The customer experience (CX) landscape is evolving, changing how businesses connect with consumers and redefining expectations at every touchpoint. The rise of AI, the abundance of data across channels, and the increasing expectation that organisations offer personalised omnichannel experiences are among the factors making the industry ripe for disruption. In fact, traditional CX workflows fail to solicit feedback in a personalised, timely manner – instead offering a reactive approach to feedback, such as asking for generic feedback after an in-person shopping experience.
Today’s modern organisations must get more out of their CX investments, including how to get quality feedback in a digital-first world using timely and personalised engagement methods. If the engagement method isn’t timely and personalised, organisations risk disjointed responses, which ultimately impacts CX.
The future of data collection for CX professionals
According to CMS Wire, “smart customer strategies are the secret sauce for businesses looking to win customer trust and deliver real-time experiences.” CMS Wire states that AI and machine learning are transforming customer data collection in the areas of predictive analytics, customer segmentation and real-time personalisation.
Findings from CallMiner’s 2024 CX Landscape Report shows that CX leaders recognise the value in diverse data collection. Our research reveals organisations are increasingly less reliant on solicited feedback alone, suggesting they understand the value of using a variety of data sources to understand the voice of the customer. We found that organisations are using, on average, a greater number of different sources/types of data and are using these more extensively, with 25% of organisations collecting an equal amount of solicited and unsolicited customer feedback (compared to 20% in 2023).
While CX professionals are using a greater number of data sources to make decisions, many have not adopted AI to assist with data analysis. Less than two thirds (60%) of CX professionals are using automated processes to analyse their CX data. Tools that enable the analysis of CX data at scale are crucial for empowering organisations to act quickly and remain competitive.
Combining surveys with conversation intelligence
Surveys, a core capability of CX programs, have the potential to identify pain points, measure the impact of initiatives, and track trends over time. However, they remain imperfect. While traditional survey capabilities are aimed at soliciting and collecting direct customer feedback – helping support data-driven decisions and personalised interactions – they are often sent to customers without a true understanding of any given interaction, meaning they are general and ask questions that lack important context of the true experience.
Organisations can gain greater insight into CX by leveraging conversation intelligence data alongside solicited feedback. With this information, CX leaders can improve survey design and create more personalised experiences. For example, CX leaders can send surveys referencing specific customer challenges, such as an isolated payment issue, instead of a generic survey.
Real life Success Stories
We have seen that many organisations can use conversation intelligence to inform their CX strategy.
- Foundever improved NPS by 5% and sentiment scores by nearly 10% for a large U.S. telecom company.
- Kelsey Seybold Clinic improved the patient experience by using conversation intelligence to identify agent coaching issues from process issues.
- Workhuman improved overall customer satisfaction by 0.4%, despite the increase in contact volume and drivers.
Learn more on how AI driven insights can enhance CX and business outcomes in the annual CX Landscape Report