BID2WIN Software Inc. Names 2010 Client Referral Program Grand Prize Winner

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Portsmouth, NH, January 11, 2011 – BID2WIN Software Inc. is pleased to announce that the grand prize winner of the 2010 Client Referral Program is Mike Hoffman of Alan’s Excavating Inc. in Augusta, Kansas.

As the grand prize winner, Mike will receive a custom vacation—selecting the location (or locations), accommodations and travel arrangements of his choice. Mike was selected in a random drawing of those who referred new business through the BID2WIN Software Client Referral Program throughout the course of 2010.

The Client Referral Program, which runs annually, was created in 2006 to reward clients for referring potential business to BID2WIN Software. In 2011, with the addition of BUILD2WIN Logistics, BID2WIN Software clients will be able to earn even bigger rewards! Each client who refers a prospect that purchases BID2WIN, BUILD2WIN Field, or BUILD2WIN Logistics by year’s end will earn a $500 American Express gift card for each product purchased—up to $1,500! Plus, each successful referral will be entered into the drawing for the 2011 grand prize.

To learn more about the 2011 Client Referral Program, visit www.b2wsoftware.com/company/referrals/.

Located in Portsmouth, NH, BID2WIN Software Inc. offers state-of-the-art enterprise-class construction management solutions for the infrastructure industry worldwide, and is the leading provider of Windows-based cost estimating and bidding solutions. The company’s flagship product, BID2WIN Estimating & Bidding, is the first estimating and bidding software built from the ground up with a true client-server architecture utilizing Microsoft .NET and SQL Server technology, offering a unique competitive advantage and superior performance and flexibility. BID2WIN helps leading construction firms increase profitably through more accurate and efficient estimating and bidding. And BUILD2WIN Field is the first browser-based solution of its kind, allowing real-time collection and analysis of production and related job performance cost data.