While working on an augmented reality project, Myles Leighton and Jennifer Ganther were looking for a way to market their product to local bars and restaurants in Austin, TX. Myles spent countless hours in front of the computer, tediously searching websites for email addresses and phone numbers of possible leads. He admits it wasn’t a pleasant experience:
“Having to go through and individually search for contact information on each one of these businesses’ websites was an incredible pain. This process took up a large portion of my time that could have been easily spent somewhere else. Furthermore, if I want top-of-the-funnel info, I have to pay a lead gen company a small fortune.”
In the marketing world today, finding lead contact information is done in one of three ways: manually through online searches, using an email scraper system, or subscribing to a corporate lead generation service. An email scraper system effectively “scrapes” the web for contact information based on the type of business the user is searching for. However, the outputted lists are often unreliable, full of typos and inaccurate results.
The results are more accurate and relevant with a corporate lead generation service such as Lead Genius or Salesgenie, because they’ve hired a team to do the manual work. However, due to this needed manpower, the cost of service is incredibly high and only larger companies with the necessary capital can afford to utilize their services.
Unsatisfied with their options, Myles and Jen thought, “What about the small startups and middlemen in the business game? Why can’t there be a system that combines the lists generated by the cheaper, automated email scrapers while still offering the precision and relevancy of larger lead generation businesses?”
Thus, the idea for was born. The duo decided to create a cutting-edge system that delivers premium contact information and leads using artificial intelligence, machine learning, and natural language processing with the goal of improving time and costs, all while making it more accessible for a larger market. After UI testing of the prototype revealed positive results, they knew they were on to something.
works by feeding it torrents of data and letting the cloud-powered artificial intelligence crunch for accuracy and relevancy. After entering a few simple terms to identify your target audience, the platform easily outputs desired information and you can use this information to create marketing lists, add data feeds and users, or push it over to your CRM.
The company’s chief engineer, Barrett Simms, explains that SugarBot “uses to perpetually scan various search APIs and data repositories for contact information, which is then stored in a super database.” SugarBot offers a complete customer acquisition dashboard to help you find people and businesses, track and perfect your communication progress, and even provide reporting of your success. No more sitting in front of a computer hours at a time, deciding where to search next for leads. SugarBot walks you through each step so you no longer have to be a marketing expert.
After Barrett and the team’s data scientist, Hyejee Bae, tweaked SugarBot to its current patent-pending state, the team measured its performance and the findings were glorious. Finally, SugarBot became the first high-relevancy, ridiculously time-saving product that even a start up on a shoe-string budget can afford.
Making sure SugarBot didn’t just work right, but work easily for the user, Myles added some final touches from his behavioral economics repertoire to leverage a series of principles that he designed to keep the user experience light, rewarding, and immersive. The product provides the perfect balance of hand-holding and autonomy, allowing the user to create and execute their own strategies so they walk away feeling happy, rewarded, and that they owned the process.
To sweeten the deal even more, Jen added the cherry on the top with her experience in the defense contracting world. “It is very difficult to find people and resources offshore, especially when you don’t know the language,” claims Jen. To solve for this, she developed a natural fitting multi-language component to the system. “We once used SugarBot to get us contact information for all of the coffee shops in Italy, so we could simply send them an email thanking them for existing. Nothing like real Italian coffee.”
By combining machine learning, AI technology, and viral behavioral techniques, SugarBot helps marketers and businesses reach contacts relevant to their preferences and patterns instantly, all at an exceptionally low cost. Although only in its early stages, it’s safe to say that SugarBot is already showing promising potential of becoming the world’s most effective customer lead acquisition platform. Take that, box.