The Digital Universe (DU) is defined to encompass the sum total of all the world’s digital data collected, generated, processed, communicated, and stored. The size and growth rate of the DU continues to increase at an exponential rate with the estimated size growing to over 44 zettabytes by the year 2020. The bulk of this data consists of unstructured data. We believe that until customer data is analyzed, it lacks the ability to predict the future. This is where Pulse comes into play. We predict the future!

At Pulse, we are creating new ways to analyze unstructured data, creating new sources of data, new ways to apply the analysis to the business, and as a result, new revenue streams are created. We are using new approaches, moving from descriptive to predictive and prescriptive analytics and doing all that in real-time. This means our clients are able to respond and change in real time to what is actually happening in their business. We are not only focused on acquiring new customers for our clients, we are also focused on retaining their existing customers.

Our goal is to identify the potential defectors way before they actually defect.(or better yet, even before they thought about defecting!)

As online retail continues to increase their market share against the brick and mortar store, we understand why there is so much focus put on gaining new customers. But at Pulse, we believe that retaining and further engaging existing customers is a higher priority. Otherwise, the new customers that are gained will be offset by existing customers who defect.

CUSTOMER-CENTRIC DATA ANALYSES

Retailers have vast amounts of data about their customers. One of the challenges is that customer data is “owned” by separate departments. This departments have a tendency to exist as disengaged silos. Each department has a partial view of its own customer but lacks a structure in which to piece together the entire end-to-end customer view across all of the customers' touch points. .

PREDICTIVE ANALYSES  AND ADVANCED TRENDING

While retailers have always used data to attempt to make predictions - like using sales from previous years to estimate next year’s inventory or for future sales forecasts.

Predictive analytics is at a micro-level-down to a specific individual - rather than macro-level predictions based on averages or generalities.

CUSTOMER SERVICE  

ANALYSIS 

Collecting, correlating and analyzing data from customer interactions across channels is the key to transforming the customer experience from nightmare to nirvana. The nexus of big data and machine learning in all its forms, are the underpinnings of well informed, highly efficient and deeply satisfying interactions that benefit both customers and retailers.