For a service-based business, technology challenges are as numerous as the opportunities. Today’s customers can access a plethora of information via the Internet and view competitive choices with ease. This contributes to a growing demand for interactive and high-quality support within an organization’s customer service, research and marketing departments. Such organizations must be armed with the right data and insights to remain competitive in today’s Big Data environment while maintaining trust with customers.
To do this, customer support executives may collect data and metrics but find it challenging to derive valued insights from this overwhelming amount of information. The rapid adoption of social media channels alone has created an ocean of customer data, and the majority of organizations have yet to integrate social streams. There are plenty of reporting tools available, but they often lack the ability to consolidate and analyze data from multiple sources.
To better understand the massive amounts of customer data, organizations must identify links and trends across multiple outlets, getting down to the source of the issue. In this Big Data scenario, it’s not the volume or velocity of the information that’s the problem — it’s the variety of places in which the information is residing.
In this scenario, the best solution to identify linkages and trends and allow for a better understanding of customers’ situations is advanced unified indexing technology. This is a successful way to connect the dots for customer service agents and significantly impact performance metrics.
Advanced unified indexing technology not only provides access to metrics and analytics but takes the process one step further by presenting collective knowledge about the customer, as well as their products, support cases, and more — all in one place. Advanced search can also bridge the gap between traditional customer relationship management data and social data, retrieving any applicable records. This allows agents to understand the whole picture and take action. Agents can more quickly solve customer challenges the first time, improving resolution time and overall customer satisfaction.
There are many facets to take into consideration when trying to improve the data mining process. A company should evaluate where their internal and external data is coming from and what systems/interfaces that the employees work with on a daily basis. If the end goal of a company is to create actionable insights, leading to positive interactions through even complex situations, then advanced unified indexing technology may be the solution to their Big Data chaos.
Ed Shepherdson serves as Coveo‘s senior vice president of Enterprise Solutions. Ed brings 30 years of experience in the technology industry to his role with Coveo. Prior to Coveo, he spent 18 years at Cognos, now an IBM company, where he most recently served as vice president of Global Customer Support.