Here at Thinking Phones, we talk a lot about the value of advanced analytics as part of a cloud UC platform. We use analytics to help our customers better understand their businesses, but we take the practice well beyond the simple call and messaging reporting that you find in most systems. The example below was created to help understand what was happening in an inside sales environment. What you see is a visual representation of the performance of an inside sales team based on UC data from the Thinking Phones platform, and CRM (contact and opportunity) data from Salesforce.com for the quarter to date.
Each bubble represents one of the inside sales reps on the team. Where that sales rep falls on the horizontal axis is determined by the number of calls he or she made to lead and opportunity contacts defined in Salesforce. Where the rep falls on the vertical axis is determined by the total amount of talk time he or she had with lead and opportunity contacts. The size of the bubble shows the sales performance of the rep, quarter to date, based on closed opportunities.
When plotting these three data sets in this way simultaneously, several things immediately became obvious. First, the most productive reps on the team (e.g. those who closed the most business) tended to cluster in the middle of the chart. This strongly suggested that there is a signature amount of calling and talk time that is characteristic of the successful reps on the team. We started calling this central region the “bull’s-eye of productivity.” But just as the successful reps were clustered in the bull’s-eye, there were several outliers in different corners of the chart. Not surprisingly, two of the reps in the lower left-hand corner were not particularly successful, as they were not putting in the required calling effort. On the right-hand side of the chart, the reps were putting in calling effort, but it wasn’t converting to closed business. Those reps were candidates for additional sales training, as they had challenges either in the early or later part of the sales process.
I like this example because it illustrates the power of combining UC data with other business data to gain insights that wouldn’t otherwise be possible. Looking at a call report and then separately looking at a CRM report won’t give you the understanding that this combined view provides. Furthermore, while the first motivation was to understand the historical performance of the team, this analytical view started to be used as a predictor of future performance. When new reps are added to the team, they are plotted on this chart and managers can see if they are exhibiting the types of UC behavior that will lead to sales productivity in the future. Copious amounts of data are generated through UC activity in businesses today, and this data is largely underutilized and untapped. There is huge potential to help customers understand their businesses better through the analytical use of UC data, especially when combined with other business data.