CallMiner

Simple Health, a full-service health insurance brokerage, experienced rapid growth, expanding from four call centers with 170 agents to seven call centers with 410 agents. With this growth, the company faced the challenge of effectively monitoring and training new agents. They were particularly interested in ensuring that all agents adhered to their carefully developed scripts and responded appropriately to sales objections. The company needed a solution that could capture and analyze data from their contact center operations to support their objectives.

Stoneleigh Recovery Associates, a debt recovery company, was facing challenges in monitoring and ensuring compliance in its operations. The company was manually monitoring a few calls each month by each of its approximately 100 agents. A quality assurance (QA) manager would listen to the call and score it using a scorecard of Stoneleigh’s requirements and best practices. However, this method was not comprehensive and left room for non-compliance. When the Consumer Finance Protection Bureau (CFPB) updated its regulations for debt collection, Stoneleigh’s largest customer requested that some modifications be made to the company’s approach to compliance. This prompted Stoneleigh to look for a solution that could enhance its technology platform with next-generation automated interaction analytics.

British Gas, a leading energy supplier in the UK, was keen to unlock the potential to better understand agent conversations in a digital environment. The company had concerns that much of the sales activity of the digital agents was being under-reported. Many WebChat sessions would start and end with a simple query, and many customers would follow up with a visit to Web Self-Service or voice contact. Without any data linkage or visibility into the subsequent customer journey information, no sales activity was attributed to the digital team. The company wanted to assess the validity of this theory and improve the visibility of agent performance by allowing CallMiner to mine all promotional chats.

Afni, a business process outsourcing (BPO) services provider, wanted to improve the quality of work performed in its contact centers by identifying training opportunities and improving the training and coaching it gives its more than 9,000 agents. The company was firmly committed to quality training, but wanted to more accurately identify areas for performance improvement and then make the training more targeted and effective. Afni recognized that the keys to optimizing customer contact outcomes including raising customer satisfaction among the clients’ customers it contacts, improving performance on sales calls, and increasing its first call resolution (FCR) rate. It specifically wanted to use analytics to learn what language was used and what other specific behaviors occurred on its calls. The idea was to assess the best outcomes for contacts, determine which agents achieved those results, benchmark what those top performers did and apply it across all agents through training, while also using coaching to bring agents that lagged on KPIs closer to the norms.

Bluegreen Vacations, a timeshare and vacation club management company, was facing a high agent attrition rate in its 175-seat call center in Indianapolis. The churn was particularly high in the first month as new employees often discovered that the life of a call center agent wasn’t what they thought it would be. The churn rate settled after the first month, but then approximately doubled starting in month five. Bluegreen was convinced that its CCR attrition reduced morale, increased the cost of running the contact center and ultimately had a significant impact on customer experience results. The company wanted to give the managers and quality assurance (QA) staff insight that could improve hiring, training and coaching to reduce turnover.

Frontline Asset Strategies (FAST) is a rapidly growing call center that provides consumer-focused and compliance-based customer care, call center, and collection services to various industries. The company was facing challenges in continuously evaluating and improving collector performance. They also wanted to ensure better compliance with company policies and laws, and realize operational efficiencies through streamlining internal processes. Before implementing Eureka Interaction Analytics, FAST used manual scorecards to evaluate and score their collectors. However, this method only allowed for the evaluation of about 1.2% of the 250 calls each collector handles each month. The company knew that this was unlikely to be representative of true performance and that it was missing out on the potential benefits of the insight provided by measuring all 100% of their interactions with consumers.

Nationwide Credit Corporation (NCC) is a large collection agency in the mid-Atlantic region, providing collection services to various industries since 1967. The company was looking for ways to improve its compliance adherence, agent monitoring, and reporting capabilities. They also wanted to enhance collection rates and customer experience for their clients. With increased focus on CFBP and FDCPA regulations, NCC aimed to create a full compliance safeguard to minimize complaints, escalations, risk of fines, and legal actions. They also wanted to optimize their QA efficiency to develop agents into better collectors and increase their productivity. To achieve this, NCC needed to monitor, score, and analyze 100% of its agents’ interactions.

Nautilus, a global fitness products company, was facing challenges in managing its contact center efficiency and customer experience. The company was struggling with a cumbersome caller verification process that was causing customer frustration and wasting time. The process was taking approximately 30-60 seconds per call and in 20% of the calls, the agent wasn't able to assist the customer, leading to a transfer and repetition of the verification process. This resulted in redundancy, additional wasted time, and unhappy customers. Additionally, Nautilus was facing difficulties in identifying trends and pinpointing the root cause of issues due to the lack of actionable data. The company was also in need of a tool to monitor compliance training and adherence.

Higher Ed Growth, a company that provides lead generation services for colleges and universities, was facing several operational challenges. The company wanted to reduce its manual call recording review time, which would allow it to review more calls. It believed that by monitoring and coaching more thoroughly, it could improve its compliance rate and get more insight into overall contact center operations and individual agent performance. The company was also looking to accurately identify and score critical KPI’s and create fair and balanced client-specific automated scorecards.

AXCESS Financial, a consumer financial services firm, was a frequent target for fraudsters who tricked employees into transferring money through bogus transactions. The fraudsters were successful an average of about once a week and were costing the company more than $360,000 annually. The company knew it was getting scammed, but didn’t always know how, or even who the perpetrators were. A typical fraud investigation would start when a store associate felt a customer interaction was suspicious. The process was time consuming and often only began after AXCESS Financial had been defrauded. The process had little preventive value, and left many attempts unreported and uninvestigated. AXCESS Financial had between 35,000 and 40,000 customer contacts in a typical day and over 60,000 during peak periods, so some suspicious activity inevitably fell through the cracks.

AMCOL Systems provides complete accounts receivable management services to hospitals, healthcare systems and physicians groups in 34 states. Its scope of work exposes AMCOL to many different compliance regulations, especially for its collection activity. With enforcement of the Fair Debt Collection Practices Act (FDCPA) and other regulations becoming more aggressive, AMCOL wanted to find ways to improve what was already a highly compliant, efficient and automated operation. Many organizations in that position could introduce contact center analytics to provide the feedback for improving compliance and raising agent performance and proactivity. But AMCOL already had a contact center analytics solution in place, plus an advanced portal that makes it easy for supervisors and agents to share performance feedback and take action based on accurate, objective metrics. For AMCOL, the best opportunity to make additional, sustainable improvements was to compress the cycle of collecting performance metrics, analyzing them and providing actionable feedback to agents.

Real Time Resolutions (RTR) is a full-service mortgage servicer, debt collection, and business process outsourcer operating in the 1st and 3rd party marketplace with a portfolio consisting of mortgage and a variety of consumer accounts including those in bankruptcy. RTR employs 150 Recovery Agents (CSPs) across their U.S. branches. The company was facing challenges in reducing After Call Work (ACW) and operational costs, and improving call volumes in their contact center. They identified that the agents’ average ACW had a strong relationship to product type. For one specific product type, the average call duration was 2 minutes 30 seconds, but the average after call work was 6 minutes 30 seconds. This was not an occasional occurrence. In some months, the average for call durations was only one third of ACW. The analysis also uncovered that some agents (even those who sat next to each other) had drastically different ACW times.

Open English, a Miami-based company that provides English instruction for groups and individual students via 24/7 access to online courses led by American teachers, was facing challenges in monitoring contact center performance and addressing quality issues. As the company's services grew more popular, the call volumes increased, making the manual methods used to review calls difficult to maintain. The company uses its contact centers in the U.S., Colombia, and Brazil to attract new students by calling prospect leads generated by its website and marketing campaigns. These calls are the lifeblood of the company and are the focal point of its new student acquisition process. Therefore, in 2015, Open English set out to automate its call monitoring and review process by using speech analytics to improve its outreach efforts.

Delta Outsource Group, a nationwide provider of collection and receivable management programs, was facing challenges in proving compliance with TCPA or FDCPA regulations. The company was using manual scorecards to assess the performance of their agents, which was time-consuming and based on analyzing only a small percentage of agent calls. This left the company vulnerable to the risk of legal actions being taken against them due to the lack of ability to verify compliance with TCPA and FDCPA regulations. The company also identified several issues with collectors’ calls, including potential FDCPA violations, use of abusive language, mentions of legal action, and actions affecting profitability such as overall call duration and excessive silence on the call.

Sokolove Law, a national personal injury law firm, had a call center with 55 agents that dealt with sensitive personal information. Quality and professionalism were paramount. To ensure these standards, Sokolove employed a team of five quality assurance managers (QA) to supervise the agents. The QA team's job involved listening to call recordings to ensure interactions met Sokolove’s high standards and to identify areas for improvement. However, this manual process was time-consuming and could only cover a fraction of the calls. The firm needed a solution that could analyze more calls, ensure adherence to interaction protocols, improve productivity and outcomes, and provide objective agent evaluations on more calls.

TradeGlobal, a leading end-to-end eCommerce provider, recognized that their customer care center is often the first live interaction a customer has with their client’s brand. They wanted to ensure they were delivering best-in-class service and customer experiences. To achieve this, they needed to identify ways in which agent performance could be continuously evaluated and improved. They also wanted to identify any underlying problems with their internal processes and systems, through which operational efficiencies could be realized. They did not set out to identify process and product improvements for their clients but this was one of the unexpected benefits of the insight delivered by the CallMiner Eureka Interaction Analytics solution.

DEFENDERS, a leader in home services sales, was facing a challenge in improving sales performance as traditional quality assurance methods and simple transactional data were not providing the key insights needed for effective coaching. The company wanted to monitor more calls, identify and benchmark top agent performances, improve sales performance, raise customer satisfaction levels, improve “Voice of the Customer” insights, and increase agent quality scores. The company initially deployed CallMiner speech analytics in its sales center using a pilot program. The sample group consisted of 15 agents with various levels of experience. During the trial period, these agents received weekly reporting and feedback based on speech analytics insights, with the goal of increasing sales of a specialized product line.