How to create a unified view of your consumer

Introduction

Creating a comprehensive, 360-degree view of your customer in today’s competitive business landscape improves end-customer experience, operational strategy, and marketing efficiency. Customer behavior is moving from in-person transactions in brick-and-mortar locations to online, personalized interactions fueled by data. Companies are capable of learning more about their customers if they can sort through the noise. A unified view of the consumer refers to the ability to consolidate and connect all the disparate signals from all the interactions a customer has with a business, across various touchpoints and data sources. This includes transaction history, loyalty program memberships, website and mobile app visits, customer service interactions, and more. All of these sources of data contain valuable insights about customer behaviors but are keyed to different pieces of customer data and are siloed into disconnected systems. A customer may interact with a brand through its website, mobile app, in-store, and through various marketing campaigns – each touchpoint generating its own set of records. By linking these fragmented data points into a single, cohesive profile using Amazon Connect Customer Profiles and AWS Entity Resolution, businesses can unlock a deeper understanding of their customers and deliver truly personalized experiences.

Consider the example of a banking customer named Shirley. Over the years, Shirley has opened a checking account, applied for a credit card, applied for a mortgage, enrolled in the bank’s rewards program, and contacted the customer support team on several occasions. However, this data is fragmented. She opened an account at a regional bank that was later acquired. Her mortgage was associated to a postal address she no longer resides in. She has opened both person and business accounts using different billing information. These factors may contribute to the bank having only a partial picture of Shirley’s relationship with them. They might miss opportunities to provide tailored offers based on her history, anticipate her needs based on past behaviors, or resolve her issues efficiently when she calls into customer service. However, by leveraging AWS Entity Resolution, the bank can connect all of Shirley’s records and interactions, giving them a comprehensive understanding of her as a customer. They can then create a unified source of truth record for Shirley using Amazon Connect Customer Profiles, which is updated in real time with every new interaction the bank has with Shirley across their banking and marketing channels.

Key challenges

Companies would have to address several challenges to give customers like Shirley a better experience:

1. Fragmented data: Customer data is siloed across disconnected applications with different schemas, formats, locations and access, making it challenging to centralized.
2. Inconsistent customer profiles: Companies end up with inconsistent, incomplete, or even contradictory information about their customers. This makes it difficult to develop a clear, accurate understanding of each individual.
3. Difficulty in personalization: Without a unified customer view, it becomes nearly impossible to deliver truly personalized experiences. Businesses may fail to recognize returning customers, offer relevant recommendations, or provide a seamless experience across interactions.
4. Suboptimal marketing and sales: Fragmented data inhibits a company’s ability to gain meaningful customer insights, map buying journeys, and execute targeted, effective marketing campaigns. This can result in wasted marketing spend and lost sales opportunities.
5. Compliance and privacy risks: Modern data privacy regulations, such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), require businesses to have a comprehensive understanding of the personal data they collect and store about each customer to use for access requests, audits, opt outs and deletions. Fragmented data makes it challenging to comply with such regulations.

By addressing these challenges and consolidating customer data into a unified view, businesses can unlock a wealth of opportunities to enhance the customer experience, drive growth, and stay ahead of the competition.

In this blog, we will discuss the use of Amazon Connect Customer Profiles and AWS Entity Resolution to create a unified view of the consumer.

Solution

Amazon Connect Customer Profiles consolidates and stores all relevant customer information – from contact details and transaction history to support interactions and preferences – into a single, unified customer profile and then creates actionable insights. These profiles contain the most important contact details, most recent interactions, and other calculated insights around that customer. Customer Profiles supports dozens of no-code integrations to the most important customer data systems to seamlessly ingest data, and automates the processing and storing of that data to make it available in a low-latency store for lookups or access within Amazon Connect. By seamlessly integrating with AWS Entity Resolution, Amazon Connect Customer Profiles ensures that each profile is linked to the correct, de-duplicated customer entity, eliminating the risk of inconsistent or fragmented data.

AWS Entity Resolution helps companies match, link, and enhance related customer, product, business, or healthcare records stored across multiple applications, channels, and data stores. The service addresses the challenge of fragmented consumer data by leveraging rule-based and machine learning-based matching techniques. AWS Entity Resolution ingests consumer records from disparate sources, de-duplicates them, and identifies unique consumer entities. By assigning a unique matchID to all records belonging to the same consumer, the service creates a common key to represent a person to key all sources of data that can be unified for analysis and segmentation. AWS Entity Resolution removes the heavy lifting required to build an identity resolution pipeline – data normalization, pair generation on large data sets, comparison distribution, ID consistency, clustering and splitting – so that companies can use easy-to-configure matching techniques instead of building complex data engineering solutions. If they do not know where to start with rule-based matching, ML-based matching provides industry-leading accuracy out-of-the-box on personally identifiable information (PII) based data so that no configuration is required.

Customers can also build upon the data foundation, processed through AWS Entity Resolution, to provide businesses with a comprehensive, actionable 360-degree view of each customer using Amazon Connect Customer Profiles.

This combined solution offers several key benefits:

1. Unified customer intelligence: Businesses gain a holistic understanding of each customer, including their demographics, behavior, interests, and pain points, across all touchpoints and interactions.
2. Personalized experiences: With a complete view of the customer, organizations can deliver highly personalized products, services, and communications, strengthening customer loyalty and satisfaction.
3. More personalized marketing: Fragmentary or duplicate records, when used for marketing or advertising campaigns, can result in wasted marketing spend, poor campaign results, and annoying your customers with redundant messaging.
4. Personalized customer support: Customer service agents can quickly access the full context of a customer’s history and previous interactions, enabling them to provide faster, more effective support.
5. Improved cross-selling and upselling: By understanding the customer’s entire journey and product/service usage, businesses can identify relevant cross-sell and upsell opportunities to drive revenue growth.
6. Compliance and privacy regulation: Modern data privacy policies, such as GDPR and CCPA, require businesses to have a comprehensive understanding of the personal data they are allowed to collect and store about each customer. They also need to ensure op-outs and record deletion requests are effectuated accordingly to meet all regulatory standards.
7. Respecting contact preferences: If a customer opts to not be contacted via phone or email, a company can provide a better experience if they respect that even if they have multiple phone numbers or email addresses.

By combining the power of Amazon Connect Customer Profiles and AWS Entity Resolution, businesses can achieve a comprehensive, 360-degree view of their consumers, unlocking new levels of customer understanding and business impact.

How it works

The reference architecture below outlines how Amazon Connect Customer Profiles and AWS Entity Resolution unify customer data to create a 360-view that can be used to reduce customer churn, enhance personalization, improve customer service, and more.

Amazon Connect Customer Profiles and AWS Entity Resolution reference architecture

Data sources that contain consumer records and interactions are sent to AWS Entity Resolution for de-duplication, matching, and linking. These sources usually include personally identifiable information (PII) about the consumer, and systems like loyalty/enrollment, CRM systems, are good examples. AWS Entity Resolution’s matching logic and configuration allows customers to build rules that leverage multiple touchpoints or complex logic and fuzzy algorithms. Customers can also use the Machine Learning-based matching model to accurately match data using PII without complex rules.

Amazon Connect Customer Profiles can then ingest other data sources, such as marketing automation, call center interaction records, or user preferences in order to create actionable insights about your customers. These sources do not require the same logic and are usually attached to a known user/entity using a specific key or identifier, such as an account ID.

By separating the data sources in this manner, the architecture can optimize the use of each AWS service:

• AWS Entity Resolution focuses on the core task of resolving and linking customer identities from the primary systems of record to a customer identifier.
• Amazon Connect Customer Profiles aggregates the resolved customer data with the additional engagement data to provide a holistic, 360-degree view of each customer identifier.

This approach ensures efficient data processing and enables the creation of a comprehensive, unified customer view that supports personalized experiences, targeted marketing, and enhanced customer insights.

Since customer data evolves over time as companies increase their visibility into customers, companies must plan for a resilient architecture that can grow and evolve as the profile changes. Many consumers interact with a business across various channels, both as anonymous and known visitors. This fragmentation of data across channels often lead to the creation of multiple profiles for the same person and creates challenges to identify the individual in the moment. A common approach to address this issue is to leverage rule-based and machine learning-based matching through AWS Entity Resolution. While the initial rule based-matching may result in the creation of separate profiles due to incomplete information, the machine learning-powered matching capabilities of AWS Entity Resolution over time can be applied to provide a more robust link between these disparate profiles. By unifying customer data in this way, organizations can gain a more holistic, unified view of the consumer, empowering them to deliver more personalized and seamless experiences across interactions.

Once the profiles have been created, and customer data feeds begin feeding into Customer Profiles to populate the profiles, companies can use Customer Profiles as a customer data fabric for segmentation, analytics, and personalization through several activation channels. Using Amazon Connect Outbound Campaigns, companies can create audience segments for outbound email, SMS or push notification events, or use attributes of customer profiles as triggers for customer service actions, outreach, or experiences. Additionally, users can use the unified customer view as a unified, rich, up-to-date customer fabric in their Customer Data Platform of choice, including Adobe and Salesforce.

Customer Success

Customers like United Airlines significantly improved end-customer satisfaction and ROI of their marketing budget by using AWS Entity Resolution and Amazon Connect Customer Profiles to build a unified customer view. United Airlines used AWS Entity Resolution to create both a deterministic ID using rule-based matching and a probabilistic unified ID using AWS Entity Resolution’s ML-based matching model. By applying both ML- and rule-based matching, United achieved a matching accuracy of more than 90 percent.

“Using AWS Entity Resolution, for every single booking, we can associate the correct probabilistic ID with that customer in NRT,” says Mahesh Veda, Managing Director, Customer Travel Experience, at United. “This creates a unified view for their entire journey.”

United Airlines then connects traveler and guest data to unlock insights and drive personalization. Using this solution, the system ingests data from 14 backend sources and legacy systems, including reservation databases and customer-relationship-management software. Using the new solution, United Airlines reduced duplicate customer records by 35 percent and consolidated its infrastructure, reducing operating costs by 30%. Most importantly, customers noticed the difference in their travel experiences.

“We witnessed a 15 percent increase in our net promoter score,” says Veda. “Our customers are happy because they can say, ‘Hey, you recognize me. Even though I made a booking this way and I came back in, you recognize me.’”

Conclusion

Companies collect fragmented data from their customers across many channels, and struggle to unify that data accurately. Amazon Connect Customer Profiles and AWS Entity Resolution unify data from many sources and them merge duplicate profiles that can be used to deliver more personalized experiences. Reach out to your AWS representative, or learn more online about how to get started with and Amazon Connect Customer Profiles and AWS Entity Resolution to unify your customer view for better insights and personalized experiences for your customers.