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Bloom Intelligence Introduces Cloud-Based WiFi Marketing, Analytics Platform

Bloom Intelligence, a provider of sophisticated data analytics, announced a new cloud-based Wi-Fi marketing and analytics platform that provides advanced tracking metrics for omnichannel retailers and the hospitality industry, specifically restaurants.  

Seventy percent of consumers shop at brick-and-mortar stores, but increasingly prefer the convenience of digital purchasing. Bloom Intelligence mixes the digital and in-store experience to give retailers the essential analytic tools they need to act on consumer behavior in real time. The platform is also customizable for restaurants that benefit from the ability to track guest behavior and trigger deals in real time.

The Bloom Intelligence platform gets ahead of customer sentiment when they are on the premises by immediately sending offers and suggestions to influence purchasing decisions. The company also has the  ability to send deals to people both before and after they visit the retail location and remarket to them just as they are about to exit the store or restaurant.  

 The goals are to increase visit frequency and retain churning customers. The company’s unique capabilities will soon encompass heat mapping and on premise-presence messaging based on the customer’s location in the store. The Bloom Intelligence team provides seamless, white glove service to clients, encompassing hardware and software, implementation and ongoing system management. Everything is completely firewalled, including the highest level of security.

Customers are encouraged to register for in-store WiFi, which is both a value-add service for customers and an asset to retail and hospitality marketing and operations. Data is collected whether the consumer logs in or not, and Bloom Intelligence is able to interact with a customer who does not have the store or restaurant’s mobile app installed. The platform is also able to automate customers’ onboarding to third party applications, such as loyalty programs and mobile apps.

Bloom Intelligence triggered offers utilize advanced segmentation based upon demographics, presence analytics, and purchasing behavior. Acting on actual customer behavior, Bloom Intelligence automates one-time, repeating and triggered promotions that align with individuals’ shopping or dining behavior. Specific triggered promotions can be built around several metrics, such as:


  • At Risk – sends an offer to people who Bloom Intelligence has marked as having broken their regular visit pattern.
  • Milestone – used to send an offer when customers reach predetermined milestones such as their 10th, 25th, or 100th visit. Offers can also be generated annually, for example, on the anniversary of a customer’s first visit to the store or restaurant.
  • Loyalty – creates a virtual loyalty program that works like good old-fashioned “coffee club” punch cards. Customers will get an offer every time they reach the number of visits specified by the retailer or restaurant.
  • Rolling – rewards frequency and consistency based on number of visits and time period set by the retailer (for example, 3 visits in 10 days); an offer is sent when customers meet these criteria.


In addition to triggered marketing, customer data is collected to measure customer sentiment in real time with Bloom Intelligence ratings and NPS score capabilities. Their analytics also answer key omnichannel retail questions, including:


  • What is the projected lifetime value of a specific customer?
  • How can you use customer data to optimize and measure return visits?
  • How do you build a truly integrated consumer experience?


Metrics are made available to the retailer via the proprietary Bloom Business Intelligence Platform, an easy-to-read dashboard that simplifies interpreting and acting on the data to:


  • Measure customer behavior and the actual ROI of specific deals that drive customers back into the store.
  • Use special offers to drive social interaction, encourage customer reviews and rescue at-risk customers.
  • Track and project retail traffic flow by week, day and hourly increments.
  • Decrease customer churn rate by creating campaigns for first-time customers that encourage return visits.
  • Identify most frequent customers through built-in segmentation for easy targeting.



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