Creating effective and insightful summaries of customer interactions is essential for understanding the reasons behind your customer inquiries, the dynamics at play during conversations, and enhancing overall contact center performance. But it’s not easy to do, especially at scale. Here are the top 8 factors impeding contact centers from getting quality, actionable customer information from interactions that move the needle on improving customer experience:
Manual Processes: Agents are burdened with manually creating summaries, or agent notes, during or after calls, diverting their attention from assisting customers and resulting in inconsistent and incomplete summaries with no useful data for acquiring insights.
Time Pressure: Agents face pressure to meet aggressive Average Handle Time (AHT) goals, leading to rushed summaries of low quality or skipped summarization altogether.
Over-reliance on Surveys: Relying solely on surveys for data collection can be problematic due to low response rates and biased feedback from only the most opinionated customers.
Disruptive to Conversations: Summarization during calls can disrupt the natural flow of conversation, leading to increased friction and potentially lower Customer Satisfaction (CSAT) scores.
Agent Frustration: Manual, rushed, and frictional summarization processes contribute to agent frustration and burnout, exacerbating already high attrition rates in the industry.
Inconsistent Quality: The rush to complete summaries results in inconsistent quality and unreliable data, hindering decision-making and organizational performance.
Under-Reporting: Manual or hurried summarization may lead to under-reporting of critical information, impacting key performance indicators and organizational awareness.
Multi-Channel Communications: Managing summaries across multiple communication channels adds complexity, making it challenging to aggregate data and provide seamless customer experiences
What does this friction look like?
According to our research, an average call center may be staring down the barrel at these bleak stats regarding summaries:
120-300 seconds spent dispositioning per call.
Less than 25% of notes that are actually of a usable quality.
No data to aggregate for key business insights.
Overcoming these challenges requires effort, but fortunately, generative AI offers a promising solution to alleviate much of the friction. Implementing a modern AI summarization solution is essential to overcoming these obstacles and unlocking the true value of contemporary CX summaries.
Don’t miss out on summarization value
Without good summaries, your business could miss out on valuable insights and advantages. The absence of crucial historical context hampers agents' ability to assist customers effectively, reducing the personalized touch that builds loyalty. Moreover, lacking necessary compliance data can put your organization at risk of regulatory violations.
Without comprehensive summaries, you lose access to valuable customer and business data vital for strategic decision-making and growth. And the lack of a true reflection of agent performance hinders identifying areas for improvement. Most importantly, without insights into customer satisfaction drivers (or detractors), you're unable to implement targeted improvements, limiting overall service quality and customer experience enhancements.
What’s next? Learn how to get good summaries at scale without adding to your agents’ workflows.
Download the AutoSummary eBook, our exhaustive guide to revolutionizing CX with generative summaries. This eBook will cover the best practices and technologies that will deliver the value that good summaries promise without undue agent distraction. Readers will learn:
What good summaries look like and contain.
Best practices for summarization - regardless of your methods.
How new technologies, like generative AI, can both eliminate the need for manual entry and enrich summaries with all necessary vital details.
What to look for when evaluating summarization technologies.
How to ensure you are collecting valuable business insights from your summarization efforts.
Good summaries are essential to a well-run CX organization. They provide a snapshot of customer interactions, distilling essential customer information into concise summaries that give agents quick customer context and contact centers rich analytics data. However, not all summaries are created equal. Below, we’ll explore what summaries are, what makes a good summary, and why they are invaluable for modern CX organizations.
What Are Summaries?
In the context of CX, summaries are condensed representations of longer customer interactions that capture the essence of customer-agent conversations, distilling critical information for reference and analysis. They can be created manually or automatically, and they serve various purposes within a contact center.
Good Summaries Create Value
Not all summaries are created equal. Some are created by agents manually. Some are automated. And the quality of automation can vary drastically. When done right, with precise and context-rich information, good summaries at scale can yield surprising value. Quality summarizations delight customers, empower agents, and give you a clearer picture of what is really driving the successes and areas for improvement in your organization. Here’s how it works:
1. Delight Customers
Customers want to feel recognized and understood quickly. Good summaries ensure that agents can greet customers with appropriate and relevant context and customer information, along with recognition of their past interactions and issues with the brand. This leads to more efficient and personalized customer service, reducing frustration and elevating customer satisfaction.
2. Boost Agent Happiness and Effectiveness
For agents, good summaries provide agents with essential customer background information, allowing them to address issues more effectively. Armed with context, agents can tailor their approach to get to customers’ core problems faster. When summaries are automated, they reduce the time agents spend on manual summarization, leading to a reduction in overall Average Handle Time (AHT). That means more time helping customers and less time doing after-call work. This makes agents happier while solving customer problems more quickly.
3. Generating Valuable Business Data
Summaries serve as a goldmine of data for CX organizations. They help track interactions, identify problem categories, evaluate sales efforts, assess agent strengths and weaknesses, analyze customer sentiment, and monitor high-level initiatives. This summary data is crucial for making informed decisions and holds value for various facets of the business. For example, when a specific problem consistently arises within a product, it can be communicated to the product team to ensure they are aware of and can consider addressing it. It’s a great starting point for automating and improving more of your contact center activities.
Obstacles to Creating Good Summaries
Despite the myriad advantages offered by good summaries, many CX organizations have to overcome various obstacles to get there. Here are some examples:
Manual Entry Takes Time: Many agents are still required to create manual summarizations, which distracts them from their core responsibility of assisting customers. The result is inconsistent quality and incomplete, often unusable data.
Rushed Summaries: Agents frequently contend with aggressive AHT goals, leading them to hurriedly complete summarization tasks or even skip them altogether to meet performance targets. This rush compromises summary quality and accuracy.
Agent Frustration: Agents already dealing with challenging situations find summaries to be an additional burden, extending the time required for each interaction, while trying to adhere to shorter call times. This frustration can contribute to already high agent attrition rates.
Inconsistent Quality: When hundreds of agents create summaries from scratch, the quality can vary widely, leading to unreliable data and unusable summaries.
Under-Reporting: Relying on agents to accurately represent both positive and negative aspects of interactions can cause critical key performance indicators to go unnoticed.
Where to Start?
To improve your summarization efforts, consider these high-level best practices:
Tailor the questions you ask in summaries to what is important for your business.
Optimize for humans by making questions clear and easy to answer.
Designate a resource to monitor and extract key insights from summaries.
Implement a Generative AI solution to automate and enhance your summarization process.
While implementing some best practices can improve summaries, a modern summarization solution can provide accurate, exhaustive, and data-rich summaries at scale. It’s the key to fully realizing summarization value. Here are some high-level points to consider:
Structured Data and Enrichment: Seek configurable structured data capabilities and ensure availability from the start. Additionally, explore data enrichment options for insights valuable to technical leaders in areas like compliance, service optimization, and new product introductions.
Handling Multiple Contact Reasons: Verify that your summarization solution effectively supports multiple contact reasons, enabling precise tracking of individual issues within interactions or over a customer's lifetime.
Generative AI vs Extractive AI: Extractive AI is commonly used but may lack data consistency and flexibility. In contrast, Generative AI offers flexibility, high-quality summaries, and structured data generation.
CCaaS, Point Solutions, and Key Selection Factors: Be aware that large CCaaS (Contact Center as a Service) vendors may impose limitations on flexibility. Smaller AI point solution vendors might not meet enterprise requirements. And small CCaaS vendors can be costlier and less interoperable. It's crucial to select a partner in line with your strategic objectives and possessing strong AI expertise. Building a DIY solution presents challenges and extended development timelines.
Want more? Read our exhaustive eBook.
Curious to dive deeper into summarizations? Download our summary-focused eBook “The Modern CX Guide to Summaries,” the ultimate guide to revolutionizing CX with generative summaries. Dive in to explore best practices, technologies, and solutions that promise to deliver comprehensive summaries effortlessly. Improve agent efficiency, gain valuable business data without sacrificing agent focus, and harness the full potential of your customer interactions.
Good summaries are the backbone of a well-functioning CX organization. They provide essential context, improve agent efficiency, and offer valuable business insights. However, achieving high-quality summaries at scale can be a challenge. With the advent of modern Generative AI summarization solutions like ASAPP AutoSummary, CX organizations can break the tradeoff between cost and quality, ensuring accurate, data-rich summaries that drive customer satisfaction and business success. Don't miss out on the opportunity to transform your CX organization with the power of great summaries.
ASAPP is the AI-native software for contact centers, and ASAPP exists to end bad customer service. We help customer service leaders unlock their full value by minimizing costs & inefficiencies, improving agent compliance & productivity, and surfacing actionable insights while helping you deliver a great customer experience. Our customers are large enterprises who care deeply about leveraging AI to transform CX by delivering unprecedented cost savings and maximizing customer delight.
Want to learn more about ASAPP and how they can help your team? Request a Demo
In 2024, generative AI is poised to redefine how businesses engage with their customers and streamline operational efficiency. We expect AI to not only automatically flag particular problems, but also to promptly resolve those specific customer issues. At the core of contact center transformation, generative AI is reshaping the nature of customer interactions, data-driven insights, and how agents are helping customers resolve their issues.
Although we’ve seen AI create incremental changes in service, we’ve arrived at a pivotal moment where commonplace technologies like transcription and free text summaries are evolving into profound generative insights. A large share of agent tasks can now be managed through automation, and for those tasks requiring human intervention, AI stands ready to support and assist agents in their work. Fueled by capabilities now unlocked by generative AI, enterprises can improve contact center efficiency and reduce both direct and indirect costs through nuanced understandings that enrich data and unlock unparalleled value.
To implement AI into their CX stack in 2024, enterprises must establish foundational building blocks, such as high-quality transcription, and get their data house in order before they can really take advantage of the benefits of AI.
– Michael Lawder, Chief Growth Officer, ASAPP, Former CX Leader at Apple, Samsung, and EA
Lawder underscores the importance of laying strong foundations for AI integration. Building these blocks, including high-quality transcription and organized data, is pivotal to reaping the full benefits of AI in contact centers.
Anticipate these impactful trends shaping CX in 2024:
Evolution of Text Summaries: From Extraction to Generation
Unveiling Valuable Sentimental Customer Data
Surge of Generative AI in Bots
Blending Technology and the Human Touch
Ending Bad CX: Reconciling Cost vs Quality
Evolution of Text Summaries: From Extraction to Generation
For years, the promise of automating summaries using AI to reduce Average Handling Time (AHT) seemed within reach. But the early AI models, mostly adept at extractive summarization, only provided contextual information from past interactions. While they lightened the post-call workload for agents, these summaries merely offered light context, necessitating manual review for additional insights and a clearer view of the full picture.
So, why will 2024 be the year of AI-driven text summaries? Because the benefit shifts dramatically with the summaries created by generative AI. Unlike extractive methods, generative summarization not only includes pertinent conversation elements but also gauges customer sentiment.
If your CX stack is integrated, then generative AI summaries can be customized based on factors like intent or agent groups. This means automatic categorization of complaint types and severity, identification of key issues, or post-launch focus on new product mentions becomes possible. ASAPP’s AutoSummary stands as a testament to this evolution, showcasing the transformative potential of generative AI in turning data into actionable customer insights.
Generative AI will continue to deliver incremental innovation across GPUs, LLMs, and Compute frameworks. Data will dominate to be the biggest differentiator, applying LLMs in a hybrid domain focus to achieve accuracy, time to value and scale. These vectors coming together will be the key to unlock exponential value for enterprises.
Priya sheds light on the pivotal fusion of technology and data. This convergence across computational frameworks not only drives incremental innovation but also highlights the indispensable role of data in achieving accuracy and scalability. It's the synergy between Tech, Data and seamless orchestration connecting enterprise systems for business outcomes that unlocks exponential value for enterprises.
Unveiling Valuable Sentimental Customer Data
Training generative AI on a particular business’s customer conversations can identify unique pain points, understand satisfaction drivers, and strategically enhance the overall customer experience. At the forefront of this transformation is Sentimental Data. This data segment delves into human emotions, pinpointing areas of improvement that customers feel, providing a roadmap to elevate customer experiences to unprecedented levels. Let’s look at a few industry examples.
Using sentiment analysis in the travel industry can uncover customers’ emotions tied to hotel stays, flights, and destinations, guiding improvements. Apparel industry brands can understand customer reactions to their offerings. By decoding feedback from various channels, these companies identify trends and specific customer preferences, enabling targeted product improvements and personalized marketing strategies.
In 2024, more businesses will invest in leveraging AI and advanced analytics in order to create tailor-made offerings at dynamic price points and individualized levels of service.
Sentiment data is also playing a pivotal role in telecommunications CX. Companies gain crucial insights into what delights or frustrates users by dissecting customer sentiments linked to service interactions, network experiences, and support encounters. Ultimately, this information empowers telecommunication providers to address pain points promptly, improve service quality, and tailor offerings to meet specific customer needs.
Surge of Generative AI in Bots
Next year, we’re anticipating a significant rise in the utilization of generative AI in bots, with unprecedented low barriers to accessing this technology. The immediate potential lies in elevating bots to conversational entities and eliminating hurdles in understanding user intent, which allows seamless navigation through customer inquiries.
Looking ahead, the evolution of generative AI involves integration with APIs for tailored responses derived from individual customer data. This could extend to bots understanding unique customer situations, departing from standard responses to offer personalized interactions. Ideally, generative AI bots not only achieve this but also autonomously act on behalf of customers, either independently or after human agent confirmation.
This surge in generative bots represents a transformative shift in customer interactions. Its impact varies based on implementation nuances. Some applications optimize workflows and virtual assistant functionalities, adapting dynamically to interactions and policy changes, substantially reducing manual effort.
But a more advanced, integrated generative bot transcends these efficiencies. It seamlessly handles multifaceted queries, customizing responses by fusing knowledge base insights with specific customer data. It could comprehend customer queries holistically, autonomously accessing APIs, gathering required information, and executing tasks on the customer's behalf, reshaping the customer service landscape.
Blending Tech Investment to Amplify the Human Touch
The transformative integration of generative AI and people in contact centers isn't a distant vision—it's an unfolding reality informing the way businesses empower real human agents. It isn't about replacing human interaction but amplifying the human touch with technology. Generative bots act as indispensable sidekicks to agents, offering nuanced, real-time information, enabling agents to focus on complex calls and foster meaningful connections.
By embracing generative AI, leading contact centers will transcend transactional interactions and foster relationships that are built on understanding, empathy, and personalized attention. It's this blend of technology and human interaction that paves the way for more high quality customer experiences.
In Forrester’s 2024 Planning Guide for CX, 71% of leaders are prioritizing increased budgets to drive deeper customer insights, while 48% are earmarking resources specifically for contact center technologies. This heightened investment shows a serious commitment to leveraging tech advancements to enhance customer experiences. Moreover, a substantial portion of this budget increase is directed at data and research, highlighting the pivotal role of unlocking hidden CX data in the year to come.
Ending Bad CX: Reconciling Cost vs Quality
The struggle to articulate needs and provide seamless experiences often defines poor CX. Miscommunication and missed connections hinder the very relationships businesses aim to build. We all have our bad customer experience stories. Yet, the challenge persists: how to achieve high-quality service while managing costs. It’s been a core CX issue from day one.
Traditionally, this balance led to compromises, where either quality suffered or expenses soared. Now, the emergence of generative AI introduces a new trajectory, bridging the gap between cost-effectiveness and exceptional quality in CX, ensuring each interaction embodies the ethos of service at the heart of every contact center. As it shapes our approach, we move toward a CX era where the convergence of cost and quality through generative AI finally ends bad customer service.
ASAPP is a research-based artificial intelligence cloud provider committed to solving how enterprises and their customers engage. Inspired by large, complex, and data-rich problems, ASAPP creates state-of-the-art AI technology that covers all facets of the contact center. Leading businesses rely on ASAPP's AI Cloud applications and services to multiply Agent productivity, operationalize real-time intelligence, and delight every customer. To learn more about ASAPP innovations, visit www.asapp.com.
ASAPP has significantly improved our efficiency in a very short time. Not only are we moving interactions from phone to digital, we’re doing it in a way that both our customers and our crew members love.