Drive sales and growth while reducing costs by better understanding retail customers with external data

machine learning in retail
The retail environment creates challenges in reaching customers for brick and mortar businesses.
Understanding your customer doesn't stop at knowing what they like and dislike, but understanding how they're reached is important.  To stay relevant, retailers need to implement more effective marketing tactics, both online and offline. External data enriches internal information to create more compelling shopping experiences, market more effectively to existing and prospective customers, optimize store locations, and forecast store traffic.

Explorium's automated data science platform


Consolidating external data for analytics is resource and time consuming
Explorium’s External Data Platform centralizes access to public, premium, and proprietary external data for business analysts, data scientists, and business leaders

Transforming, matching, and integrating external data is tedious work
Explorium’s External Data Platform ML capabilities automatically match and integrate external data with your internal data accelerating time to value

Assessing the value of external data is inexact
Explorium’s External Data Platform identifies the relevant external data signals and calculates the uplift in your ML models before deployment

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The right external data is a competitive advantage. 

Understanding the broader trends in the market and including that in your analytics and models will improve their performance. Integrate external data with your internal sources to improve decisions and outcomes for your business
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Improve Ad Retargeting
Many retailers augment their brick and mortar locations with an online presence. Retargeting customers who abandoned their shopping carts or made smaller purchases is vital to success. Where to allocate marketing dollars is driven by the behaviors, actions, and interactions that indicate a potential customer. Enriching internal customer data with external sources such as location based data (zip codes and IP addresses), geospatial financial indicators, and time series data on repeat visitors significantly improves your models to retarget customers.
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Optimize marketing efforts through improved customer segmentation
Knowing who your best customers are and what they’re more likely to purchase allows you to market more effectively to prospective customers. Send the right message at the right time to improve conversions.
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Refine direct mail programs
Many retailers still have catalogs and other promotions (coupons) they mail to prospects and customers. Despite the shift to online these are still an important tool in the marketer’s kit. Given the increasing cost of postage, targeting the right recipients is imperative to maximize ROI and grow sales. Combining your internal customer and engagement data with external sources such as Census, internet behavior, purchase behavior, hobbies, and interests gives richer insights on who is more likely to engage and boost response rates.
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“The ease of use and flexibility of Explorium allows us to launch new use cases on a monthly basis with minimal effort but maximum impact.”

Nadav Yekutiel, Head of Product Analytics & Data Scientist,


Unlock new business value with external data.

Explorium’s External Data Platform improves analytics and machine learning. Explorium enables organizations to automatically discover and use thousands of relevant data signals to improve predictions and ML model performance. Explorium’s  External Data Platform empowers data scientists and analysts to acquire and integrate third-party data efficiently, cost-effectively and in compliance with regulations.

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Example data signals for Retail

Review based information:

  • Business rating and reviews
  • Health score
  • Noise level
  • Average pricing of businesses in area

Consumer Interests and habits:

  • Hobbies
  • Interests by industry: apparel, groceries, music, sports, gifts, art, culture, and more

Business information:

  • Number of businesses nearby by category
  • Foot traffic information: number of visits in the area, places people visited on the same day, etc.
  • Tourist attributes: hotels and attraction characteristics (number of hotel rooms in an area, etc.)

View our Data Gallery to see more examples and learn more.

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