When it comes to choosing data providers, there are few criteria more important that data quality. But what does “quality” mean? If you care about data quality, it’s an important question to ask, because different providers define it in different ways.
At Leadbook, we define data quality across 3 dimensions:
- Accuracy: Is the information correct? This is measured for each individual field.
- Completeness: How much of the essential information is included
- Coverage: How much of the market is accounted for in the data set?
For each of these 3 data quality dimensions, we have extraordinarily high standards and apply rigorous methods to achieve them.
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.