Data—and a lot of it—has recently begun flooding into businesses. According to Baseline magazine, 90 percent of the world’s data has been created in the last two years.

Sales teams especially have begun to see the benefit in using data to make accurate goal forecasts. But there’s often confusion about what data to mine—and when. 

Among the noise around big data is another type of data that hasn’t yet found its way into the sales analytics limelight: small data. Named for the information they represent, both big and small datasets have their advantages and disadvantages. But as big data becomes increasingly overwhelming for sales teams to comprehend, small data is gaining its edge. 

Below are five ways that small data can often prove more valuable for sales teams to mine and interpret:

1. Small Data is personal; Big Data is impersonal

Big data is extremely beneficial to measure overall sales organization results, but often individual team members want to know how they are specifically performing. Small data can hone in on targeted members and decipher the right behavior that leads to increased performance. 

To use small data effectively, sales leaders must identify Key Performance Indicators (KPIs) to track. These KPIs can then be broken down to the individual sales rep level in order to uncover what’s working and what’s not. This also helps eliminate educated guesses by sales managers that often don’t match up to actual team members’ results. 

 2. Small Data is actionable; Big Data is exciting

Receiving an influx of big data is often exciting and interesting, but it’s very difficult to mine the information for actionable results. If your sales team cannot use the data to drive change and impact bottom-line results, then it doesn’t hold much value.

Because of its targeted nature and flexibility, small data is much easier to interpret and can immediately be used by sales managers or team members to make changes—fast.

3. Small Data is tailored; Big Data is broad

A major difference between big and small data is that big data is more about capturing as much information as possible, while small data focuses more on the outcome that the data can produce. Small data is typically based on customized information related to a job role—such as a sales manager—whereas big data is organization-wide.

 4. Small Data is real-time; Big Data is historic

Small data provides insights to uncover sales statistics and trends immediately, helping to leverage data for positive, real-time results. Big data is traditionally based on historic metrics that are beneficial for understanding past performance, but don’t really help looking forward. To make accurate and sound decisions based on current sales performance and trends, small data is the best way to go.

5. Small Data is pushed to you; Big Data must be pulled

Push and pull are the two different methods of moving data from its source and reporting on it.

Big data lets you pull all the data you have, whereas small data allows an organization to pose specific questions or identify target information and outcomes.

Small data allows for targeted and strategic reports to automatically get pushed to sales teams with no effort. Reports are easily transmitted to a sales leader’s email, enabling him or her to view the reports and then relay the information to the team members. Reports for big data, on the other hand, must be pulled by sales leaders—something they don’t have the time for.

Both big and small data have their specific benefits, but it’s often small data that is most efficient and beneficial for sales leaders. Small data delivers visibility into what’s going on within the funnel to help guide effective sales and coaching strategies. By educating themselves and their teams on the different kinds of data available, sales leaders can better position their organization for greater future success. 

 To learn more about harnessing the power of data, visit the website, or take a look at the free e-book.