Medallia vs Qualtrics vs Level AI for Improving Customer Experience
Qualtrics, Medallia, and Level AI all focus on improving the customer experience. While Qualtrics and Medallia are primarily known for their survey tools, Level AI specializes in helping contact centers boost efficiency while enhancing the customer experience.
In this guide, we compare Level AI, Qualtrics, and Medallia in the following categories:
Before we jump in, we’re going to provide a brief overview of each platform.
Platform Overview & Pricing Information
Level AI: In-Depth Analysis of Customer Interactions & Real-Time Support for Improved Customer Experience
Level AI is an AI-driven customer experience and automation platform designed for contact centers. By leveraging AI speech analytics, it enables QA teams, managers and agents to accomplish more in less time, enhancing the customer experience.
Rather than relying on surveys to gauge customer satisfaction, Level AI analyzes customer calls in real time, capturing both customer intent (the goal they want to achieve) and customer sentiment (the emotions expressed during the call) to assess experience quality.
Level AI is used by customers in healthcare, financial services, insurance, retail, and more. Our customers report results like a 13% decrease in call handling time and a 75% decrease in after-call work for agents.
You can book a demo to learn more about Level AI’s features and pricing.
Qualtrics: Data Analysis Across Multiple Touchpoints, Channels & Locations
Qualtrics is ideal for large enterprises focused on understanding the entire customer lifecycle. It offers features for optimizing digital experiences, in addition to customer experience optimization.
It’s also well-suited for companies with multiple locations, as its reporting capabilities track CX optimization, employee experience management, and customer satisfaction trends across locations.
Qualtrics pricing is based on purchasing a full suite of products, with specific details available upon request.
Medallia: Proactive Intervention & Follow-Up Automation for Higher Customer Satisfaction
Medallia makes it easy to track customer interactions across multiple channels before, during, and after they engage with customer support. The platform is well-suited for teams managing large numbers of frontline employees in travel, hospitality, or retail, and those needing to automate various customer support tasks.
Medallia identifies customer responses to brand interactions and offers suggestions for improving those interactions, such as setting up automated workflows to prevent churn for customers with negative experiences.
Their website mentions a pricing model based on Experience Data Records, but specific pricing details are not provided.
Next, we’ll cover customer feedback collection capabilities in Level AI, Qualtrics, and Medallia.
Gathering Customer Feedback
Level AI: 100% Call Coverage & Advanced AI-Powered Analysis
Level AI automatically captures 100% of calls, leveraging speech recognition, natural language understanding (NLU), and semantic intelligence to analyze customer interactions.
It understands both customer intent and the emotions they experience during the interaction. Additionally, Level AI can integrate data from other channels, like chat and email, for cross-channel text analytics.
The benefit of incorporating these data sources is that customer support teams aren’t reliant on survey data to assess customer satisfaction.
Since not all customers complete surveys, survey responses only offer a partial view of how customers feel about their interactions with the brand. Because surveys provide incomplete information, opportunities to improve customer satisfaction and retention can be missed.
This is particularly important for customers whose experiences are neither very positive nor negative. Level AI helps uncover previously unidentified ways to improve CX through call analysis — more on that in the section below on reporting capabilities.
But first, let’s explore how conversational intelligence helps teams gain a complete understanding of customer goals and experiences.
To analyze customer conversations, Level AI uses its Scenario Engine and sentiment analysis.
The Scenario Engine captures and categorizes customer intent. In other words, it understands customer goals — for example, returning a product or getting help with completing a transaction — and labels them as specific scenarios within the platform.
It also recognizes phrases that indicate a specific scenario and applies conversation tags, making it easy to see customer intentions without reading through the entire conversation. This tagging system allows for grouping multiple conversations by intent for further analysis.
Level AI provides a variety of out-of-the-box scenarios, but you can also add custom scenarios by training the AI with example phrases that your customers are likely to use.
Level AI uses sentiment analysis to capture and analyse the emotions expressed by customers during the call.
Our platform recognizes a wide range of emotions, including gratitude, happiness, admiration, worry, disapproval, disappointment, and anger — more than any other product in our category.
When Level AI detects a sentiment during a call, it creates a timestamp for that instance and marks it with a sentiment tag. This helps provide a quick overview of the call and an easy way to filter conversations.
Compared to surveys, sentiment analysis uncovers emotions that you might not otherwise be aware of. For example, a customer may feel frustrated during a call but forget to mention it in a survey after the issue is resolved to their satisfaction.
Level AI also evaluates the overall sentiment of the call with a Sentiment Score ranging from 0 to 10, where 10 represents the highest positive sentiment and 0 indicates the most negative emotions.
For improved accuracy, the Sentiment Score assigns different weightings to expressed feelings based on when they are expressed during the call.
This provides a more accurate picture of call resolution, giving more weight to emotions expressed at the end of the call, as they are more likely to be remembered by the customer and better reflect their overall satisfaction with the experience.
Qualtrics: Cross-Channel Customer Surveys for Customer Feedback
Qualtrics offers a variety of cross-channel surveys that include both structured and unstructured question types. These surveys can be presented at specific moments in-app or on the website, as well as sent out after customer interactions.
Qualtrics surveys can be trained to ask follow-up questions for additional feedback and uncover deeper insights, like customer motivations.
Qualtrics can also pull in external data sources for more detailed analysis (more on that in the Additional Features section below). Additionally, it offers online reputation monitoring and management of social media and review sites.
Medallia: Smart Sampling Support and Multiple Data Source Analysis
Medallia offers various feedback management and collection options, including customizable in-app surveys that help companies with digital products gather insights efficiently.
It collects and analyzes direct and indirect feedback, including:
- Surveys
- Speech
- Digital behavior
- Social and 3rd party reviews
- Video
- SMS, messaging, and chat data
- Benchmarking data
- IoT
- POS
- Operational data
In addition to data analysis, it ensures unbiased results through smart sampling, which manages quotas by segment and applies automatic weighting to reduce customer service workload.
Below, we’ll cover how these platforms display customer feedback data to help teams improve the customer experience.
Reporting Capabilities
Level AI: Custom Reporting Capabilities & Subtle Trend Detection for a Better Customer Experience
As mentioned earlier, Level AI captures 100% of customer calls and can integrate with other sources of customer interactions, such as chats and emails. This provides support teams with a comprehensive overview of all topics covered in customer support interactions.
That aggregate customer interaction data is displayed within the Voice of the Customer Insights. It shows both trends in customer satisfaction scores and patterns in customer queries, such as categories with the most customer queries and topics within those categories:
You can use these VoC tools to understand call drivers and identify issues that other departments may need to address (e.g., quality issues from switching to a new supplier or frustrating shipping delays).
In addition to these detected patterns, Level AI offers standard metrics like customer effort score, net promoter score (NPS), first call resolution, and average first response time.
One Level AI customer saved millions of dollars with VoC Insights by identifying common customer concerns (such as airline cancellations) and enabling a self-service cancellation flow that deflected calls not compensated under contract.
You can also create in-depth reports using our Query Builder by setting up custom filters based on metrics like sentiment score, conversation count, channels, and more:
The Query Builder allows you to build a call center analytics dashboard to answer questions like:
- Is there a noticeable difference in customer satisfaction across different channels for the same type of queries?
- Are new topics emerging that correlate with high customer frustration?
- Is there an increase in requests for self-service solutions for specific customer intents?
Qualtrics: Prescriptive Next-Step Actions Based on Customer Profiles
Qualtrics gathers omnichannel customer feedback, from survey responses to chat and call responses, and builds detailed customer profiles based on past feedback and customer interactions.
This data can be used for segmentation and follow-up automation.
Qualtrics reporting features include analytics dashboards to understand customer satisfaction trends and the ability to sort feedback by venue location. It can also generate prescriptive next-step actions based on customer history.
Medallia: Actionable Next Steps & Customer Churn Prediction
Inside Medallia, reporting dashboards can be customized based on location, team hierarchies, or products. Some of the reporting capabilities worth mentioning are:
- Churn prevention: Medallia can analyze customer interactions to predict when customers are at risk of churn. It then recommends specific actions and templates for responses to increase retention.
- Role-based reporting and action items: Action items to improve CX can be broken down by role, from C-Suite to frontline customer support employees.
- Customer journey visualization: Medallia unifies customer data across web, contact center, and locations for a full customer journey visibility. This is especially relevant for organizations with multiple locations, such as retail stores or restaurants, as it helps track each location’s performance and identify which steps of customer journey can be optimized.
Additional Features
Level AI: Real-Time Agent & Manager Support for Higher Customer Satisfaction
Below, we’ll share details about two more Level AI features:
- Real-Time Agent Assist and AgentGPT
- Real-Time Manager Assist
Agent Support: Real-Time Context-Based AI Suggestions
In an ideal world, agents would be fully trained and remember all the rules for resolving multiple issues, so they wouldn't need reminders for next steps or policies. In reality, however, agents may forget how to resolve specific issues or become too overwhelmed to recall a particular policy.
This is why Level AI offers two types of support for call center agents: Real-Time Agent Assist and AgentGPT.
Real-Time Agent Assist shows action hints, warnings, FAQs, and a call summary based on what’s being discussed during the call, all in an easy-to-follow user interface. The content is updated in real time based on the details of the call.
Real-Time Agent Assist automatically generates a call summary that will include follow-up actions based on the conversation, if necessary.
Within Real-Time Agent Assist, agents can also use AgentGPT, a ChatGPT-like search feature that summarizes information from multiple resources to suggest next steps toward resolution.
It proactively suggests resources based on topics mentioned during the conversation, reducing the pressure on agents to quickly find the right answer during the call.
The suggestions AgentGPT provides can be upvoted and downvoted to train the AI to provide relevant information in future sessions.
Real-Time Manager Assist for Call Monitoring
While some call center solutions only notify managers when a call runs too long, this isn’t always the most accurate indicator of when agents need help.
Instead of only relying solely on call duration, Real-Time Manager Assist flags calls when customer Sentiment Score drops below a certain level.
Those calls are displayed live on the Real-Time Manager Assist dashboard. Alternatively, managers can set up live alerts to be notified on Slack or Microsoft Teams about at-risk calls.
On the dashboard, managers can explore the reasons for low agent performance or Sentiment Scores by clicking on specific details:
After reviewing these, managers can join the call to resolve the issue or use call whispering for additional support. This allows them to assist the customer more quickly without interrupting the call.
One of Level AI’s clients, ezCater, used agent and manager support features to reduce peak-hour hold times by 23%.
Qualtrics: HR Surveys and Digital Journey Optimization Tools
In addition to customer experience optimization, Qualtrics can be used to improve employee experience and customers’ digital experience.
For companies with multiple frontline locations, tracking employee satisfaction on the same platform is valuable. Since frontline employees often directly impact CX, understanding when they lack support or need more training can also enhance the customer experience.
Employee Experience: Automatic Training Suggestions and Development Opportunities
Qualtrics offers features necessary to conduct HR surveys at every point of the employee lifecycle, including:
- Annual or biannual HR surveys
- Training and development program assessment
- Pulse surveys for regular employee feedback
- 360, 180 and self-assessment HR survey templates
- Onboarding feedback surveys triggered in the first 6 months of employment
The platform’s survey features can also be set up to send out real-time alerts to HR when employees appear to be at the risk of quitting.
In addition to out-of-the-box surveys, Qualtrics offers on-demand support for survey creation.
Digital Experience: Customer Profiles for Better Ad Targeting & Insights
In addition to must-have digital experience analytics tools like heatmaps, session recordings, and digital journey tracking, Qualtrics can help teams improve marketing campaign performance through:
- Personalization and data enrichment tools: Marketing teams can build customer profiles and use them for targeted campaigns, reducing reliance on first-party and third-party cookies.
- Ad effectiveness measurement: Qualtrics captures demographic data of website visitors to improve ad targeting and increase conversions.
Qualtrics is also valuable for product teams, allowing them to gather feedback from existing product users.
It integrates with tools like SAP and Amplitude, enabling both product and marketing teams to set up and deploy surveys based on specific targeting criteria to reach the customer or user segments they need.
Medallia: Automated Suggestions on Next Best Actions for Employee Experience & Digital Journeys
Employee Experience: Evaluating Company Culture & Improving Experiences
In addition to surveys for specific employee lifecycle touchpoints, Medallia offers in-the-moment surveys and feedback opportunities for higher employee engagement and timely feedback.
It can also be used to collect feedback on company culture, such as assessing trends that impact inclusion.
Medallia can be configured to send role-based alerts across the HR team and provide actionable insights on the next steps for improving employee experience.
Digital Experience: Guided Journeys with Next Step Suggestions
Medallia uses feedback responses and digital experience analytics tool data to evaluate user experience and improve it. The following functionality can be helpful for conversion-focused marketing teams:
- Behavioral signal analysis: Medallia automatically scores each digital experience and can be set up to trigger specific actions to improve digital experiences (e.g., opening a chat window for a user that appears to be confused).
- Intent-based customer journey personalization: This feature can suggest next best actions to a website visitor to elicit a desired response. Medallia can also provide recommendations for additional touchpoints through different channels (like email or text).
Conclusion
When choosing between customer experience analytics solutions, it’s crucial to consider your organization’s specific needs.
Level AI is ideal for companies looking to enhance call center quality assurance, provide real-time support for agents and managers, and leverage detailed reporting to improve their call center performance.
Both Qualtrics and Medallia offer AI tools for customer service, but they are better suited for organizations seeking an all-in-one platform that integrates CX, employee experience, and digital experience optimization.
Medallia helps users optimize follow-up actions and enables proactive outreach to dissatisfied customers in real time.
Qualtrics offers deep analysis and provides granular, role-based recommendations from various data sources.
Reach out today to schedule your Level AI demo.
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