Methodology of
We ensure a highly accurate and actionable data by making sure all our top guns are clocking in for each of these strategic data compilation and verification stages.
Our Research Analysts, Data Specialists, Verification Team, Quality Team and Data Sourcing Teams work in tandem for each.
Steps
1. Collection Of Primary Data
Search Analyze and collect primary data from millions of public documents for technology-specific, technographic, firmographic, and demographic information. Information on technology usage is gathered from tech Association memberships, user group communities, millions of tech-specific job boards/portals, technology magazine subscriptions, user group communities, tech blogs, entitlements, tech specializations, case studies, testimonials, featured customers, white papers, and other sources.
3. Data Standardization
Data is Standardized, structured, and categorized by our proprietary AI based, Rule based algorithms into the actionable formats.
5. Data Loading Into Relavant Data Types
The relevant data types are identified to load the relevant fields in each data type where it makes sense.
7. Periodic Data Refresh
In a frequency from 45-90 days all data points are verified and incorrect and stale data is removed. Also, prior to delivery, each project file goes through a mandatory pre-delivery verification process.
2. Data Sorting & Segmentation
The Data is then supplemented with appending by our teams and sorting it out it categories and specific fields.
4. Data Validation
Each data points are validated, vetted, and verified by the team. All incorrect data is removed for a cleaner Masterfile.
6. Data Complaince
Each of the data points are checked by our privacy team to make sure all information points are compliant as per the applicable laws.
8. Data Enhancement
As a part of data maintenance and continuous cycle of data compilation, more companies and contacts are added to the Master Data by the Data Enhancement team.
Steps
1. Collection Of Primary Data
3. Data Standardization
5. Data Loading Into Relavant Data Types
7. Periodic Data Refresh
2. Data Sorting & Segmentation
4. Data Validation
6. Data Complaince
8. Data Enhancement
Turn Data
The purpose of data marketing is to make the jobs of marketers simpler and faster. Over the years, data marketing have evolved to stay up-to-date with modern business through
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Sales
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Focus on high value prospect & know the stack
Marketing
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Success campaigns with highly targeted data
Strategy
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Based on market info, share, size & understanding
