How is Leadbook different from professional networking sites such as Linkedin?
Firstly, Leadbook is designed for Sales & Marketing teams and allows downloading of prospect information, lead enrichment and true CRM connectors, all of which are not available on social networks.
Secondly, Leadbook gives you a complete picture of your lead from thousands of sources, including verified business contact emails.
Finally, Leadbook lets you connect with leads in any way you choose. LinkedIn’s InMail looks like SPAM with no corporate branding, rich text formatting, or ability to attach collateral.
How often does Leadbook refresh its organisation and contact data?
We currently update our organisation and contact profiles every quarter. The business contact email is verified in real-time when a user decides to unlock a contact profile.
Why is data quality so elusive?
Business data, by it’s nature, is ever-changing. Even the best data sets begin to change as soon as they are assembled. However accurate your data is today, it will be less accurate tomorrow. So, there is no such thing as perfect data, but make no mistake, there are better and worse data, so its important to know what you are getting.
At Leadbook we are committed to providing the best data set, and we have built the technology and processes to do that. We are obsessive about data quality and we are constantly working on ways to further improve what we deliver to our customers.
How do we measure data accuracy?
For most users, Data Accuracy is what matters most. At Leadbook we are obsessive about continuously improving the accuracy of our data. We constantly measure it through regular sampling.
Here is how we do it: Each quarter, we randomly sample 100 company profiles with contacts. To determine accuracy, we manually check each of the main fields against various information sources: company websites, LinkedIn profiles, marketplaces, and other sources. Each data must be corroborated by at least one of these credible sources. Accuracy is assessed field-by-field, and our goal is to reach a benchmark of 85% average accuracy score across all fields and records.
We use the learnings from this sampling to fix specific errors and, more important, assess the quality of our sources and improve our methods for processing and refreshing the data.