Hyper-Local Shopper Engagement

Hyper-Local Shopper Engagement

Seeloz, Inc.


Designed to revolutionize your approach to shopper engagement, Seeloz pushes the boundaries of data science and predictive modeling to help you deliver the right product, to the right person, at the right place, at the right price... at exactly the right time.


Data Science: Seeloz uses a cloud-based data mining engine to process billions of data signals from retailer systems at the SKU level.

Collaboration: To fully engage with shoppers, retailers and manufacturers can leverage Seeloz as a collaborative space to craft the optimal campaigns and promotions.

Omni-Channel Offers: Location, location, location… and timely, relevant content of course. Putting together an offer with Seeloz is about maximizing and customizing engagement. So a given shopper might get a timely, targeted email based on recent purchase history or cyclical buying propensity. Taking full advantage of Seeloz' hyper-local targeting capabilities, the same shopper could potentially get a location based message with an offer alert based on proximity to a retail location… again, ultra targeted, timely, and personalized.

About the Company

Seeloz is a Big Data company building the next generation Hyper-Local Shopper Engagement platform for retailers and manufacturers. 

In a nutshell, the Seeloz Platform is a comprehensive digital marketing solution utilizing advanced data science and predictive modeling to deliver hyper-personalized messaging and promotional offers to individual shoppers via any channel. 

Seeloz provides a collaboration platform for retailers and manufacturers to work together towards achieving their respective business objectives, improving the 1:1 engagement with shoppers at the point of decision (at home, in-store, and on-the-go) and maximizing ROI from promotional dollars. 

The Seeloz team consists of experts in big data, data science, retail and CPG with years of experience building similar platforms at Google, Yahoo!, Amazon.com and a series of successful startups.

Best For: Unavailable
Retail Verticals: Unavailable

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