WattzOn, a provider of utility bill data solutions, launched a new AI-powered product called SNAP to enable energy and cleantech companies to quickly capture data from utility bills. SNAP supports field sales teams by providing key data in seconds, enabling customized quotes and pricing. SNAP supports the consumer’s online on-boarding journey with its simple user experience and speedy data extraction. WattzOn’s advanced machine learning system returns highly accurate data in seconds.
“Leading solar and energy companies are out in the field, meeting potential customers where they are at. Mobile data capture solutions are critically important for converting leads into customers, and for instantly offering customized plans that meet customer needs and secure profitable operations,” said Martha Amram, CEO of WattzOn. “We delighted to bring this streaming use case to the market, opening up a new way to engage with energy and cleantech consumers.”
How it works
SNAP is an application built on WattzOn’s advanced machine learning system. A streaming data service, SNAP uses a library of pre-trained machine learning models to automatically extract utility bill data from pdfs and images from supported devices. A new utility is easily added to the library, enabling deep coverage in every state. Extracted data is delivered to WattzOn’s customers via API in seconds, ready for integration into CRM, ERP and custom software tools. SNAP is pre-trained for residential utility bills, and can be customized for commercial and industrial utility bills upon request.
“We built SNAP to help our customers smooth their sales experience.” said David Nelson, Director of Product Management at WattzOn. “Our years of market experience have shown that adding the option of data capture from a single utility bill in paper or pdf form increases consumer engagement and sales conversion rates. I’m delighted that our powerful machine learning system can be applied to this important use case, opening up new sales opportunities for our customers.”Tags: sales and marketing, soft costs