Case Study
How A Leading Global Business Process Outsourcing Firm Leveraged Call Journey CI To Deliver Unique And Substantial Benefits to Their Customers
Background
The Challenge
Market Challenge
According to a 2024 McKinsey global study, companies are also looking outside their organizations for innovative ways to fill capability gaps. Outsourcing, once viewed primarily as a way to reduce costs, is increasingly seen as an effective source of additional skilled capacity and innovation capabilities. Fifty-five percent of the companies in our survey currently outsource part of their customer care operations, and 47 percent of those organizations expect to increase their outsourcing over the next two years.
Outsourcing relationships are becoming deeper too, with respondents telling us that they are now using their business process outsourcing for a range of activities that extends far beyond traditional call and email handling. They include content management and digital-marketing services, payments handling, and the development of AI-based customer care tools. Following the blueprint established by major players in the industrial products, medical device, software, and e-commerce sectors, some companies are now working with outsourcing partners to set up global innovation hubs that will drive the development of next-generation customer care technologies.
BPO Specific Challenge
To be honest, we were really struggling to find accurate data and insights to remediate our client's challenges. By accurate data, I mean qualitative and quantitative data, to quite detailed dissection levels. We were facing the real risk of losing 6,000 seats to our competitors.
The Chief Commercial Officer and Head of Client Services was frustrated that the key initiatives that they were driving lacked effective intelligence, hampering the success of those initiatives.
Although we had been getting some level of dissatisfaction from our FS customer in our QBRs, we were blindsided by the performance feedback, particularly when we didn't have the data, statistics or intelligence to validate their feedback.
There were a number of challenges presented by the FS customer to the BPO, which included:
- Customer Dissatisfaction – The FS client measured and assessed customer satisfaction through survey tools, revenue attrition measures, AHT overruns, interaction volumes, and FCR metrics. The inference was that the BPO experienced incompetency whilst contributing to the negative customer dissatisfaction category.
- CSAT/NPS – The FS client was aiming for a CSAT score of 80% or above and an NPS of 45 and above. They were tracking at 61% and 28 respectively.
- Complaints – Defined as where customers contacted a complaints area (voice and digital). Complaints were up 27% year on year.
- AHT/FCR – In some queues, AHT was almost 40% over guidelines and in others, FCR was in the high 50% – low 60% range.
expansion of value
Call Journey CI was already supporting the global BPO with agent-focused conversation intelligence with a predominant focus on agent performance, agent coaching, and team leader intelligence. As part of our regular partner update with our BPO customer, Call Journey outlined its expanded intelligence capability from BPO interactions with their customers. Once the BPO became aware of the new modules of capability, they moved quickly for an expanded overview with the broader BPO leadership team.
Post the overview, it was quite clear to the BPO leadership that Call Journey’s new platform could deliver unique and accurate data points and intelligence that would help validate their FS customers’ challenges. The components and functionality of the platform that the BPO saw as both significantly unique and having potential to deliver significant upside for their FS customer were as follows:
Vendor Comparison
Call Journey Ci unlike all other vendors utilized far more details relevant and context-aware data mining techniques to surface things like the root cause of customer contact, the root cause of dissatisfaction, and the cause of high AHT and low FCR. All other vendors fundamentally were utilizing basic word-spotting and topic analysis which statistically showed to be surfacing inaccurate and misleading data and insights.
Before we were aware of Call Journey's new platform, we had already begun looking at vendors to help with one of our core challenges, being able to REALLY understand what drove them to contact our client (whose interactions we were already managing). When we were able to compare Call Journey's output to other vendors results, the comparison was so far in Call Journey's favor - it was staggering!
We were hugely impressed with the outputs of Call Journey CI Uncover platform as we didn't need to lean into our own internal data or business analytics capabilities. As a BPO data leader, I have both limited capacity and specialized competency in my team to even access this sort of data, let along wrangle it! The platform did the majority of the work for us, utilizing advanced data storytelling approaches and new and unique data.
Once we had time to be exposed to and understand Call Journey CI Uncover platform, it became abundantly obvious to us that we had just discovered a new, unique and valuable intelligence asset for both ourselves and most importantly our clients.
The Methodology
How the BPO Used Call Journey Ci
The BPO decided to explore conversation intelligence as a means of extracting valuable, actionable insights from customer interactions. Leveraging advanced natural language processing technologies, advanced machine learning, and data science principals and models with Call Journey CI, the BPO benefits from a hands-off diagnostic assessment of their client’s CX problems.
Key elements/modules of the platform utilized:
- PII/PCI Redaction: Implementation of cloud-based PCI and PII redaction, ensuring that customers’ identities are protected throughout the analysis process.
- Dissatisfaction Analysis: Data science and AI/ML-driven analysis of what was truly driving dissatisfaction. Layers 4 and 5 of interaction assessments applied including the use of GenAi as a component of the solution to understand, categorize, and report on dissatisfaction. Elements include context and relativity and are achieved through qualitative and quantitative assessment.
- Root Cause Analysis – Contact Drivers: Data science and AI/ML-driven analysis of what was truly driving customers to make contact. Layers 4 and 5 of interaction assessments applied including the use of GenAi as a component of the solution to understand, categorize, and report on the key reason/s for customer contact. This is not a basic level of topic analysis common in the market to levels 1 and 2 at best – this is a comprehensive, levels 4 and 5 data-driven, precise assessment using sophisticated data science algorithms and models.
- Root Cause Analysis – Repeat Contact: Data science and AI/ML-driven analysis to a) pinpoint when a customer has made repeat contact and b) diagnose why that customer had to make repeat contact. This helps not only quantify but also qualify the factors impacting FCR.
The Results
The Results
The conversation analysis examined 2,000 agents’ interactions over a 2 week period and yielded a total of well over 100 distinct opportunities for business improvement by addressing preventable elements within the business and the contact center’s productivity to save costs. The potential savings/business benefit associated with these opportunities was estimated at $23 million in potential savings.
Outcome: A New Revenue Stream Uncovered
- Armed with the transformative insights of Call Journey Ci, the BPO was able to develop a value-adding program to deliver incredible results to their clients, including this flagship client. Their model included either per-seat or one-off engagements.
- Their flagship client was the first of many to expand their BPO arrangement to include insights-as-a-Service, increasing their processing volume with the BPO by 200%. This included their top customers and key near-term renewals.
- The BPO realized an 18% increase in per-seat revenue through the additional ‘Insights-as-a-Service’ capability.
With a constant challenge to find unique and innovative ways for us to stand out from our competitors, being able to accurately, definitively, and quantitatively provide high impact intelligence to our clients became a very compelling proposition for us. Not only would we be able to explicitly understand where the root cause of challenges sat between our own internal operation and that of our clients, but we would be able to provide our clients invaluable intelligence which they most likely don't even have themselves.
