Develop consolidated, complete profiles of customers that will never be sensitive to fluctuation or under-merging. Use AI to develop behavior-enabled and predictive profiles for anonymous and known users.
Identity Resolution Services for Customer Journey Mapping
Convert different customer records into broad customer profiles.
Industry-based Solutions
Express Analytics lets businesses find and resolve the identities of individuals across different platforms and sources. Using dynamic capabilities, organizations can create a consolidated, cross-channel view of their customers.
Ideally, clients can combine identity graphs from various data providers and receive complex entity resolution and identity matching to support data-enabled strategies with enriched, reliable customer profiles for improved personalization, outstanding customer experiences, and more fruitful marketing campaigns.
Technology providers
- Resolve audience identities across various platforms, devices, and channels to develop more complete and specific user profiles.
- Deliver more customized advertising content and marketing messages, resulting in greater engagement, ROI, and conversion rates for your clients.
Data providers
- By developing complete and error-free customer profiles via ID resolution, data providers can offer valuable data products to their customers.
- Providers can conduct modern analytics, including predictive modeling, multi-channel attribution, and customer journey analysis.
- This lets them extract detailed insights from their data and provide complex data-based solutions to their customers.
Media companies
- By finding users across sessions and devices, they can offer constant experiences, including remembering the preferences of users, providing suitable content recommendations, and maintaining reading development across devices according to user behavior and interests.
System integrators
- By expanding solid identity resolution features and providing modern data integration, analytics, and customized solutions, system integrators set themselves apart in the position and market as superior providers of data-based digital transformation services.
Win new customers with customer journey mapping
Identity Resolution Features
Why Express Analytics?
- Simply integrate data sources
Having a centralized view of data from different sources allows responsiveness to ever-changing customer demands and market conditions. - Re-establish performance with enhanced match rates
Greater match rates allow better targeting and identification of customers across different devices and channels. This results in greater customer satisfaction, engagement, and conversion rates. - Keep control of data
We don’t store your data and provide the latest governance features, support cloud deployments across different regions, and version control. - Self-service users and analytics for marketers
Allow marketers with journey orchestration, visual audience building, and analytics over the data warehouse – all without writing a line of code.
Lets Connect
What can we address
We are one the US-based identity resolution providers, who are capable of addressing the following challenges:
1. Shattered customer view
Without an identity resolution solution, unifying and combining audience data from different platforms and sources becomes challenging.
This results in an incomplete view of the user journey, hampering targeting and personalization efforts.
2. Incorrect measurement
The absence of ID resolution hampers marketers’ capability to perfectly measure the productivity and attribute conversions of their marketing efforts. This results in poor decision-making as marketers don’t have clarity on which techniques, touchpoints, and channels are yielding expected results.
3. Unstable customer experiences
Without ID resolution, it’s not easy to provide constant, uninterrupted experiences across platforms.
Our Capabilities
What Questions Does the Customer Identity (Identity Resolution) Resolve for Clients?
- Who is the customer across different channels?
- Is this the same customer or different individuals?
- What are the customer’s behaviors and preferences?
- What is the customer’s journey across touchpoints?
- What is the customer’s engagement with the brand?
- What is the customer’s value to the business?
- Which communication channels does the customer prefer?
- Are there any data inconsistencies across systems?
- How does the customer interact across devices?
- Is the customer likely to churn?
To get answers to these questions, fill out this contact form.
- Who is the customer across different channels?
Helps identify the same customer across multiple channels, devices, and platforms.
Example : John Doe uses both a desktop and a mobile device to interact with the brand, but both are linked to his unified profile. - Is this the same customer or different individuals?
Resolves duplicate records by merging customer data from multiple sources into a single profile.
Example : John Doe and Johnathan Doe are recognized as the same person despite having different email addresses. - What are the customer’s behaviors and preferences?
Provides insights into customer behavior, such as preferred communication channels and browsing habits.
Example : John prefers shopping online on his mobile device, and he interacts most with promotions sent via email. - What is the customer’s journey across touchpoints?
Tracks how customers move from one touchpoint to another, enabling seamless customer journeys.
Example : John browsed winter jackets on his laptop, added one to his cart on his mobile device, and completed the purchase in-store. - What is the customer’s engagement with the brand?
Shows how customers engage with the brand through different interactions, including emails, ads, and purchases.
Example : John frequently clicks on Facebook ads and opens promotional emails related to winter clothing. - What is the customer’s value to the business?
Provides insights into the customer’s lifetime value (CLTV) and potential for future transactions.
Example : Based on John’s purchase history and engagement patterns, his CLTV is estimated at $3,000. - Which communication channels does the customer prefer?
Helps businesses understand which channels (email, social media, SMS) customers prefer for engagement.
Example : John prefers receiving promotions via email but rarely interacts with SMS messages. - Are there any data inconsistencies across systems?
Identifies and resolves inconsistencies or missing data in customer profiles across different systems.
Example : John’s mobile number was missing in the CRM system but was present in the e-commerce platform, and the CIR model merged this information. - How does the customer interact across devices?
Tracks customer behavior across multiple devices (mobile, desktop, tablet) to build a complete profile.
Example : John browses on his desktop during the week and completes purchases on his mobile device during weekends. - Is the customer likely to churn?
Predicts the likelihood of a customer becoming inactive or leaving based on their behavior and engagement.
Example : John’s engagement with the brand has decreased over the past few months, indicating a high risk of churn.
