Retailers need a level setting analytics platform to succeed in the ecommerce world
Boomerang’s flagship product is a Dynamic Pricing Platform, which currently powers millions of pricing decisions across the world’s biggest retailers. Shedding light on the key offerings of the firm, Hariharan says, “At the core, our analytics platform consists of two key components. One is external Competitor Intelligence. Given the retailers’ products, we provide almost realtime intelligence about products on competitor websites and their corresponding prices. Second is internal Profitability Intelligence–for every online t ransact ion , we track unit level profitability by baking in numerous variable costs such as COGS, shipping, vendor funding.
”Staples.com, the #2 online retailer after Amazon, leverages Boomerang for dynamic pricing. “The initial results are very encouraging and we are planning to roll out Dynamic Pricing for the entire site in a phased manner”, said Hariharan. “Our system quickly identifies opportunities for price optimization and we have been able to show incremental revenue and margin impact within 4 weeks”. Other customers include Groupon and Radioshack.
Pricing Analysts and Category Managers use Boomerang software to create, plan, execute and measure the impact of various pricing strategies. They set high level business goals such as revenue or margin objectives at a category/subcategory level and perform “what-if” analysis to compare outcomes. Category Managers can also monitor price competitiveness for similar and substitute products and make informed decisions on Private Label and New Product pricing. They can also spot deals and MAP violations on competitors’ websites to negotiate better rates with suppliers.
Boomerang Commerce is headquartered in Santa Clara, CA and has a product development center in Bangalore, India. “We are an enterprise team with an Amazon DNA. Most of us are from Amazon and have deep expertise in retail, analytics and enterprise software.” said Hariharan. “We are investing heavily in building Amazon-scale infrastructure to support the large scale analytics needs of our customers. We are ramping up our team of data scientists to solve seminal big data problems in large scale web crawling, text analytics and visualization. We just rolled out a new capability that allows our customers to do A/B testing on pricing strategies. We are applying machine learning, portfolio optimization theories to solve price optimization. In future, we will be implementing game theoretic approaches to predict competitor reactions to price changes.”