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Aberdeen studied hundreds of companies to understand the impact of Artificial Intelligence on customer experience. This article deeply analyzes the findings of the study and projects the expected ROI from AI investments to enhance CX.
This article highlights how artificial intelligence (AI) Capabilities influence performance results of modern customer experience (CX) programs.
Why Are CX Leaders Investing in AI?
In 2019, Aberdeen surveyed 369 CX leaders across companies of all sizes, industries, and locations For The CX Executive’s Agenda 2019 study. The findings revealed that 53% of companies were using one or more of the AI capabilities noted in the sidebar. In early 2020, This survey was refreshed With The CX Executive’s Agenda 2020, (March 2020), which surveyed 405 businesses (of all sizes, industries ,and locations). This latter study revealed that 68% of companies use AI capabilities as of 2020 reflecting a 28% year-over-year (YoY) Increase in adoption of AI capabilities between 2019 and 2020.
Why are CX leaders increasing their adoption of AI capabilities at such a rapid pace?
Table 1 reveals that the number one factor driving AI investments for more than half of all firms using AI capabilities in both 2019 and 2020 is the desire to infuse greater intelligence within customer interactions. The CX Executive’s Agenda 2020, (March 2020) study indicated that 78% of companies are not satisfied with their ability to use data when managing customer interactions. As a result, companies are increasingly turning to capabilities such as machine learning to analyze vast volumes of data rapidly and accurately with the help of algorithms to reveal hidden Factors influencing their activities. Additionally, they rely on tools such as automation and prescriptive guidance to leverage these insights to accomplish their goals.
Why Are CX Executives Using AI?
Definition: Artificial Intelligence (AI)
For the purposes of this research, Aberdeen defines AI capabilities 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 guidance: 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. Firms may use one or more of the above capabilities at the same time to support their activities.
The second most cited reason firms invested in AI in 2019 was employee Empowerment. Employee empowerment is crucial as it’s the employees who ultimately design holistic CX strategies and execute on them. However, as firms increase their adoption and use of AI capabilities, their expectations from these technologies evolve. Instead of aspirational goals such as empowering employees, CX leaders in 2020 and beyond are more practical. For example, one driving factor for AI investments is reducing inefficiencies through identifying manual and repetitive tasks and then implementing automation capabilities to handle them.This helps free up employee time from repetitive (and often low-value) tasks, and instead allows them to focus on tasks where they can use their critical thinking and human empathy.
Given the uncertainty caused by the COVID-19 pandemic, it’s no secret that companies across all industries are aiming to control (if not cut) their costs —including labor costs. Table 1 Indicates that not only are firms aiming to make better use of employee time by reducing their involvement in manual and repetitive tasks, but they are also using automation to decrease the number of employees they need to continue operating.
It’s noteworthy to point out the minor drop in the percentage of firms citing labor cost decrease as a driver of their AI investments. While this one data point may not be enough to reflect a broader trend, it signals That business leaders are starting to have more realistic expectations from AI. Instead of assuming that AI and automation can be used to eliminate or reduce the workforce, more firms acknowledge that while some jobs will be replaced by AI and automation, not all jobs will be eliminated. In fact, AI capabilities will augment tomorrow’s workforce by improving their productivity. It’s also worth noting that as technology advances, AI capabilities will be able to handle more complex tasks. Both firms already sing AI capabilities and those planning to use AI capabilities should consider designing and implementing programs that upskill their employees. Continued training will help employees adapt to future operating needs where their critical thinking skills and empathy will be used in combination with evolving capabilities to deliver top-notch customer experiences.
Are AI Capabilities Delivering on CX Leaders’ Expectations?
In addition to the aforementioned reasons for investing in AI, firms are also driven by a desire to replicate the successes of companies that are already using AI profitably. Aberdeen asked a series of questions the YoY performance changes observed by all firms, including those that use AI and those that do not. Data shows that firms using AI capabilities outperform non-users across three key categories: customer experience, service excellence, and financial results.
AI Capabilities Rank Among the Top 10 Technologies for Planned Adoption
In June 2020, Aberdeen surveyed 307 CX and service leaders for The Intelligent Contact Center study to observe the trends and best practices influencing customer care programs in 2020 and beyond.The findings from the study revealed that AI capabilities are among the top 10 technologies firms plan to implement by the end of 2021.
AI Performance Benefits Are Pervasive
While the data presented in pages 4 to 6 will reveal the performance impact of AI on contact center success, all business departments can use AI capabilities in their activities and enjoy similar benefits from AI. In fact, CX and financial performance results are influenced not just by the contact center but also sales, marketing ,and back-office activities. Business leaders across all departments should expect similar results with their contact center counterparts.
1. How Does AI Impact CX Results?
One interesting finding from Aberdeen Study, The Intelligent Contact Center, (June2020), is that despite the uncertainty and disruption caused by theCOVID-19pandemic, contact center leaders cited improving the quality and consistency of customer experiences as their top priority. Figure 1demonstratesthat firms using AI capabilities outperform non-users in achieving this goal. Specifically, it shows that they enjoy 3.5X greater annual improvement in customer satisfaction rates (10.1% vs. 2.9%) . Additionally, AI users achieve 8X greater annual improvement(decrease) in customer effort scores (8.8% vs. 1.1%). Together, these findings validate the use of AI capabilities and allow CX leaders to use data more effectively in their activities. With better data management, they can hyper-personalize interactions across all channels and make it easier for their customers to do business with them.
  Firms Leveraging AI Capabilities Enjoy Superior CX Performance Improvements
Customers reward those businesses that deliver effortless experiences and address their unique needs. As Figure 1 shows, a user that lead the way in improving customer satisfaction results enjoy 3.3X greater annual improvement in client retention rates (10.5% vs. 3.2%). AI users outpace non-users due to their ability to use machine learning to analyze vast volumes of customer interaction data that reveal factors influencing customer churn. This allows AI users to leverage real-time, next-best-action guidance to minimize risk factors based on those insights, helping firms use data to truly understand and address buyer needs.
Customer Effort Score
While customer effort score Is increasing in popularity, not every business is currently measuring it. Firms can measure effort in various ways. The most common method is asking customers for their input (on a scale of 1 (low effort) to 5 (high effort) or 1 to 10) on how easily the company or the process addresses their needs.
Other ways of measuring customer effort include observing customer behavioral data such as repeat contacts to determine the level of effort a client needs to put in to address their needs. Firms not currently measuring customer effort can use repeat customer contact as a way to gauge their success in minimizing buyer effort. Firms using AI minimize customer effort by using machine learning to analyze vast volumes of data and determine factors negatively influencing customer effort. They also use automation capabilities to streamline process execution, there by reducing delays and customer effort related to manual and repetitive tasks.
2. How Does AI Impact Service Excellence?
Customer experiences don’t happen in a vacuum. While technology and processes help firms manage CX activities, it’s ultimately the employees who rely on these technologies and processes to help customers. As such, it’s critical to enable employees with the right tools and the information they need to do their jobs. However, findings from Aberdeen’s Study, The Intelligent Contact Center ,(June 2020), shows that on average, agents spend 14% of their time looking for information. Use of AI capabilities such as next-best-action guidance helps firms address This lack of productivity.Â
Specifically, by using speech analytics, desktop analytics ,and interaction analytics, firms can automatically determine the context of an interaction in real -time. Using this contextual knowledge, agents are automatically provided with relevant knowledge base articles through screen pop -ups on the unified agent desktop. Use of machine learning enables firms to continuously gauge the efficiency of these articles And monitor which articles are most effective in addressing client needs. This Analysis Allows companies to update knowledge base articles as they Determine the efficiency of certain articles in helping agents address client needs.
In Figure 2 we see that firms using AI capabilities to support the Above activities achieve 2.4 X greater annual improvement in agent productivity (7.4% vs. 3.1%).Boosting agent productivity allows AI users to Maximize Employee Efficiency, Helping to improve agent utilization rates by 2.2 (4.0% vs. 1.8%). Better utilization rates Allow Firms to use their existing resources more efficiently , thereby reducing unnecessary labor costs.
Firms with Remote Work Capabilities Outperform Others in Delighting Their Clientele
Besides empowering employees with timely and relevant guidance, firms using AI drive service excellence by finding ways to improve first contact resolution rates. Improving this metric is important as it reflects the percentage of customer issues Addressed In just one contact with the business. Firms that fall behind in this metric Observe Repeated Customer contact , resulting in frustrated clients and elevated churn risks. AI helps firms improve first contact resolution rates by using machine learning algorithms to build and maintain customer and agent persona profiles. These profiles reflect technology skills, channel preferences ,and personality types and are invaluable in truly optimizing customer routing activities. Firms using AI capabilities enjoy 2.3x greater annual increase in first contact resolution rates (6.3% vs.2.8%).
3. How Does AI Impact Financial Results?
One of the key attributes of Best -in -Class CX programs is that they’re not just focused on creating happy customers. They’re also focused on driving cost savings and Reinvesting those savings into innovative activities That facilitate customer delight and revenue growth. Figure 3 Proves That AI helps firms align their activities with that of The Best-in -Class. As a result, AI users enjoy 11.5x greater annual improvement (decrease) in service costs (4.6% vs. 0.4%).This is facilitated by using machine learning to continuously analyze customer and operational data to reveal sources of inefficiency such as reasons driving repeat customer contact and client churn as well as labor and operational costs. The AI-enabled analytical process Optimizes the forecasting of future customer traffic across all channels While automatically adjusting. agent staffing levels in alignment with That anticipated demand ,minimizing agent overtime costs due to poor scheduling.
AI Users Grow Revenue and Reduce Costs
Figure 3 reveals that AI users have a financial advantage over their peers while driving top-line revenue growth. They enjoy 6.5% YoY increase in annual revenue compared to the 2.9% worsening by non-users. The resulting 9.4% gap in revenue growth between users and non-users of AI is significant. For example, consider A company with $100 million in annual revenue. Data shows that using AI within CX Activities would help this firm with $9.4 million in added annual revenue(9.4% times $100 million)
AI helps facilitate revenue growth by Arming firms with insights revealing which activities are most effective in addressing customer needs. The elevated customer trust and satisfaction resulting from this truly data -driven process ultimately boosts buyer spend ,helping AI users enhance their financial results.
Key Takeaways
CX programs have come a long way over the past decade. They’ve been transformed from ad-hoc projects siloed across different business departments to a C-suite priority driving strategic activities . As CX programs matured, companies increased their focus on utilizing data to achieve goals. However, as illustrated earlier in this report, effective use of data to drive intelligent customer interactions is still a challenge and is the number one reason driving firms to invest in AI capabilities. Firms struggle with minimizing operational complexity and empowering employees with the tools and knowledge they need. As a result, the adoption of AI capabilities has increased 28% between 2019 and 2020 with growth rate anticipated to continue in 2021 and beyond. In fact, AI capabilities rank among the top 10 technologies contact center leaders plan to deploy by the end of 2021.
The rapid adoption and use of AI capabilities can also be attributed to the success observed by firms that have already incorporated AI within their activities. Specifically, this report shows that firms utilizing AI capabilities enjoy superior YoY growth in customer satisfaction rates, increase in agent productivity, reduced customer effort and service costs, and growth in annual revenue. If you’re not currently using The AI capabilities depicted in the sidebar on page 2, we suggest you consider how adding them in your CX activities can help you achieve The outcomes outlined in this report.
If you’re currently using AI, we suggest you continuously monitor your performance across The key metrics indicative of success in attaining your CX goals. This will help reveal if you’re using AI capabilities effectively Or If they need to be Fine -Tuned to truly maximize their benefits.
Aberdeen Strategy & ResearchOpens a new window , a division of Spiceworks Ziff DavisOpens a new window , with over three decades of experience in independent, credible market research, helps illuminate market realities and inform business strategies. Our fact-based, unbiased, and outcome-centric research approach provides insights on technology, customer management, and business operations, to inspire critical thinking and ignite data-driven business actions.