As marketers, buying lists of emails is commonplace. Perhaps it is for customer acquisition or to append missing information to our customer database. Whatever the reason, marketers license data from a limited set of brokers – and for the most part, it’s generally all the same. Unfortunately, most of this data is stagnant data compiled from third parties like names and email addresses. With zero competitive advantage among data lists, list acquisition has become about shopping on price, not value.
As marketers, buying lists of emails is commonplace. Perhaps it is for customer acquisition or to append missing information to our customer database. Whatever the reason, marketers license data from a limited set of brokers – and for the most part, it’s generally all the same. Unfortunately, most of this data is stagnant data compiled from third parties like names and email addresses. With zero competitive advantage among data lists, list acquisition has become about shopping on price, not value.
To make matters worse, different marketing groups within the same company continue to work in siloed environments, procuring different data sets for their own individual purposes. Rather than a holistic data acquisition approach, digital marketers secure data for their digital objectives, and direct marketers are purchasing separate email lists for their own purposes.
The New Way of Modern Data Acquisition
So what’s the answer? How can you access fresh sources of data, and more importantly, how can you access fresh sources of data that your competitors don’t even know exist?
Data-as-a-Service (DaaS) is a unique approach to leveraging the Big Data ecosystem to access unique and Hard-to-Find Data (HTFD) sources. Distinctly different from list-buying, DaaS is a revolutionary way of mining today’s massive data sets to find qualified prospects in the market now for what you are selling. This way is quite different than traditionally buying email lists for one-time use.
Three Types of Data to Create a Unique Data Set
DaaS combines three types of data to create a unique data set:
- Foundational Data: Internal data combined with additional demographic and firmographic enhancement and specialty data.
- Onboarded Data: Offline data transformed into addressable online identities.
- Fast Data: Real-time behavioral data.
Foundational Data: The foundational data set comprises internal data, demographic or firmographic data, and unique and HTFD which have been mined and aggregated from hundreds of Big Data sources. Some examples of HTFD include:
- Niche company lists, beyond high level SIC and NAIC code descriptions
- Information (contacts, top customers, products, shipments) on 1.5 million buyers and suppliers in 90 countries. Helps sellers identify/evaluate buyers, helps buyers identify/evaluate suppliers.
- Data collected on residential and commercial building permits 88 million residential and commercial building permits, 155 million inspection records, and 7 million contractors in the U.S.
- Spend data on specific businesses by categories.
- U.S. manufacturing industry data with unique attributes such as certifications (ANSI, ISO), business type (exporter, distributor) and products & services (adhesive technologies, compounds).
- Comprehensive healthcare data (doctors, dentists, other prescribers, their practices, clinics, hospitals, etc.)
Onboarded Data: Data onboarding is all about bringing offline data into the online world. As part of a data onboarding process, matches are made between offline data and online user profiles. Data such as a phone number, email address, name, or a physical address are used as identifiers. These identifiers are then matched to online cookies, creating a universe of digitally addressable prospects and customers.
Fast Data: Fast Data aggregates event and behavioral-driven data to determine purchase intent as it occurs. These moment-to-moments insights are crucial for today’s enterprises and play an important role in targeting in-market consumers and businesses to generate ROI. Just imagine the competitive advantage in having exclusive knowledge about who is actively searching for products you (or your competitors) sell.
Examples of Fast Data include:
- Aggregated “intent data” from over 160 million unique users on e-commerce, online travel agency and auto comparison sites.
- Digital data that includes web pages surfed, all email, and Machine to Machine (Internet of Things) digital activity.
- Transactional data such as purchases, requests, insurance claims, deposits, withdrawals, flight reservations, credit card purchases, and more.
- Search data on any term, such as “Home Renovation”, “Excited about the Move”, or competitors names and products.
For years, marketers have been reliant on their internal data enhanced with data from list brokers. Buying email lists is old news. This is stagnant data compiled from third parties. DaaS on the other hand is transformational in nature – a perpetual data asset that delivers competitive advantage every day.