Organizations, both contact centers and enterprises, today are charged with key strategic and operational tasks.
They need to deliver a first-rate customer experience, ensuring loyalty and retention. They need to understand what drives customer satisfaction, why certain products are selling more than others, what is the effectiveness of a new marketing campaign, which competitors are being mentioned most often by customers, and in what context, only to name a few.
As the main interface between the enterprise and customers, contact center managers are expected to nurture customer relationships, to understand customer wants and needs and deliver these business insights to corporate functions. All the while, they need to run an operation at maximum cost efficiency.
The key to achieving these critical strategic and operational goals is a multi-dimensional interaction analytics solution.
The Multi-dimensional Analytics Approach
NICE offers an advanced interaction analytics solution that has a multi-dimensional approach, by which organizations can locate and analyze the most important interactions that come into their call centers, the ones that contain strategic insights into how they can achieve these goals.
NICE’s multi-dimensional approach enables organizations to automatically sift through the thousands, or tens of thousands of calls that come into the call center on a daily basis, and focus only on the relevant ones. NICE’s multi-dimensional interaction analytics solution includes a range of speech analysis capabilities, such as content analysis by key words and phrases, emotion level, and text mining techniques.
The first step is to perform a mass-analysis of customer interaction content on three levels: speech data (i.e. speech analytics), interaction data (i.e. CTI generated: talk pattern analysis, call duration, queue times, number of holds, number of transfers), and customer data (i.e. CRM generated: demographics, customer’s purchase history, etc.).
Next, the calls will be categorized. They can be categorized by products, technical issues, billing inquiries, or analysis type – such as ‘satisfaction’. Next, trends can be mapped graphically to reveal whether there was an increase or decrease in call type or in satisfaction levels. Finally, a root-cause analysis report will be generated to provide managers with an understanding of what went wrong, or right, and why.
Improving Operational Efficiency
Among a contact center’s top cost-intensive areas for improvement are First Call Resolution (FCR) rates, Average Handling Times (AHT), and Self Help Enhancements.
Self Help Enhancements: Major European Airline
A major European airline implemented NICE’s multi-dimensional analytics solution across all of its contact centers which handle ticket sales and customer service inquiries for nearly 2,000 daily flights.
The airline also wanted to better understand how they could cut costs by picking up on call topics which could be handled without an agent, either through their website or IVR system. The first step was to gauge the user-friendliness of their website. By analyzing call content through key words and phrases, such as “website” and “online” they found that a large percentage of the calls they were receiving started out with the phrase “I tried to do this online”. They then created a correlating category, automatically analyzing these calls – to create a report for the MIS department with a list of recurring issues. Once the MIS department had made the required changes, the airline experienced a drop in call volumes – which resulted in a correlating decrease in costs, and many customers who were no longer frustrated.
Strategic Initiatives
Another critical benefit of a multi-dimensional interactions analytics is its ability to better understand which customers are at risk of defecting to the competition and be proactive in ensuring that they stay.
Case Study: Major US Financial Services Company – Customer Retention
One of the US’s leading financial services company, with a range of products including mutual funds, retirement planning, and brokerage services, among others, had several strategic initiatives, including improving customer retention.
To improve customer retention, a week’s worth of customer churn related calls were analyzed, using transcription and text mining to create a report that listed all competitors with more than 10 mentions, which were listed in descending order in terms of number of mentions. Not only were the top competitors identified, but it was also revealed that while competitor X may have gotten the top mentions, competitors Y and Z seemed to be taking the bigger accounts. It was also realized that another competitor consistently had one of their staff on the line to assist in the move.
The call center could then deliver this information to the customer retention team directly from the interaction analytics solution, via email alert which could look as follows:
Subject: Competitive intelligence:
Dear Manager,
Customer interactions mentioning competitor’s name – have exceeded the defined threshold over the last 48 hours.
Click on Interaction Analytics Solution to learn more.
Category Name: Competitive Intelligence – Related Calls
Current results: 575
Last 30 days average: 480
Threshold: 20%
The retention team could now study the competitive offering and understand why customers were churning. This information is then delivered to the marketing team which can make the requisite changes to their product offerings and services to better ensure customer loyalty.
Interaction Analytics Best Practices
Getting the most out of an interaction analytics solution entails, first of all, obtaining early executive sponsorship and making the strategic and operational goals discussed above a priority for the organization. The team involved will need to identify and map specific business objectives up front. Once objectives are prioritized, they will need to define the implementation phases, beginning with ‘low hanging fruit’. Engaging an experienced interaction analytics consulting team can expedite the process, and eliminate trial-and-error for a more efficient and effective discovery process and implementation.
The other half of the coin lies in the solution’s capabilities. The solution should be able to perform a mass analysis of as many interactions as possible. It should have drill down capabilities, enabling users to get to the details of the interaction and other relevant data with just the click of a button. It should be able to create automated call categories, define thresholds and set alarms – as with the customer intelligence example discussed above.
The optimal interaction analytics solution should include the following capabilities: combination of two or more speech analytics techniques (content search by key words and phrases, transcription, phonetic indexing), emotion detection, CTI analytics (speaker separation and talk pattern analysis), screen content analytics, quality evaluation scores, customer feedback, automated call categorization, threshold definition, and alarms. It should be able to capture or tag any type of interaction (voice, VoIP, chat, email, co-browsing), by agent screen activity, or by type of information that appears on the screen (such as customer name, segmentation, monthly bill, etc.). It should also be fully interoperable with home-grown or third-party applications, such as CRM, ERP, e-Learning, e-mail/Chat, Help-Desk applications and more.
Furthermore, when it combines with quality management, workforce and performance management the contact center can achieve optimal business performance. Interaction analytics enables organizations with precision quality monitoring, for tapping into customer interactions with strategic insights – insights which a random sampling is most likely to miss. It also enables contact centers to better link its customer interactions with its workforce planning and management processes. Workforce management combined with an interaction analytics-driven agent coaching solution can efficiently manage and optimize scheduling of coaching sessions to ensure the success of knowledge transfer.
Finally, when combined with interaction analytics a performance management solution can generate more accurate reports that are directly linked to customer calls. These reports can be automatically delivered to key business functions in the organization to determine which actions need to be taken to improve performance (i.e. new product features, a revised marketing campaign, better scripts for agents, etc.); and enable KPI-based (key performance indicators) management tools that help set business performance goals and objectives for employees.
Organizations today are looking for quantifiable, accurate, and immediate insights into critical issues such as operational efficiency, customer loyalty and retention, and marketing/sales effectiveness. With a multi-dimensional interaction analytics solution in place, the contact center today, as a hub of customer interactions, can enable organizations to leverage these interactions to meet their most critical operational and strategic goals.
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