Identity Resolution: A Comparative Analysis of Leading Customer Data Platforms
Identity Resolution: A Comparative Analysis of Leading Customer Data Platforms
In today’s digital landscape, data is king. Companies collect vast amounts of data from various sources, including websites, social media, and customer interactions. However, this data is often siloed and fragmented, making it challenging to understand customers and their behaviors comprehensively.
This is where customer data platforms (CDPs) come in. CDPs are powerful tools that help businesses collect, unify, and activate customer data to create a single customer view. One crucial aspect of CDPs is identity resolution. In this article, we’ll compare different CDPs and their identity resolution capabilities to help you choose the right one for your business.
What is Identity Resolution?
Identity Resolution is the process of creating an addressable customer profile by analyzing and resolving data across multiple touchpoints, attributes and systems. Attributes might include email addresses, cookie identifiers, device identifiers, mailing addresses, social media handles and more.
Identity resolution is crucial for businesses as it allows them to understand their customers and their behaviors comprehensively. Companies can create more personalized and targeted marketing campaigns with a unified customer profile, improve customer experiences, and make data-driven decisions.
How Do CDPs Handle Identity Resolution?
CDPs use various methods to handle identity resolution, including deterministic and probabilistic matching.
Deterministic Matching
Deterministic matching is a method of identity resolution that uses unique identifiers, such as email addresses or customer IDs, to match customer data from different sources. This method is highly accurate, relying on a single identifier to match customer data. However, deterministic matching has its limitations. It can only match data if there is a known identifier and cannot handle data from anonymous sources.
Probabilistic Matching
Probabilistic matching is a method of identity resolution that uses statistical algorithms to match customer data from different sources. This method uses data points such as IP addresses, device IDs, and browsing behavior to create a probability score for each match. While probabilistic matching is not as accurate as deterministic matching, it can handle data from anonymous sources and is more scalable.
Heuristic Matching
Heuristic Matching is a method of identity resolutions that applies a different set of rules or sub-algorithms in order of most strict to least strict. Heuristic matching endeavors to align records according to predefined rules established by the business. This approach offers flexibility and enables the application of rules tailored to patterns identified within their data, often unique to their industry.
Comparing CDPs and Their Identity Resolution Capabilities
Now that we understand the different methods of identity resolution let’s compare how different CDPs handle this crucial aspect.
Salesforce utilizes deterministic matching to match and merge customer data from different sources accurately, including email addresses, customer IDs, and device IDs. In addition to deterministic matching, Salesforce provides a feature called “Identity Graph,” which leverages advanced data modeling and machine learning techniques to match customer data from anonymous sources. This includes data points such as IP addresses, browsing behavior, and social media interactions. The Identity Graph enables businesses to create a comprehensive and unified customer profile, even for customers who have not provided explicit identifiers.
Adobe provides identity resolution capabilities through deterministic and probabilistic matching techniques. They match customer data at various levels, including household, person, address, email, URL, and account, ensuring comprehensive data alignment. Adobe leverages probabilistic matching by searching for signals and calculating the probability of a match using attributes or identifiers. They also utilize heuristic matching to apply custom rules for generating or excluding matches based on specific criteria. As part of their commitment to innovation, Adobe plans to leverage AI/ML techniques to enhance their identity resolution capabilities further.
Action IQ offers robust identity resolution capabilities using deterministic matching. They match customer data from various sources, including email addresses, customer IDs, and device IDs. Action IQ also enables cross-device identity resolution through probabilistic matching, allowing businesses to track customer interactions across different devices and browsers. This holistic view enhances understanding of customer behaviors and preferences.
Redpoint employs deterministic, probabilistic, and heuristic matching techniques for comprehensive identity resolution. They match at various levels like household, person, address, email, URL, and account. Their approach includes signal-based probabilistic matching, custom rule-based heuristic matching, and a commitment to leveraging AI/ML for stronger resolution. Redpoint ensures accurate linking of identity fragments using known identifiers and supports additional data activation through collaboration. They offer flexibility, but precision may vary depending on implementation.
Comparing CDPs and Their Identity Resolution Capabilities
When choosing a CDP for your business, it’s essential to consider your specific needs and goals. Here are some factors to consider when comparing CDPs and their identity resolution capabilities:
Data Activation
Data activation is using customer data to create personalized and targeted marketing campaigns. When comparing CDPs, consider how each platform handles data activation and whether it aligns with your business goals.
Data Platforms
CDPs can integrate with various data platforms, such as CRM systems, marketing automation tools, and data warehouses. When comparing CDPs, consider which data platforms each platform can integrate with and whether it aligns with your existing tech stack.
Customer Support
When choosing a CDP, it’s essential to consider the level of customer support each platform offers. Look for platforms that provide 24/7 support and have a dedicated customer success team to help you get the most out of the platform.
Pricing
Pricing is another crucial factor to consider when choosing a CDP. Some platforms offer a flat monthly fee, while others charge based on the number of customer profiles or data points. Consider your budget and choose a platform that provides the best value for your money.
Conclusion
Identity resolution is a crucial aspect of CDPs, as it allows businesses to create a unified customer profile and gain a comprehensive understanding of their customers. When comparing CDPs, consider their identity resolution capabilities, data activation features, data platform integrations, customer support, and pricing to choose the right platform for your business.
While CDPs excel at managing and consolidating customer data from various sources, their identity resolution capabilities may not always meet your specific business requirements. Therefore, it’s essential to have a comprehensive understanding of your data and unique needs to assess whether your business can benefit from more advanced identity resolution technology. This could be with an Identity Resolution Platform (IDR), dedicated to resolving and integrating customer identifiers effectively. Integrating an IDR with your CDP can significantly enhance your data management and activation capabilities.
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