Voice of Customer (VoC) platform is a core technological process specifying the wants and expectations of the customer base and congregating data using tools like Internal and External Data (existing company information, competitors benchmark etc.), Listening Post (complaints, sales and accounts payable Information etc.) and Research Methods (interviews, surveys, focus groups etc.)
VoC platform can be explained in four simple steps:
- Assemble (structured and unstructured feedback)
- Measure (time, value, errors, availability, completeness etc.)
- Target (daily or weekly product updates or based on specific customer requirement)
- Monitor (customer satisfaction, Net Promoter Score [NPS], customer effort etc.)
Adoption of VoC platform is crucial, and it showcases measurable terms about customer wants so that organizations do not end up taking wrong decisions. The primary purpose of VoC is to identify the critical requirements and measure the success of work which organizations are delivering to their customer. The customer, in this context, is the receiver of the output which the company delivers.
However, covering VoC is only the first step. To be useful, it must be translated into something that can measure the performance of the process. This can be done by taking VoC inputs, converting them into the measure and then identifying them into a specific target.
Software embedded with VoC capabilities delivers enterprise visibility of market awareness, employee training, customer trends and product insights by accumulating and disseminating automated individualized outcomes. Vendors offer out-of-the box data collection and integration capability with support to ingest a variety of Customer Experience (CX) data from third-party applications and data sources. Moreover, data ingestion features embody interactive self-service User Interface (UI) to configure ingestion, configure encryption, map data, and script data transformation along with passive batch and real-time ingestion. They also support standard formats for file import such as delimited Text, triple-S, XML, and Excel. The platform trigger alerts via a range of multiple channels including email, SMS or app notification based on predefined rules. Stakeholders or predefined individuals receive notifications/alerts in the entire span of survey process or in subsequent data processing.
Voice of Customer (VoC) platforms comprehend case management – a multi-source platform for customer problems, providing tools to immediately track, assign, respond and resolve for an effective service recovery process. The platform enables users to add comments within cases, review records of action taken by others, share cases within the organization, request reassignment of cases, approve/reject reassignments, and forward cases to other users in order to drive further action or provide visibility. Additionally, they also allow the export of case reports that show how cases are trending over time, tag cases for future analysis of root cause, corrective actions, response method, and compensation offered.
The platform can provide voice analysis for categories including laughter, anger, engagement and over talk (if there are two channels of speech). Technology developers are leveraging machine learning and AI capabilities to incorporate text analytics into their VoC platform. The sentiment engine uses deep learning with a combination of NLU and NLP to find the overall sentiment in verbatim as well as the sentiment by category. The platforms offer an intuitive reporting and dashboard that can be easily configured and customized (allowing users to drill down or delve into details of data). It supports role-based reporting for any organizational hierarchy structures.
To conclude, vendors should stress majorly on the adoption of speech, image, video and text analytics, enabling CX professionals to gain meaningful insights into customer viewpoint about company, products and services. Vendors should continue enhancing tonal/voice emotion analytics through native or partner system in addition to real-time voice analytics performed on voice responses to a survey using partner technology.