Marketing Data Enrichment

This article examines data enrichment, which increases the accuracy and value of data by including external information. It analyzes the benefits of data enrichment, key data sources, various enrichment methods, and popular tools such as HubSpot CRM, Clearbit, and LeadGenius. Whether applied to B2B or CRM data, enrichment allows the creation of more accurate customer profiles, contributing to improved marketing strategies and business development.

What is data enrichment?

Data enrichment is a key process in information management that increases its accuracy, value, and content. Combining existing data with external sources allows businesses to refine and improve the original array of information. The importance of this process lies in ensuring the quality of data for companies and organizations that use it to make decisions, create strategies, and maintain competitive advantages.

Enriching data is not just adding new information but improving and expanding their usefulness. The main tasks of this process include standardizing data formats for consistency and adding context that makes data arrays more valuable.

For example, enriching customer data in marketing can involve supplementing profiles with information about demographic characteristics, purchasing behavior, or social media activity. This helps to improve the personalized approach to customer interaction and increase the effectiveness of marketing strategies.

Pros of data enrichment for marketing

• Personalization. Rising customer acquisition costs and a crowded digital space make an effective attribution model crucial for tracking touchpoints and optimizing budgets, while data enrichment helps companies tailor products and strategies to audience preferences and behaviors. Personalized offers, recommendations, and notifications are sent to customers based on their demographic characteristics, interests, geographical location, and purchase history, which allows for more accurate segmentation of the customer base.
• Better decision-making. Enriched data provides a complete understanding of the topic, allowing businesses to make more informed decisions
• Targeted advertising. Enriched data allows companies to better understand their target audience, leading to more effective and personalized marketing strategies.
• Efficiency. Data enrichment can help improve performance and procedures. For example, it can improve the effectiveness of campaigns targeting specific audiences.
• Increase sales efficiency. Enriched data improves sales performance by providing sales teams with practical information and priority leads.
• Innovation. Data enrichment can open up new opportunities and solutions by providing more diverse and comprehensive data. For example, it can be used to identify new markets, trends, and patterns in data, from which new functions, products, and business plans can be created.

Main data sources for enrichment

Various sources are utilized to enrich the data by providing additional information about customers and the market. The main ones include:

1. Internal company data. These are information about sales, consumer complaints, accounting, pending orders, etc.
2. External public sources. Data is available through government agencies, non-profit organizations, and non-governmental organizations that publish information about demographics, economics, and other aspects that may be useful to marketers.
3. Online resources. Tools such as Google Trends provide data on the popularity of search queries, which helps to understand the interests and needs of the target audience.
4. Data from social networks. Information from platforms such as Facebook, LinkedIn, and Twitter allows you to analyze user behavior, interests, and interaction with the brand.
5. Data on competitors. Analyzing public information about competitors, their marketing campaigns, and their positioning in the market helps to understand the competitive environment.
6. Customer Data Platforms and Data Vendors - CDP collects data from different sources in the organization and creates a single view of the customer. It helps avoid the use of isolated or inaccurate data by structuring real data into individual customer profiles. CDP works in conjunction with CRM to provide enhanced capabilities, such as tracking customer interactions across multiple channels (online and offline).

Types of data enrichment

Existing data can be enriched in the following ways:

• Contact data enrichment, such as phone numbers and email addresses, allows direct customer communication
• Geographic data, such as country, region, or city of residence, helps to run location-based campaigns.
• Demographic data, particularly age, sex, or marital status, is especially useful for personalized B2C campaigns.
• Technological data, such as customer device type, usage habits, or technology stack, which contributes to more efficient targeting.
• Behavior data, from browsing duration to search history, helps to understand individual customer models and plan accordingly.
• Proprietary data such as company industry, size, and revenue are especially important for targeting decision-makers in B2B campaigns.

Best ways for data enrichment

Regardless of the size of databases, manually viewing data today is too resource-intensive. Special services have already been developed to simplify and automate this task, greatly facilitating the management and enrichment of data.

Here are the best data enrichment solutions:

• Stape offers powerful data enrichment capabilities through server tracking and integration with Google Tag Manager (GTM): HTTP Lookup Variable is a function for server GTM that allows HTTP requests to external APIs or web services, which makes it possible to configure and enrich data directly in the tracking process. Stape Store Lookup  is a variable developed in the Google Tag Manager (sGTM) Stape server environment. It allows users to retrieve data from the Stape Store by specifying a document ID or setting query criteria to search for specific documents. This functionality facilitates efficient data retrieval and management for server-side tag implementation.
• HubSpot CRM is an effective solution for managing client data. It offers customizable properties, tasks, web forms for collecting data, built-in chat, tracking, and email sending.
• Vainu is B2B sales and business intelligence software. It allows you to filter the database with millions of companies and find potential customers that match the ideal profile. Integrates with HubSpot, Salesforce, Pipedrive, etc.
• Clearbit is a platform for enriching data about companies and contacts. It allows to update, qualify, and evaluate potential B2B-klієntіv thanks to access to more than 200 million contacts.
• Reverse Contact is a reverse email search service that only finds information about a person and company by email. Uses real-time public data and meets GDPR and CCPA requirements.
• LeadSpace is a technology that updates information by combining multiple data sources and CRM systems. It uses artificial intelligence (AI) to collect data based on user behavior on the Internet, which helps to target potential customers more accurately.
• Datanyze is a service that searches for and communicates with potential customers around the world. It integrates with CRM systems and allows you to collect data while browsing social networks, create segmented lists, and target ads.
• LeadGenius allows checking information about B2B leads so that teams refer only to the most accurate and interested potential customers. It creates personalized datasets, improving the quality of communication and customer engagement.
• Trifacta offers an open and interactive cloud data platform that enables data preparation and management for analytics and machine learning. It also helps track quality and data sources in enrichment processes.
• Accurate Append enriches B2C data by providing detailed information on demographics, income, and donation history. This service helps improve the quality of leads and allows you to more accurately target marketing strategies, providing businesses with additional data to attract customers effectively.

7 data enrichment techniques with examples

Data enrichment is a key step to improving customer information quality and accuracy. Here are some effective data enrichment examples:

1. Define clear enrichment criteria

The first step is to set specific goals for data enrichment. For example, a company may aim to achieve 90% accuracy in customer data verified by third-party sources. It will assess the effectiveness of enrichment efforts and identify areas for improvement.

2. Development of repeatable enrichment processes

Creating standardized procedures for data enrichment ensures efficiency and consistency. For example, the automated process of validating customer profile data through predefined third-party sources can be reused for different datasets, ensuring consistency and reducing task time.

3. Scalability of enrichment efforts.

If data volumes are increasing, it is important that enrichment processes can scale accordingly. Implementing automation, such as through server-side tracking, can help reduce the impact of ad blockers and improve the accuracy of data collection, which positively impacts the scalability of enrichment efforts.

4. Unification of enrichment processes for different datasets.

The unification of approaches to data enrichment for different sources ensures consistency. For example, introducing a single process for verifying customer data obtained through web forms on computers and mobile devices ensures that data from both platforms is processed similarly, ensuring their integrity and accuracy.

5. Using server-side tracking to improve data quality.

Server-based tracking allows for more accurate data collection and conversion tracking as it is less affected by ad blockers and tracking restrictions. For example, according to a study conducted by Google, Square has seen a 46% increase in registered conversions from Google Ads after the introduction of server-side tracking.

6. Data enrichment through integration with Stape Store.

Integrating the Google Tag Manager (sGTM) server container with Firestore allows you to read and write data, which opens up ample opportunities for data enrichment. It provides data collection and processing flexibility, adapting processes to business needs.

Data enrichment vs. data cleansing

Data cleansing

Data cleansing focuses on the accuracy of the available data. It is identifying and correcting errors, inconsistencies, and redundancies in a dataset. The main tasks of cleaning:

• Bug fixes. For example, fixing misspelled names, incorrectly entered values, and errors in addresses or phone numbers.
• Updating outdated information. Checking for the relevance of data, such as a change of address or customer status.
• Remove duplicates. Detect and remove duplicate records that may falsely represent the number of clients.

This process maintains the integrity of the data, ensuring its correctness and relevance. Cleaning usually takes place in the initial stages of working with data to ensure that they do not contain errors that may affect the accuracy of the analysis or decision-making.

When should you invest in data cleanup?

• If the level of involvement drops with an increase in the number of contacts, this can be a signal to clean up the data.
• Data cleansing should occur at least every six months to ensure its relevance and accuracy.

Data enrichment

Data enrichment is the process of improving and expanding existing data through external sources. Rather than simply correcting errors, enrichment adds new, relevant information that can add context and depth to existing data. It allows for the creation of a more complete customer or prospect profile.

Examples of enrichment:

• Adding demographic data. Enriching contacts with data about age, gender, family, or interests.
• Geographic enrichment. Adding customer location information can be helpful for targeted advertising or special offers.
• Psychographic enrichment involves obtaining more information about customer preferences, lifestyles, and buying habits, which allows better targeting of marketing campaigns.

Enrichment helps create more accurate and personalized customer profiles, which can improve interactions with customers and offer more relevant products or services.

When should you invest in data enrichment?

• When your database is cleared, and you want to add more depth to your customer profiles for personalized marketing campaigns.
• If you are interested in improving customer segmentation accuracy or conducting more detailed analyses.

Comparison of data cleaning and enrichment

• Data cleansing focuses on correcting errors and inaccuracies and removing unnecessary or outdated data.
• Data enrichment adds new information to improve and enhance existing data, allowing for more accurate and profound profiles.

Cleansing is usually the first step, after which you can move on to enrichment to create more prosperous and valuable data.

FAQs

1. How data enrichment improves marketing strategies? 

Data enrichment improves marketing strategies by providing deeper customer insights, allowing you to segment your audience and create personalized campaigns more accurately. By enriching data, marketers can combine all customer information in one place, which simplifies their understanding and improves interaction with them. This enhances the effectiveness of marketing campaigns, providing more accurate targeting and improved customer service. In addition, data enrichment helps in risk management and regulatory compliance, ensuring that the data is correct and up to date. Data enrichment generally turns raw data into valuable insights contributing to improved marketing strategies and business development.

2. What is CRM data enrichment?

Customer Relationship Management (CRM) is the process of improving customer information through external data sources. This allows you to get more details about customers, such as demographic information, purchase history, behavior on the site, and other factors that help you better understand their needs and preferences. Enriching CRM data allows companies to create personalized marketing campaigns, improve customer interaction, and increase sales efficiency. It also helps in audience segmentation and business process optimization.

3. What is b2b data enrichment?

Data B2B-enrichment (Business-to-Business Data Enrichment) is a process of improving and expanding information about business customers by adding external data, allowing you to get a complete picture of the companies with which you cooperate or plan to cooperate. This includes integrating additional information such as company size, industry, financial performance, contact details of key individuals, and other characteristics that help to better understand the needs and capabilities of your business customers.

Enrichment of B2B-data contributes to improving sales and marketing processes, allowing you to more accurately segment the target audience, create personalized offers, and effectively manage customer relationships.