and improve its navigation and flexibility in an ever-changing market. It can identify pain points in real time and take steps to correct them.
This system also provides the company with a full view of a customer’s journey in one place. Employees can gather necessary information about a particular customer at a glance rather than scour each silo to obtain the needed data.
Businesses can therefore use that data to improve the overall customer experience. With a complete view, the company can provide exactly what the customer needs.
Types of customer data integration
There are three types of customer data integrations. Each type has its pros and cons that companies must consider when they choose a CDI model.
While consolidation is the most common CDI type, variations in business model, size, and need may change which model is the best option.
Consolidation serves most organizations’ CDI needs, and they choose consolidation models more often than any other type. This straightforward CDI setup makes it easy to standardize data, maximize functionality, and break down silos.
Larger data volumes can drive up the cost to unmanageable levels. Fortunately, only the largest organizations gather enough data for volume to produce cost issues.
Smaller, growing businesses that currently collect less data stand to gain the most from a propagation model. This type of CDI replicates the data to share information between two or three tools, such as marketing automation services and customer relationship management.
Since propagation does not integrate and collate gathered data into a single source, it is more useful for companies with only one or two data sources.
Federation has a rare use case — when data consolidation becomes too expensive. It has the most complex setup of any of the three types because it makes no changes to data until a user requests it. The CDI system then reviews all gathered data to find and organize the information relevant to the user request and provide it.
Few businesses need to justify the cost of a federation setup. Only those that work with truly massive data sets should consider this option.
Benefits of customer data integration
There are many benefits to integrating customer data. CDI combines data across customer service departments and eliminates the need for redundant data entry. Removing redundant entries also minimizes discrepancies between silos.
Here are some of the benefits of customer data integration.
Removes data silos
Many different departments handle aspects of customer service, and while the data should be cross-functional, it often isn’t accessible to all teams.
Centralizing data gives all departments the ability to access all parts of a customer’s profile, eliminating the data silo.
CDI allows companies to remove duplicate and outdated user profiles and correct any inaccuracies. It ensures that all data gathered about a particular customer is updated and accurate — and that automated systems do not gather information more than once and waste resources.
Ensures accurate data
Many platforms for CDI are automated, which eliminates manual data entry, mitigates human error, and ensures that all entered information is as accurate as possible.
With one access point for all data, a business has only one database that it needs to protect. As an added benefit, that single access point means the customer data needs one update from one platform rather than multiple updates scattered across department silos. All staff can see the update as it happens.
Easier data management
Ultimately, CDI makes data management easier. Once implemented, updating customer records and consolidating information is easy. Adobe Real-Time Customer Data Platform, one of the top customer data solutions, is capable of updating gathered data and providing insights in real time.
Challenges of customer data integration
Like any other platform, implementing customer data integration does have some challenges. These include:
Retaining historical data
Most companies must retain information after its use case expires for regulatory reasons. A lot of historical data is missing relevant information like dates and lacks the same thorough profile as more recent records, which makes it more difficult to organize.
Managing a multitude of data sources
The constant data flow from multiple sources is often presented differently than the way CDI organizes and lists information. Data managers may have to manually verify that new data is integrated correctly. Staff and other resources spent on verification come at a cost that can reduce the overall return on investment of CDI.
With an enormous variety of CDI platforms available, even something as simple as choosing a provider can be overwhelming. Businesses must carefully consider, organize, and prioritize their needs as they make a choice.
Customer data integration best practices
These guidelines ease the implementation process and ensure that after setup, the CDI platform can continue to operate without issue.
Create a data tracking plan
Data silos can limit ease of operation, but they do provide an essential service: organization. Multiple sources of data connected together can create a large mess of information that swells into an unsorted data lake. Careful organization, tracking, and planning to ensure data is securely sorted and accessible ensures the CDI adds the promised value.
Assign a “data boss”
A data boss is a single person who manages the whole CDI process. With one person or a small team reducing human points of error, failures occur less frequently. That person should also understand and be assigned to the company’s data management and tracking plan.
Regularly audit data
Regular audits ensure the data gathered is relevant to current or future needs. If not, it can be deleted safely. Audits also detect redundancies and remove them to maximize the efficient use of storage space.
Automate whenever possible
Automation removes manual errors in data entry. The larger the volume of data, the larger the chance of human error. Companies that deal with high volumes of data must automate as much as possible to ensure accuracy.
While some of these best practices may seem expensive or difficult to implement, all provide a direct benefit to the organization. CDI optimization ensures data collection integrates with other systems as seamlessly as possible.
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Overall, customer data integration eases the information-gathering and organization process. It removes several barriers to entry for data use — including redundancies, inaccuracies, and security risks — and creates a single, consolidated point of storage that eliminates data silos and makes information easier to manage.
CDI also improves the human element. As an organization establishes a system to integrate consumer data, it designates individuals to handle data issues. These teams conduct regular audits, upgrade automation solutions, and monitor data security.
By now, you should have a deep understanding of the purpose, functions, and importance of CDI systems, along with the benefits and challenges they bring.
Some solutions do more than just provide information. Adobe Real-Time CDP collects, normalizes, and unifies known and unknown individual and company data into robust customer and account profiles — which automatically update in real time. Marketers can use these profiles to deliver timely, relevant, and personalized experiences to any channel at scale. And with best-in-class usage governance, brands can use data more responsibly and transparently, so consumers have greater control over their information.