What is identity resolution?
Companies leverage identity resolution to collect and integrate information from a range of sources to build a comprehensive customer profile. Such profiles are key for delivering personalized experiences that resonate with individual consumer preferences and behaviors.
When businesses interact with consumers, they gather data across multiple channels and touchpoints, from social media interactions to transaction histories on e-commerce platforms.
Identity resolution takes these disparate data pieces and merges them, creating a single, cohesive view of each customer – so that businesses can understand their customers more deeply, tailoring interactions and offerings to meet unique needs and preferences.
Personalization is still a core focus
Personalized experiences have become the foundation of modern consumer expectations. Studies show that tailored experiences can boost engagement, increase customer loyalty, and drive revenue growth.
For instance, a survey reveals that customers are more likely to purchase from brands that recognize them by name, know their purchase history, and provide recommendations based on past purchases.
The process of identity resolution involves sophisticated technology and methodologies to accurately merge data while ensuring privacy and compliance with regulations. The ultimate goal is to achieve a 360-degree view of the customer, which is a linchpin for crafting personalized experiences that captivate and retain customers in today’s competitive business environment.
Key insights from identity resolution
Identity resolution crafts a comprehensive customer profile by aggregating and analyzing data from numerous sources. When businesses understand their customers’ behaviors, preferences, and needs in depth, they can tailor their interactions more effectively, resulting in a more engaging and satisfying customer experience.
Developing a comprehensive customer profile
A unified customer view emerges from the meticulous integration of data points such as purchase history, online behavior, device usage, and personal preferences.
For instance, a business might observe that customers who browse their website via mobile devices tend to prefer certain product categories. This insight can inform mobile-specific content or offers, enhancing the relevancy of the business’s engagement with these customers.
The process involves sophisticated data analysis techniques and technologies that sift through and make sense of vast datasets. Such comprehensive profiles enable businesses to understand not just the ‘what’ but the ‘why’ behind customer behaviors, empowering them to anticipate needs and tailor their offerings accordingly.
Facilitating targeted marketing and personalized experiences
With a complete view of the customer, businesses can execute marketing strategies that are highly relevant to each individual. For example, if data reveals a segment of customers who frequently purchase eco-friendly products, the business can target these customers with campaigns focused on sustainability.
Data shows that customers respond positively to personalization, with 71% of consumers expecting personalized interactions, and 76% get frustrated when this expectation is not met.
Personalization now reaches beyond marketing and encompasses the entire customer journey, from personalized recommendations on e-commerce platforms to customized support experiences.
Understanding the identity resolution process
Sources like browser activity, purchase history, and personal information contribute to a vast dataset that businesses need to consolidate to form a coherent customer profile. Each data source provides a unique piece of the puzzle in understanding customer behavior and preferences.
For example, browser activity can reveal a customer’s interests and engagement level, while purchase history offers concrete insights into their buying patterns and preferences.
Laws such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States mandate strict guidelines on how companies can collect, store, and utilize customer data.
These regulations are set to make sure that customer privacy remains protected, but they also require businesses to implement robust systems and processes to remain compliant. For instance, a company must obtain explicit consent from customers to track their online activities, adding a layer of complexity to collecting and integrating browser activity data.
The impending phasing out of third-party cookies, a change led by industry giants like Google, is further set to disrupt how businesses collect and use customer data.
Third-party cookies have traditionally allowed businesses to track users across different websites, providing valuable insights into their broader online behavior. With these cookies disappearing, companies must find new ways to collect data, emphasizing the importance of first-party data and direct interactions with customers.
Tools and software for identity resolution
Core features of identity resolution platforms
Identity resolution platforms offer a suite of tools designed to tackle the complex process of unifying customer data. Data onboarding is a major feature whereby customer information from various sources undergoes ingestion and integration into a centralized system. This process ensures that data, whether from online interactions or offline engagements, is accurately and securely transferred, laying the groundwork for a unified customer view.
- Identity graphs: Identity graphs act as dynamic databases that connect an individual customer’s data points across different channels and devices. These graphs are intricate maps of customer identities, linking disparate data like device usage, online behavior, and transaction history to create a cohesive identity profile.
- Real-time matching: Real time matching is where the system continuously updates and synchronizes customer data. This capability ensures that the customer profiles are always current, reflecting the latest interactions and transactions. Real-time processing is crucial for businesses to react promptly to customer needs and preferences, enabling more dynamic and responsive engagement strategies.
- Compliance features: These platforms address the growing concern and necessity for data privacy and security to ensure that businesses adhere to strict regulatory standards, safeguarding customer information and maintaining trust.
Data Warehouses and Customer Data Platforms
Data warehouses (DWHs) and customer data platforms (CDPs) play distinct yet complementary roles in the ecosystem of identity resolution. A data warehouse acts as the repository for vast amounts of structured and unstructured data collected from various sources. In the context of identity resolution, the DWH serves as the initial consolidation point where raw data begins its transformation into actionable insights.
The role of CDPs in identity resolution is more nuanced and direct in enhancing customer understanding. These platforms take the consolidated data from DWHs and apply advanced algorithms to perform deterministic and probabilistic matching. Deterministic matching offers precision by linking customer data points using unique identifiers, such as email addresses or phone numbers, ensuring high accuracy in profile creation.
On the other hand, probabilistic matching employs statistical models to infer connections between data points in the absence of unique identifiers, useful in broader analysis scenarios but with a margin for error.
Applications and benefits of identity resolution
Identity resolution plays a key role in crafting a seamless customer journey across multiple platforms. Businesses that implement identity resolution effectively can offer consistent and personalized experiences, which are instrumental in boosting customer engagement and fostering loyalty.
For instance, when a customer interacts with a brand through various channels such as mobile apps, websites, and physical stores, identity resolution helps in stitching together these interactions.
As a result, businesses can provide a coherent and customized experience, acknowledging the customer’s preferences and history with the brand. Enhanced engagement through personalized experiences leads to increased customer satisfaction, repeat business, and a higher likelihood of referrals.
Optimizing marketing campaigns
When marketers have a unified view of the customer, they can design campaigns that are highly relevant and targeted, avoiding the pitfalls of misclassification.
When a customer is incorrectly identified as a new prospect, they might receive offers and communications meant for first-time customers, which can lead to frustration and a sense of being undervalued.
Accurate identity resolution prevents such scenarios, ensuring that marketing efforts are directed appropriately, thereby maximizing the effectiveness of campaigns and optimizing resource allocation.
Gaining insights into customer behavior
Identity resolution provides insights into the behaviors and preferences of both existing and potential customers, offering a rich source of insights for businesses. Aggregating data from various touch points helps companies form a comprehensive view of customer interactions, even for new or unregistered users.
Such insights are invaluable for businesses looking to understand the pathways customers take before making a purchase, their browsing habits, and the factors influencing their decision-making.
Companies can then apply this knowledge to tailor their strategies, products, and services to better meet customer needs and anticipate market trends. Insights gained from identity resolution can guide businesses in identifying potential areas for growth and innovation, ensuring they remain competitive and responsive to evolving customer expectations.
Implementing identity resolution
Implementing identity resolution requires a methodical approach, focusing on the selection of an appropriate vendor and adherence to a structured process. Businesses aiming to leverage identity resolution must make informed choices, considering their specific needs and the capabilities of potential solutions.
Vendor selection
Choosing the right vendor is a decisive step in the identity resolution implementation journey. Companies need to assess the vendor’s technology, expertise, and compatibility with their existing systems. Key considerations include:
- Data integration capabilities: The vendor should offer robust solutions for integrating data from diverse sources, ensuring a comprehensive view of customer interactions.
- Matching accuracy: Evaluate the vendor’s ability to perform deterministic and probabilistic matching, prioritizing those with advanced algorithms for accurate customer identification.
- Compliance and privacy: Ensure the vendor adheres to data privacy regulations, providing features that respect customer consent and data protection laws.
- Scalability: The chosen solution must scale with your business, accommodating increasing data volumes and complexity.
- Support and collaboration: Opt for vendors known for their customer support, offering guidance and assistance throughout the implementation process.
Structured implementation process
After selecting a vendor, businesses should follow a structured process to integrate identity resolution into their operations:
- Data audit: Conduct a thorough audit of available data sources, identifying all potential inputs for the identity resolution system.
- Goal setting: Clearly define what you aim to achieve with identity resolution, setting measurable objectives to guide the implementation.
- System integration: Work closely with the vendor to integrate the identity resolution platform with existing systems, ensuring seamless data flow and functionality.
- Testing and validation: Before full deployment, test the system to validate data accuracy and the effectiveness of the matching algorithms.
- Employee training: Ensure team members understand how to use the new system, emphasizing the benefits and changes to their workflows.
- Continuous monitoring: Regularly monitor the system’s performance, making adjustments as needed to maintain data accuracy and relevance.
