While data sources should be varied, B2Bs generally focus on two different types of data. The first is descriptive data, a category that includes demographic and firmographic information about an individual buyer and the company that buyer works for. This encompasses basics like names, titles and contact details. But it can also add context like company organization charts, performance reports or even budgets.
The second type of data is behavioral data, which adds additional insight into buyer’s interactions with marketing and sales touchpoints across the web. This type of data tells things like what pieces of content have been downloaded, which web pages were clicked and which emails opened.
No. 2 Data needs to be analyzed
Of course, all of the data in a B2B marketer’s arsenal is pretty useless if it isn’t properly managed and then analyzed to glean actionable insight that both marketers and sellers can use.
July 2017 research from Bluewolf found that more than half of US sales professionals have invested in predictive analytics that apply statistical models and forecasting techniques to their data through machine learning or artificial intelligence. Other popular types of analytics include descriptive, which aggregates and mines data to provide a summary of historical data, and discovery, a method that searches through data for patterns to reveal previously unclear associations. Other less common implementations of data analytics are diagnostic, prescriptive and contextual.