Innovative Online Tool Helps Consumers Pinpoint The Right Appliance, Increases Showroom Sales For Home Furnishing Retailers

Case study reveals that PERQ’s online guided shopping solution, including new appliance assessments, helps educate shoppers and generated over 14,000 leads in a 90-day period — boosting overall lead-to-sale conversions to over 30% for Big Sandy Superstore

Indianapolis, IN (PRWEB) - PERQ today announced the launch of new appliance assessments to help online shoppers determine which refrigerator or washer and dryer is right for them — and it is already increasing leads and sales conversions for home furnishing retailers. In a new case study, PERQ’s online guided shopping solution generated over 14,000 leads and an overall 30% increase in lead-to-sale ratios in just 90 days across 18 Big Sandy Superstore locations in Ohio, Kentucky and West Virginia, while the newly launched appliance assessments delivered a 22.5% lead-to-sale conversion in their first 60 days on the websites.

The new assessments ask shoppers targeted questions about their appliance needs, and then uses artificial intelligence (AI) to help them narrow down selections, making it easier to pinpoint the appliance that is best for them. The assessments create a better online experience on home furnishing retailer websites and a much more “sticky” online customer journey, while also providing sales personnel with key data points that help them close the sale in the showroom.

“PERQ is focused on helping retailers improve the relevance and effectiveness of their online conversations with customers who are making big decisions about expensive, and often complex, products, and then transitioning them into the showroom to complete their purchase,” said Scott Hill, Executive Chairman & Co-Founder of PERQ. “The results of our new appliance assessments confirm that today’s consumers value being able to ‘self-serve’ online, even when completing the purchase offline.”

Robert Van Hoose, CEO of the 65-year-old superstore chain, said the appliance assessments have already revealed that 77% of Big Sandy’s online shoppers are ready to buy now or within 2 weeks – making them hot leads that require immediate attention.

“The value is in the conversation we’re having with customers – both online and offline and PERQ’s assessments help us create better online conversations that make customers more willing to come into the store,” said Van Hoose. “In addition, we are gathering more comprehensive information about the customer and their needs – which we’re able to put into the hands of our sales team who can now follow up more effectively to complete the transaction.”

The Big Sandy Superstore case study offers a comprehensive picture of how improving the customer journey improves conversions both by delivering a great experience and by providing key consumer data points that fuel the sales conversation in store. Click here for details (https://perq.typeform.com/to/KBgtE5?utm_campaign=Big_Sandy_Superstore_Case_Study&utm_source=PR&utm_medium=pressrelease&utm_term=homefurnishingsutm).

In addition to serving home furnishing retailers, PERQ’s AI-powered assessment solutions are also being used to improve the online customer journey by automotive retailers and multifamily leasing companies nationwide.

About PERQ
PERQ (http://www.perq.com), boosts website conversion through its online guided shopping solution which leverages artificial intelligence to dynamically change existing websites to deliver the next best step in each buyer’s shopping journey. As experts in online consumer engagement and behavior, PERQ leverages over 10 million consumer data points, along with real-time visitor behavior.

Founded in 2001, PERQ solutions are used by more than 1,000 businesses in the home furnishing, auto retailing and multifamily industries. Its brands have been named to the Inc. “500 Fastest Growing Companies in America” list on three separate occasions. In 2017, PERQ won the Gold Stevie® Award for lead generation software and Product of the Year in the Big Business Awards.