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Blog / Artificial Intelligence

Real-Time Agent Assist: Features, Advantages & 7 Alternatives

Reading time:
19 mins
Last updated:
October 15 2024
Real-Time Agent Assist: Features, Advantages & 7 Alternatives
Blog /Artificial Intelligence / Real-Time Agent Assist: Features, Advantages & 7 Alternatives

Real-time agent assist gives contact center agents instant, AI-driven guidance during support interactions, ensuring they have the most relevant information at their fingertips to resolve customer issues.

Giving agents the information they need when they need it resolves a number of issues that have typically plagued customer service:

  • Agents often juggle several tasks at once: they’re searching for answers, navigating multiple systems, and thinking on their feet to provide solutions, all while maintaining an affable flow of conversation.
  • This process of rapidly searching through knowledge base articles — while the customer patiently waits on the other end of the line — can be very slow. It’s fine if the agent already knows the answer, but if they don’t, all this searching can slow down conversations and test the willingness and patience of customers (not to mention reduce the number of support inquiries an agent gets through in a day).
  • Agents feel unsupported if they’re thrown into complex or unfamiliar situations — which makes escalations and longer resolution times likely.

Real-time agent assist overcomes these challenges because it comprehends the meanings of words as they’re spoken.

This allows it to “know” which knowledge to show at any given moment, based purely on the topic currently under discussion.

An agent who doesn’t need to go searching for information can now stay fully engaged in the interaction, letting their empathy and personal touch shine through, rather than slogging through lengthy articles to find the bit of knowledge they need.

And for customers, interactions feel more genuine since they’re speaking to an agent who’s focused on their needs rather than reading through a script or stalling for time.

With this in mind, the rest of this article explains the mechanics of how real-time agent assist works. First, we show features from our own Level AI product, and then compare these to five alternative solutions.

1. Level AI

Boost Agent Productivity without Increasing Workload

Level AI’s Real-Time Agent Assist displays for agents relevant knowledge base articles, prompts, and suggested responses during live customer interactions.

Below, we provide examples of how our solution works, but first we want to highlight the importance of detecting intent in conversation when it comes to call center support tools. Many systems today call themselves “AI powered,” but when you peel back the curtain they’re in fact just matching keywords or relying on a rule-based system to trigger responses.

They lack sophistication to truly understand the intent and context behind what’s being said, which gives them only a crude understanding of the conversation.

Here’s an example: a customer complains about a mismatch between what was ordered and invoiced. The system might be trained to recognize such situations by identifying certain words like “invoice,” “mismatch,” “order,” etc.

But people don’t always use the same patterns when they speak. So a customer might express their issue by saying, “There’s something off with these numbers.” Although it might be clear to the agent that a particular item of the bill is under discussion, such a statement might not trigger the keywords the system is trained to recognize.

To catch all such potential situations, administrators typically enter tens (or even hundreds) of keywords for a given intent, but this doesn’t guarantee the system will capture the intent 100% of the time.

Moreover, though a keyword-based system might successfully detect a certain intent, it’s likely to still miss important nuances or underlying issues that tell you the why behind the intent (like a customer’s dissatisfaction in not being given a discount).

This is where Level AI’s natural language understanding (NLU) comes in. Our platform uses NLU and generative AI to detect not only the meanings behind words, but associated sentiments as well, like when someone is unhappy, disappointed, worried, grateful, and more.

While these secure and customizable Generative AI capabilities drive a lot of our post-call analysis features, it also enables our Real-Time Agent Assist to accurately display the right topics at the right time to provide agents with timely support.

Content that Adjusts Dynamically to the Flow of Conversation

Real-Time Agent Assist connects directly with your knowledge base and other sources to aggregate all the information and display:

  • A main feed showing action hints, warnings, and FAQs
  • Recommend resources retrieved from connected, internal sources like ticketing and knowledge systems
  • Chat with Your Knowledge Base (search functionality)

As the interaction progresses, the cards shown in both the main feed and resources are updated as new topics under discussion are detected.

All cards feature thumbs up and down icons for up- and downvoting the relevance and helpfulness of the information being shown to agents.

To effectively train the AI, the system offers several categories of negative feedback:

  • The card would have been helpful but was delayed
  • The card shows irrelevant results
  • The information shown on the card is inaccurate, although it may be timely and relevant.

Not only does this help train the AI, but it also keeps your knowledge base up to date, which is important since the completeness of your knowledge base can make or break a real-time agent assist system.

The real-time dashboard also proactively displays scripts and guidance during conversations, as well as a live transcript:

Our Chat with Your Knowledge Base predicts and displays the most relevant search queries during the discussion, automatically surfacing (and summarizing) information from multiple articles to provide at-a-glance answers.

It auto fills the search bar with relevant queries as the conversation progresses:

As you can see on the right side of the screen above, agents will also get conversational answers similar to ChatGPT.

Administrators can configure your front-line chatbot to handover support cases to Real-Time Agent Assist as the need arises.

Using Real-Time Agent Assist, our customers are seeing significant improvements in efficiency and customer satisfaction. For example, Level AI customer ezCater has seen a drop in average handle time of 13%, as well as a decrease in call hold times by as much as 23% during peak support hours. This means that 94% of calls placed by customers during that hour are reduced by 30 seconds, allowing agents to improve efficiency while maintaining the same level of consistent, high-quality service.

Steering Agent Success with Call Monitoring

Level AI lets managers guide agents based on real-time call metrics and indicators, such as sentiment analysis, agent performance, deal size, the live call transcript, and more.

Real-Time Manager Assist displays call and customer analytics in a single screen, giving managers an at-a-glance view of ongoing conversations to easily decide where to intervene.

This is in contrast to traditional indicators like whether a call has been going on for too long or if the agent is taking a lot of time for post-call wrap up.

In the past, such criteria didn’t really give managers a clear picture of what was happening on the call, which led agents to sometimes experience interventions by their supervisors as intrusive, since (for example) call duration alone is not an indication that things are faring poorly.

What’s more, supervisors often didn’t have enough context about the conversation (based on their crude metrics) and needed the agent to explain the situation, taking up the agent’s time and effort.

Level AI’s real-time indicators give a much clearer picture of the state of a given call, requiring less effort from all involved to understand a call’s context while generally improving the relationship between managers and agents.

To further explore whether it’s necessary to assist agents, supervisors can click on any of the metrics to display supporting data:

Especially useful are metrics like:

  • Sentiment score, which shows supervisors how positive or negative a customer currently is on a call (on a scale from 1 to 10, with 1 being extremely negative and 10 extremely positive).
  • InstaScore, which shows how well an agent is performing according to a predefined rubric.
  • Coachable insights summing up all the metrics like “High call time” and “Agent recommended a good solution.”
  • Call duration.

Putting these together, a supervisor might see that during the closing phase of a call, an agent is struggling while customer sentiment drops, and so decides to use the Call Whisper feature to advise the agent on how to handle the situation.

Real-Time Manager Assist also allows supervisors and coaches to easily add agents to the coaching module of Level AI’s post-call QA platform.

Auto Categorizing Support Conversations

Another way Level AI saves agents time is by automating call dispositioning.

Normally after a conversation, agents must search through a tiered tree of categories to figure out which one is relevant to the conversation they just had.

Then, they manually assign the conversation a category and subcategory. Such exercises are sometimes nearly effortless when the purpose and resolution of the call are clear. But other times, if the agent is unsure how to categorize a call, or they’re weary and stressed, the effort can be time consuming.

Because Level AI can understand what’s being said, it accurately summarizes and categorizes calls based on topics discussed and whether the customer’s issue was resolved, saving agents the time and effort of doing the dispositioning themselves. The outcome of this is also consistently accurate, as the system reduces human error and bias.

Level AI generates such categories based on the intents uncovered during conversations, and for each category associates a number of example terms on which it created the category:

If you create your own, business-specific categories, the system shows example terms for each category, including “near-miss” terms that may or may not be relevant to your intended category. By accepting or rejecting these, you train the AI to better understand and refine its category definitions.

Discover How Level AI Empowers You to Assist Agents

Level AI represents the state of the art in natural language understanding and conversational intelligence, and gives agents the tools to deliver exceptional customer experiences by accurately interpreting and responding to customer needs during every interaction.

Schedule a free demo to see how Level AI’s Real-Time Assist and related functionality boosts agent efficiency while upholding the same consistent, high-quality service.

2. Observe.ai

Observe.ai is a conversational intelligence platform for contact centers that provides agents with real-time support during interactions. It gives agents guidance to help them deliver better experiences for customers and resolve issues faster.

The software offers:

  • Smart scripts for keeping agents on track and providing them with self-coaching.
  • Alerts and prompts for contextual, step-by-step guidance.
  • Automated call notes that auto summarize completed interactions.
  • Real-time analytics for better discernment of trends in customer behavior and agent performance.

Their sales team can provide you with a price quote for their real-time agent assist feature.

3. Dialpad

Dialpad is a popular business phone service that provides real-time guidance and onboarding for customer service reps, among many other features for customer service and sales.

For real-time agent assistance, Dialpad provides:

  • Real-time assist cards showing relevant information on certain topics are displayed for agents during conversations.
  • Real-time transcriptions as a permanent record of interactions for purposes of analysis and administration.
  • Sentiment analysis for managers to assess the general direction of calls for deciding whether to intervene or not.
  • Analytics showing patterns in call volumes, to help managers maintain service levels.

Dialpad offers a variety of pricing plans starting at $15 per user per month and scaling up to the full enterprise version. A free trial is available.

3. Cresta

Cresta is contact center software that provides live guidance to agents based on the best practices of your top performers. It also lets managers track customer conversations and agent progress in real time.

The platform provides customer service organizations with:

  • Behavioral coaching driven by outcomes, using tailored workflows, reminders, and dynamic hints.
  • Generative knowledge assist to summarize and unify knowledge sources to generate accurate answers to customer questions in real time.
  • Automated summarizing of the content and outcomes of support interactions for easier comprehension by managers and agents.
  • AutoCompose for generating automated responses to save agents time and effort, and reduce agent typing by 50%.

According to Cresta’s website, you can request a custom quote from their sales team.

4. Qualtrics XM Platform

Qualtrics is customer experience software that provides tools and assistance to customer service agents for helping them increase their productivity in order to improve customer satisfaction.

The platform offers contact centers:

  • Real-time agent assist tools for surfacing relevant content when agents need it.
  • Automated call summaries to reduce after-call work for agents and save time and cognitive effort.
  • Agent coaching for driving continuous improvement by identifying areas of strength and improvement, and to track performance.

Pricing depends on the pricing a customer purchases, as well the products within a module, such as Frontline Digital or Frontline Care.

5. Five9

Five9 is cloud-based contact center software that offers inbound and outbound calling, call recording and routing, and other communication features.

For real-time agent assist features, Five9 provides:

  • Guidance cards that recommend next steps and checklists for fast resolutions.
  • Real-time transcription to save agents the effort of taking notes manually and to reduce misunderstandings and errors.
  • Automatic call summarization to reduce post-call administration work for agents.

According to their website, Five9 offers separate pricing depending on what bundle of services and features customers get. Pricing starts at around $175 per seat per month for digital interactions only.

6. Convin

Convin is conversational intelligence software that supports post-call and real-time interaction use cases for automating quality assurance and coaching agents.

The platform provides:

  • Real-time guidance and next-best actions by extracting critical information for agents during ongoing calls.
  • Guided call scripts to ensure agents stay on track during interactions and follow call flow, along with a visual checklist.
  • Proactive alerts and suggestions to notify agents of their behavior during calls, like if they’re monopolizing the talking during a conversation.
  • Dynamic battle cards with context displayed in real time, for helping agents handle difficult situations. These cards provide advice and next actions to take, and include hints, step-by-step instructions, and optional follow-up questions to ask the customer.

Convin pricing depends on features that customers purchase, and prospective customers must speak to a sales rep to get a quote.

Get Started with AI-Powered Real-Time Agent Assist

Level AI is a contact center AI solution that provides instant, context-aware support and relevant knowledge to help agents during live interactions, empowering them to resolve customer queries swiftly and accurately.

To get started, schedule a demo today and see how Level AI can enhance your customer support with AI-powered efficiency and precision.

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