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– Quantivo Marketing Optimization Review

Product Snapshot


Quantivo’s product line focuses on remotely hosted SaaS solutions using patented technology not based off Hadoop architecture.

Customer Focus

Quantivo focuses on mid and large-sized companies who conduct their business primarily through online sales, retail, wholesale or warehouse distribution in a variety of industries.

Select Customers

ASOS, RAPP, Kohler, Party City, Orange, Simplicity Creative, Manheim Auctions

About Quantivo Marketing Optimization

- Quantivo Marketing OptimizationQuantivo Marketing Optimization uses Big Data analysis to provide a picture of the overall effectiveness of your marketing operations and their resonance with the customer base.

Quantivo’s solution brings in and integrates relevant data from a variety of different sources including web clicks, POS data, and advertising spending. It’s through this feature that the program boasts the ability to eliminate the guesswork from marketing operations by identifying a company’s most effective promotional campaigns and what their impact was in relevant customer segments.

About Quantivo
Quantivo’s roots as a company date back to BigFix, a Big Data company purchased by IBM in 2010. With Quantivo CEO Dave Robbins offered cloud-based business intelligence solutions. After beginning with a focus on data analysis for retail vendors, the company expanded its service to also target prospective customers in the marketing, insurance and online sales industries.

Quantivo offers solutions in customer behavior analysis, marketing optimization and web data analytics. Central to Quantivo’s approach is speed. The company’s solutions boast the ability to deliver analysis of large data sets “within hours, not weeks.” This quick performance is combined with a simple drag-and-drop, web-based user interface which virtually anyone in a company’s command structure can use.

Quantivo Marketing Optimization Key Features

    • Analysis integrating Big Data from multiple sources
    • Tracing of correlations across multiple data sources to understand consumer behavior
    • Identification of successful promotional campaigns and key customer segments
    • Enables shift to more personalized direct marketing approach with most loyal customers
    • Elastic scalability to company infrastructure
    • Intuitive interface with minimal learning curve


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