Finding great leads has always been the struggle of the sales rep. With Lime Go we have have taken upon us to lessen this pain or even remove the problem. Great leads to all sales reps all the time. In Lime Go we have millions of possible contacts built in, always kept up to date. With simple filters and searches you can narrow down your segment in seconds based on all types of properties; geography, financials, growth, industry etc. Once you have your segment it is a breeze contacting your potential leads and deepening the relationship with Lime Go. Yet we felt that there was something missing in Lime Go to truly help the sales rep on her quest to find great leads
With all this data, filters, statistics we felt we had reached a point we never intended – complexity. A sales rep does not care that we have millions of contacts, nor does she care about all filters in Lime Go or properties of of the contacts. All she cares about is having great leads at her disposal. Adding more data, filters or properties just wouldn’t solve this need.
The science of teaching a machine to understand a very specific subject, Machine Learning, has exploded the last few years. Digital personal assistants, image recognition and self driving cars are now all part of our vocabulary.
During this year we have been training a machine to something we think you will enjoy; finding good leads for you. What it does is to look at all your customers and find what they have in common. Are they all in a specific industry? Do they all have about 10 employees? Are they all situated in the same town?
Based on more then 20 different properties we identify a pattern that is a potential customers for you. We have created a bold new page in Lime Go, called Discover where you can find new leads recommended specially for you. We are releasing this feature today as a public beta. Send us your interest and we will add you to the beta. For the recommendations to work you will need at least 30 customers, however the more customers you have, the better the result will be.
You can find more information about this feature here >