Data-as-a-Service: Real-Life Examples of Companies Who Are Using DaaS to Boost Revenue

March 14, 2015
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We’ve talked at length recently about the benefits of using Data-as-a-Service (DaaS) to target in-market consumers. DaaS is a process that leverages the modern data ecosystem and real-time data analytics to create a customized “always on” dataset.

big data, data-as-a-service, daas

We’ve talked at length recently about the benefits of using Data-as-a-Service (DaaS) to target in-market consumers. DaaS is a process that leverages the modern data ecosystem and real-time data analytics to create a customized “always on” dataset. It is completely changing the game for today’s marketers, fueling customer acquisition and retention strategies for marketers across all industries.

DaaS combines a company’s first-party CRM (customer relationship management) data with real-time triggers and Hard-to-Find-Data (HTFD) sources to deliver better targeting and a stream of in-market consumers.

DaaS has the potential to really bring new competencies and competitive advantage to marketers in new and exciting ways. But don’t take our word for it – check out these real-life examples of how companies are using DaaS to boost revenue and ROI:

Example One – Financial Services

A national banking client was seeking ways to boost customer acquisition. They used the following data sets to identify in-market targets:

1. Mortgages: First Time Home Buyers:

  • Identified a list of the bank’s customers and targeted prospects.
  • Suppressed those that are current homeowners, leaving non-homeowners with specific traits (age, head of household, HHI, etc.).
  • Monitored the resulting file for mortgage activity with a specific FICO level indicator – e.g. 680.  When a “hit” is identified, bank was notified and a fair offer of credit can be made to the potential homeowner.

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2. Mortgages: Refinance Variation:

  • Secured a list of property building permits on specific bank customers and high end prospect records. When a substantial amount of work is being done at a property, this could designate the opportunity for a refinance.
     

3. Investments: 

  • Scraped public record data in bank’s footprint to ID consumers and businesses that have experienced a significant liquidity event.
  • ID people looking to sell a high end auto.
  • ID pre-movers.
  • Monitor life triggers, such as marriages, divorces, and new births.

4. Businesses:

  • Monitor email server activity.
  • Scraped public record data in bank’s operating footprint to ID businesses that are moving, have moved, or have received certain levels and kinds of funding.
  • Review of other financial activity that may be leading indicators of growth or decline.

Example Two – Automotive Industry

The following data sets are being used by several well-known names in the automotive industry:

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Example Three – Furniture Retail

FurnitureROITM is a furniture retail data product used by a large, multi-regional furniture retailer located in the Northeast.

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  1. DataMentors’ Consumer Database: Identify New Prospects
    • 250MM US Consumers
    • NCOA Scrubbed
    • 300 Data Elements (Age, Income, Home Ownership, Home Improvement and Decorating Interests, Expectant Parent, Recent Divorce, Recent Home Buyer, Home Square Footage, and more).
       
  2. Millennial Data: Target Millennial Consumers with Multi-Channel Messaging
    • Data on 42MM millennials
    • Segment millennial consumers by proximity to your store location, income, home-owner or renter
    • Lifestyle interests, including technology, home improvement and decorating interests
    • Rich contact data including email address and mobile number
       
  3. Pre-Mover and New-Mover Data: Send Offers to Consumers Who May Soon be In Market

Innovative web mining technology identifies pre-movers and new movers who may soon be in-market for furniture. This real-time data is gathered across a comprehensive network of websites and includes information such as new rentals, houses sold, geography, income level and more.

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  1. Social Signaling Data: Boost Customer Acquisition Through Social Prospecting

    FurnitureROITM monitors social media for furniture purchase signaling, such as “excited about the move”, or “looking for a leather couch”.
     

  2. Onboarded Data: Digitally Addressable Dataset for Real-Time Messaging

These unique data sets are integrated and structured to form an “always-on” stream of prospects. Data is onboarded to link offline data to online IDs for customized ad delivery through your channel systems.

The datasets sourced through DaaS are uniquely customized to each company. While we have shared just a few examples of how DaaS can be used across industries, the possibilities are truly endless.

For years, organizations have been reliant on their internal data or data enhancements from list brokers. This is stagnant data compiled from third parties. DaaS on the other hand is transformational in nature – a revolutionary way of mining today’s massive data sets to find qualified prospects in the market now for what a company is selling.  DaaS is the next leap forward in the modern data ecosystem, fueling competitive marketing advantage in new and exciting ways.

Be sure to download our white paper for a more in-depth overview of DaaS.

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