Home Business Boomerang Commerce updates retail app, adds machine learning

Boomerang Commerce updates retail app, adds machine learning

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Boomerang Commerce, a US-based retail technology company, has launched an updated version of its flagship Price Performance Management (PPM) application which is a technology solution designed to help chief merchants and their teams make better pricing decisions at scale.

By combining machine learning technology with an interface designed specifically for merchant workflows, the system is designed to increase revenue and margin growth, save time, enhance collaboration and perfect price discipline for omni-channel retailers. The application was demoed today at the eTail West Conference in California.

“The chief merchants leveraging Boomerang Commerce’s Price Performance Management application tell us it’s like having the best and brightest from the industry’s top retailers working alongside their teams to guide and mentor them through pricing best practices that drive real results,” said Guru Hariharan, CEO, Boomerang Commerce.

Boomerang Commerce addresses retail challenges

According to the company, today’s large retailers are relying on legacy systems that were designed before e-commerce and omni-channel commerce existed. As a result, no single system is managing and optimizing the customer experience across channels – stores, web and mobile touchpoints.

Boomerang’s PPM solution claims to bring data from these disparate sources together and helps merchandisers choose pricing strategies that increase revenue without eroding margin.

Key benefits include:

– Increased revenue and margin growth
– Reduced time and effort
– Enhanced collaboration
– Improved price discipline

Enables chief merchants to capture market share

Boomerang claims that with its new action-driven interface, retailers can quickly assess the current and future health of their businesses, address key areas of opportunity with just a click and see the impact of their choices, building institutional pricing knowledge that can be leveraged to further drive business performance.

The system features:

  • Machine learning technology: Using advanced, machine learning algorithms, the Boomerang platform continuously processes and combines large volumes of external market demand signals with internal retailer data to then identify opportunities and recommend pricing strategies optimized to meet goals.
  • Pricing predictions: Based on current pricing data analytics, the PPM system simulates and predicts how well a given strategy will perform.
  • Strategic pricing recommendations: Users can choose priority parameters, and the PPM application will recommend pricing optimizations that will help users meet their margin and revenue goals.
  • Pricing alerts: The PPM system can be set up to automatically notify users when certain products or categories fall below a performance threshold and suggest corrective actions users can quickly take along with the expected results from those actions.
  • Pricing strategy playbook: To drive fast time-to-value for clients, PPM comes with proven, out-of-the-box pricing strategies that clients can quickly deploy to take actions, simulate results, test and learn, and continuously improve.
  • Intuitive user interfaces: Boomerang’s new dashboard unifies the data that chief merchant teams and other business users need to make rapid decisions without needing to go to pricing analysts or IT for multiple reports.

Pricing and Availability

The Boomerang Price Performance Management application has been made available now and is delivered as a software-as-a-service (SaaS) subscription. Its implementation reportedly takes 30 days, and merchandisers can start taking action on the advanced data analytics and recommendations immediately following.

Sharmistha Mukherjee
A tech savvy humanBOT, Sharmistha is a professional writer A tech savvy humanBOT, Sharmistha is a professional writer who engages in technical writing to simplify the use of a product or service. With a high inclination towards IoT and Artificial Intelligence, she fancies exploring all plausibilities around the subjects. Her interests revolve around connecting to people and excavating the "unexplored" through first hand investigation.