For brands that seek to manage and scale tailored marketing campaigns, customer data is the foundation. It is essential for brand marketers to collect customer data from diverse sources and build individual profiles. These profiles include information related to customers’ behavior, demographics, buying patterns, and other factors. With these datasets, brand marketers can personalize remarketing campaigns and improve customer engagement and retention.
The precision and efficiency of customer profiles depend on quality data collection and appending. When raw customer data is stored across multiple systems and applications, gathering customer data and creating extensive profiles becomes difficult. Building customer profiles using raw customer datasets leads to improper segmentation and targeting. This impacts the efficiency of remarketing campaigns. To overcome these consequences, marketers should embrace the data enrichment strategy. Data enrichment helps improve the quality and precision of raw customer data.
Data Enrichment Experts for Customer Profile Creation
Customer data enrichment involves the collection, appending, standardization, and segmentation of raw user data. These activities improve the quality of customer data and support structured customer profile creation. However, when marketers manage the customer data enrichment processes through traditional techniques, the time taken to create customer profiles increases. Delays in customer profile creation minimize the possibility of on-time tailored remarketing campaign launches and missed market opportunities.
As an alternative, enterprises should consider partnering with a reliable data enrichment services provider. This partnership enables businesses to work with dedicated data enrichment specialists. These specialists help marketing teams create structured customer profiles. Data enrichment specialists configure and integrate data extraction APIs in the business’s customer-facing tools and applications. This enables specialists to collect and store first-party customer data in a central repository.
For collecting the relevant customer information from third-party sources, enrichment experts use data appending tools. This approach improves the depth of customer data and data collection efficiency. Enrichment experts standardize accumulated datasets using a combination of automation tools and manual practices.
By leveraging machine learning algorithms, data enrichment experts segment the standardized datasets based on behavior and demographic factors. The segmented customer data profiles are integrated within CRM and marketing applications utilized by teams. By analyzing these profiles, marketers can gain insights into their customers’ preferences and buying patterns.
The advantages of hiring dedicated B2B data enrichment services providers for customer profile creation include:
- Augment Profile Quality – Through an effective standardization process, data enrichment experts help businesses create and maintain quality customer data profiles. Enrichment experts ensure that the profiles are free from inaccurate or duplicate information. This enables brand marketers to make strategic targeting decisions and eliminate mistakes.
- High Campaign ROI – With access to quality customer profiles, marketers can devise and launch tailored remarketing campaigns. This enables businesses to improve customer engagement and conversion rates. Targeting genuine customers helps marketers improve campaign returns and save costs.
- Compliant Data Management – After integrating segmented customer profiles in CRMs and marketing applications, data experts focus on security enrichment. Experts set up encryption and access control policies in businesses’ data management tools. This enables the tools to protect customer profiles from tampering and breaches and maintain compliance with data standards.
Key Steps Followed by Data Enrichment Experts During Customer Profile Creation
1. Data Collection and Appending
For extensive customer profile creation, collecting first-party and third-party customer data is essential. The first-party customer data consists of information related to customer purchases, feedback, and contact details. On the other hand, third-party customer data offers insights into user behavior, demographics, and buying patterns. Marketers should analyze both these datasets to understand customer preferences and tailor their remarketing campaigns. Data enrichment experts configure and integrate a data extraction API with the business websites, CRM systems, and customer support tools.
This API extracts and stores first-party customer data in cloud data management solutions. To collect third-party customer data from social media platforms and marketing databases, enrichment experts use data appending tools. These tools are equipped with machine learning pattern analysis and recognition algorithms. Data enrichment experts train these algorithms to identify and extract third-party data relevant to the first-party customer data inputs. The extracted third-party data is stored in cloud data management solutions. These solutions ensure secure storage of unstructured customer datasets.
2. Data Standardization
Standardizing the unstructured customer datasets is essential for improving customer data precision. Data enrichment solutions providers perform a schema analysis on customer datasets accumulated within cloud data management tools. This analysis enables data enrichment experts to identify the format imprecisions and determine the essential standardization measures to be applied. By leveraging data profiling tools, experts perform automated data cleansing and format modification on datasets stored within cloud management tools.
Data enrichment experts program profiling tools to identify and remove duplicate or improper customer datasets. By embedding formatting conditions, experts enable the profiling tools to map and match the attributes of first-party data with third-party customer data. This data matching ensures alignment in customer data segmentation. Profiling tools perform automated remodeling of unstructured datasets into structured customer data. This eliminates the format errors and anomalies in customer datasets.
3. Profile Segmentation
Segmented customer profile creation helps marketers understand their diverse audience and utilize specific information for engagement. Data enrichment experts use machine learning clustering models to create segmented customer profiles. By programming segmentation conditions as inputs, data enrichment experts enable the clustering models to assess and classify customer data in cloud storage tools.
The clustering models segment customer data based on demographics, geographic, and behavioral aspects. Segmenting customer profiles enables brand marketers to analyze and understand their customer base before initiating marketing activities.
4. Integration
After the segmentation, data enrichment solutions providers integrate the customer profiles in the cloud database with the CRM and email campaign tools used by marketing teams. For integration, data enrichment experts use data connectors. These connectors transfer customer profiles from the cloud database to the tools and applications used by marketers. With access to segmented customer profiles in CRM in campaign tools, brand marketers can analyze and obtain insights related to customer behavior and preferences. These insights help marketers ideate and launch personalized remarketing campaigns across platforms. This enables businesses to improve the lifetime value and retention rate of their customer base.
Closing Thoughts
Several brand marketers seek ways to launch tailored remarketing campaigns to improve their customer engagement and experience. However, for running such campaigns, creating and managing extensive customer profiles is essential. Businesses should consider hiring experts from a data enrichment company for customer profile creation. These experts help businesses with structured customer data profiling and enable marketers to improve the efficiency of their remarketing campaigns.
