Why bother enriching data?
Get complete customer insights: It's all about understanding your customers better. You need to know what they want and when they want it, and even predict their needs before they do.
Achieve precision targeting: Say goodbye to the spray-and-pray approach. If your data tells you your customers are likely to be interested in a new product or service, reaching out can be a helpful nudge, not an annoyance like generic campaigns can be.
Boost efficiency: Streamline operations by focusing on what matters. Data enrichment helps you identify and cut out the fluff, making every marketing dollar and effort count.
What does the data enrichment process look like?
Clean house: Before you mix, you need to clean. This means eliminating outdated, irrelevant, or incorrect data to ensure your enrichment efforts pay off.
Combine data: All the data that you collect won’t make much sense if it’s living in a silo. Integrate data from your different systems and tools with contextual data that lives in your warehouse or data lake. This allows you to understand the complete customer experience, broader business performance trends, and more.
Use automation: Data enrichment tools and platforms can help you seamlessly integrate and update this data, ensuring your insights are always fresh and actionable.
What are the benefits of data enrichment?
By enriching data, you can enhance decision-making, create holistic customer profiles, and deliver personalized experiences that drive satisfaction and loyalty.
Improved decision making
Using additional data, like demographics or psychographic profiles, in your customer data analysis can significantly sharpen your strategic business decisions. It helps you customize marketing messages, anticipate market trends, and respond proactively to customer churn risks.
Consider a tech company analyzing customer feedback to improve its product. Traditionally, it might rely on direct feedback forms. But by enriching this data with social media sentiment analysis and customer support interactions, the company gains a fuller picture of customer satisfaction. This enriched data set allows the company to prioritize product updates that are most desired by customers, leading to increased satisfaction and loyalty.
Holistic customer profiles
Creating holistic customer profiles allows you to fully understand your customers' behaviors, preferences, and interactions across multiple channels. This understanding is crucial for improving customer engagement. With a complete view, companies can segment their customers more accurately and tailor offerings and messaging to match distinct customer groups' specific needs and preferences.
Businesses can ensure that their customer profiles are continually updated and enriched with the latest data using tools like Twilio Segment’s Profiles Sync. This approach keeps the customer data relevant and actionable for creating new audience segments and models.
Using Profiles Sync, Sanofi, a global healthcare leader, crafted "golden profiles" for healthcare providers (HCPs), blending online and offline data. This wasn't just an exercise in data collection – it unlocked new levels of engagement and understanding. The impact? Enriched profiles with up to 60 traits each that allowed them to run complex omnichannel marketing campaigns, effectively teaching HCPs about new medications and treatment plans. Plus, they also achieved 93% in time savings when adding new data sources.
Personalized customer experiences
With enriched data, companies can turn generic interactions into meaningful connections, significantly enhancing customer satisfaction and loyalty.
For instance, Netflix uses enriched data to personalize content recommendations for each user. By analyzing viewing habits, ratings, and preferences, Netflix creates a unique viewing experience that keeps users engaged and reduces churn.
Personalization is now a baseline expectation. Our State of Personalization report revealed that even during tough economic times, 69% of leaders are increasing their investment in personalization. This move makes sense because 56% of customers say they're more likely to buy again after a personalized experience, a 7% increase year-over-year.
Data enrichment challenges and considerations
Data accuracy, integration, and privacy are crucial aspects that organizations must address when enriching their data. These challenges require careful navigation to ensure the reliability, integration, and compliance of enriched data sets.
1. Data accuracy
The success of data enrichment hinges on the accuracy of the underlying data. Inaccurate data can derail the enrichment process, leading to poor decisions and inefficient resource use, especially if you need to act on real-time data. To navigate this challenge:
Prioritize data quality: Before adding layers of external information, it's essential to ensure the foundational data is accurate. This means setting up stringent data validation protocols.
Conduct regular audits and cleaning: Continuous auditing and data cleaning help identify and rectify inaccuracies.
2. Data integration
Integrating enriched data with existing systems can be complex, leading to the emergence of data silos and operational bottlenecks.
Organizations should:
Use appropriate tools, such as APIs, ETL processes, and cloud services, to address this challenge effectively for seamless data integration.
Establish clear data governance policies and standards, including precise data definitions and quality rules, to ensure data consistency and integrity across systems.
Regularly monitor and evaluate data integration performance to promptly identify and rectify issues.
3. Data privacy and compliance
Ensuring data privacy and staying compliant is about more than following the law – it's about building and maintaining customer trust.
At Twilio Segment, we understand the delicate balance between effectively utilizing data and respecting user privacy. Our Privacy Portal automates data masking and user permission controls, ultimately helping you meet regulatory requirements like GDPR and CCPA.
But compliance isn't enough. Obtaining explicit consent and transparently communicating the purpose of data enrichment is vital. Plus, employing encryption, anonymization, and robust security measures are essential for maintaining data integrity and user trust.
With our platform and following industry standards, organizations can safeguard data and maintain compliance effectively.
How Segment helps enrich data at scale
Our suite of tools empowers businesses to effortlessly enhance data enrichment processes, ensuring data accuracy, integrity, and actionable insights. Here's a breakdown of the features and tools we’ve built to help you:
Connections for an integrated tech stack
Connections – our core product offering – helps businesses collect first-party data from various sources like mobile apps, websites, and servers through a unified API.
It then integrates this data with contextual information from cloud applications such as CRMs and payment systems, providing a 360 view of customer interactions.
This approach streamlines the integration process, making it easier for businesses to manage their data ecosystem efficiently and leverage enriched data for informed decision-making.
Functions to quickly leverage new data sources
Our Functions feature enables businesses to bring new types of data into Segment and send data out to new tools using just a few lines of JavaScript without additional infrastructure.
Through Functions, businesses can ingest external data, transform or enrich it before it reaches downstream destinations, or even mask sensitive data to ensure compliance with privacy regulations.
Protocols to manage data quality at scale
Protocols is a comprehensive tool designed to ensure the integrity and quality of data at scale. It automates the establishment of data quality standards, which is crucial for accurate data enrichment.
By providing a structured approach that includes creating a detailed tracking plan, validating data against this plan, enforcing data standards, and resolving issues with transformations, Protocols offers a robust foundation for data enrichment processes.
Destination Actions to optimize data flow
Destination Actions allows users to control how event data from sources is sent to destinations.
It introduces a framework for specifying required or optional event data and setting triggers for actions based on event types, names, or properties. This setup promotes easier configuration, increased data transparency, and enhanced customization for integrating various tools. It also supports partner contributions and offers a wide range of destination integrations for a tailored data exchange, ensuring that data sent is optimized for each receiving service.
By enabling such customization, businesses can ensure that the data they share is more relevant, actionable, and fully optimized for each application, whether for analytics, marketing, or customer service platforms.
Reverse ETL to activate data from warehouse
Reverse ETL enables seamless data synchronization from your data warehouse to various destination tools.
This process allows for the activation of warehouse data to enhance customer engagement and personalize experiences across different platforms. Automating the data sync eliminates the need for manual data transfers or custom data pipelines, efficiently connecting your customer profiles and other vital data with your business-critical tools.
This functionality supports creating highly personalized experiences by enriching profiles with comprehensive data and building targeted audiences for downstream activation.
Linked Events to make data more actionable
Linked Events enables real-time event streams to be enriched with data from your warehouse, ensuring each event carries more context for downstream applications.
This feature supports a broad range of use cases, such as detailed event targeting, enriched data synchronization, and load time reduction, by enhancing page view events with comprehensive product and subscription details.
To use linked events, you must have access to Unify in your workspace, a connection to an actions-based destination, and a supported data warehouse (like Snowflake, BigQuery, or Redshift).