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    Five Ways Contact Centers Use Analytics to Make Smarter Business Decisions

    It’s no secret that Big Data is having a positive impact on the contact center industry. And as businesses are faced with growing amounts of data on everything from the effectiveness of their marketing strategy to individual customer preferences, it is important to identify the right systems to make use of this information.

    In today’s Big Data age, businesses are increasingly turning to analytics as the means by which to make smarter business decisions from the data at their fingertips. In fact, a recent study found that top-performing organizations are using analytics five times more than lower performers. This is a true testament to the power businesses can unlock from great analytics.

    While most organizations can agree on the burgeoning need for analytics products in the contact center, there is still some debate around how to best use these solutions to improve business outcomes. Arnab Mishra, senior vice president of products and solutions at Transera, a cloud contact center analytics provider, shares the top five ways that contact centers can utilize analytics to make better business decisions.

    Five Ways Contact Centers Use Analytics to Make Smarter Business Decisions - slide 1

    Analytics in the Contact Center

    Click through for the top five ways that contact centers can utilize analytics to make better business decisions, as identified by Arnab Mishra, Transera senior VP of products and solutions.

    Five Ways Contact Centers Use Analytics to Make Smarter Business Decisions - slide 2

    Identify High-Value and At-Risk Customers

    In contact centers, no two customers are exactly alike, and every customer that interacts with an agent will have their own impact on the company. Customers who frequently engage or often make purchases should naturally be a higher priority than first-time callers. Likewise, extremely dissatisfied customers calling in are at a higher risk of leaving your business than those calling with positive remarks or non-urgent questions. By applying analytics to discover the frequency and sentiment of each caller’s previous interactions with your company, contact centers can determine whether they fall into one of these two categories and, if they do, set up the right procedures to handle high-priority and high-risk calls first.

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    Eliminate Unnecessary Steps in Operational Procedures

    No organization can be 100 percent efficient all of the time. The same is true for contact centers as they address a myriad of customer issues. However, by analyzing key data points, such as average speed of answer and transfer frequency, the contact center is able to pinpoint staffing issues, or procedural inefficiencies and redundancies. If answer time is below the organizational average for a particular contact center, for example, businesses will know they should research the root cause of the problem. Similarly, if the analysis reveals that callers are made to go through several unnecessary steps before they reach the proper agent, businesses can create new routing procedures for more efficient and better customer experiences.

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    Determine Customers’ Purchasing Propensity

    A customer’s preference for specific products and services is affected by demographic attributes such as age, gender, income and location, and is often indicated by past behaviors. After collecting and tracking customer data, contact center managers can use analytics to determine which products and services a customer would be most interested in. Businesses should provide agents with this customer information, and train them how to offer callers the specific solutions that they will be most open to hear about and likely to purchase.

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    Understand and Capitalize on Consumer Trends

    Your customer base provides you with a useful snapshot of your market as a whole, and what both current and potential customers want. By analyzing contact center calls for the needs and requests made by your customers, you can tailor products and services to what would interest a larger customer pool. Historical data from customer-agent interactions, for example, might reveal indicators of what products customers are looking for but not finding, so businesses can develop product lines that will bring in the most profits.

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    Identify Priority Areas for Agent Training

    Contact centers assign agents skills based on criteria that are sometimes objective and sometimes subjective. But they could score agents for different tasks by looking at the business outcomes of their customer interactions over an extended period and statistically analyzing their performance. This will reveal the agent’s indisputable real-world strengths and weaknesses, and will help the contact center prioritize routing of calls to the agent best suited to handling each issue. However, agents will sometimes have to deal with calls in areas where they are not as strong, especially in times of company crises. Therefore, analysis of agent weakness is critical, so businesses can identify where to increase agent trainings. After all, in the end, it is all about how well each agent serves each customer.

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