Contact center customer experience (CX) leaders say adapting to client needs is the No. 1 goal driving their digital transformation activities, according to a recent report by Aberdeen. Meeting these needs enables customer centricity, creating a positive experience for the customer and ultimately a long-lasting, loyal relationship. But many organizations fall short of their digital transformation objectives, and the main reason, according to the report, “AI in CX,” is insufficient data.
While companies collect a plethora of data from their customers from the various digital channels, including chat, email, phone and text messaging, the vast majority of contact centers—78% of them, according to Aberdeen’s CX Executive Agenda 2021 survey—say being able to use collected data to improve employee productivity and make better business decisions in call centers and CX activities is a challenge.
Top Reasons Firms Struggle to Use Collected Data
While nearly one-fourth of the contact center and CX leaders Aberdeen surveyed said they rely on data and analytics, not gut feel, to make strategic decisions, a variety of things are getting in the way of their ability to use the data they collect effectively.
- 34% think data is insufficient.
- 33% believe the data quality doesn’t fit its intended purpose and execution.
- 32% think there is a lack of skilled human resources needed to manage data.
- 28% lack technologies needed to manage the data.
- 27% believe conflicting data sources and systems make it difficult to create a unified view of customer data.
“Not all the data companies have in their systems is relevant for every interaction,” according to the Aberdeen report. “Furthermore, the data firms may have in their systems may be outdated and not reflective of current customer behavior and needs.”
AI Is Changing How Contact Centers Use Data
In some cases, a lack of employees with technical skills impedes contact centers’ use of data. Contact centers need to not only get employees up-to-speed on new technology but also equip them with tools able to extract insights and analytics more quickly. Increasingly, those tools are powered by artificial intelligence (AI).
Aberdeen defines the range of AI capabilities in the contact center as follows:
- Artificial intelligence: Automated reasoning and decision-making capabilities based on insights uncovered through machine learning algorithms.
- Machine learning: Technology applications that learn by themselves by analyzing a pattern of historical and recent data.
- Prescriptive intelligence: Tools used to analyze structured and unstructured historical data to make predictions and suggest decision options.
- Predictive analytics: Tools to predict future behavior of customers.
- Automation: Tools used to automate the execution of tasks such as customer routing, agent scheduling, and quality assurance.
How AI Helps Achieve CX Goals
These AI tools can be used to see how specific activities can help address customer issues, and this helps organizations create tailored customer journeys. Predictive analysis tools can show the activities of current customers who share similar characteristics and help the contact center better anticipate how to address their needs. In fact, contact centers that use AI capabilities experience superior CX performance improvements, according to the Aberdeen report, including:
- 3x greater year-over-year increase in customer retention rates (10.5% vs. 3.2% among contact center users not using AI).
- 5x greater year-over-year increase in customer satisfaction rates (10.1% vs. 2.9%).
- 8x greater year-over-year increase in improvement in customer effort score (8.8% vs. 1.1%).
AI capabilities can help contact centers translate collected data, observe agent behaviors faster and quickly learn whether interactions have a negative or positive impact on overall CX, leading to a better competitive advantage in their digital transformation. Learn more about how contact centers are leveraging AI to make better use of data in the Aberdeen report or find out how NICE Enlighten AI is making the contact center smarter by enabling a complete, objective and automated analysis of every interaction.
