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Figo Saves $700k a Year, Gains Critical Visibility into the Business

With Auto QA, Figo gets insights from every customer interaction. Based on Figo's calculations, it would have cost them $700k per year to achieve this level of visibility.

cost savings with Auto QA
visibility is driving better business outcomes
hours saved by using automation

Figo Pet Insurance is growing. Fast. Customers are increasing steadily, along with insurance orders and service-related engagements.

Although a certain percentage of Figo's customer-agent interactions were manually reviewed to ensure compliance, contact center leaders still had only limited visibility into what was actually happening on the front lines.

"When I joined Figo in November 2020, it was with the intention of building a foundation for expansion," says Ken Fausel, Director of Customer Experience at Figo. "One of the major pieces of that puzzle was quality management. Supervisors reviewed calls to ensure compliance or to respond to customers, but there was no systematic way to know what was happening in customer conversations at scale."

With that charter in mind, Fausel had two choices: "I could either go the traditional method and hire a team of quality assurance specialists to evaluate interactions and get insights," said Fausel. "Or I could go the technology route and as a technology-first company, we were ready to put our money where our mouth is."

Figo's Digital Transformation Journey

Fausel quickly realized the manual way of analyzing customer conversations was not going to provide the speed and velocity of insights the business needed.

Fausel turned to Observe.AI for its QA automation solution, Auto QA. Auto QA uses the power of AI and machine learning to automatically recommend and score agent interactions at scale, allowing teams to accomplish the unfathomable: the ability to analyze and evaluate 100% of interactions.

"The speed of the business moves fast and we needed better data to make business decisions quickly," said Fausel. "With Auto QA, we're able to get more data very quickly so if we find an area we can improve on or need to correct, we can make the change within the month because we're confident in our decisions, instead of taking six months to change a process."

Implementing Observe.AI allowed Fausel and Figo to gain unprecedented visibility into every front line customer engagement without needing to hire and train QA specialists, saving time, money, and the energy required to ramp and manage a new team.

"When I first started, we didn't have any visibility into customer interactions. We would listen to calls only for specific purposes, but there was no scoring, there was no tracking, there was little ability to see trends," says Fausel.

Now, Auto QA is evaluating all of the interactions coming into Figo's contact center and providing the entire company, not just the contact center, with actionable insights that fuel agent coaching, drive business decisions, and improve operations.

How Unprecedented Visibility is Driving Better Business Outcomes

Evaluating 100% of contact center interactions is an impressive achievement, but what really matters is how the insights from that visibility are leading to better business decisions, operations, and outcomes at Figo.

"We used to have to make significant decisions based on insights from the two or three percent of calls we would audit," says Fausel. "Now, with Auto QA, we can make those decisions with confidence because we can map performance trends across a much larger data set."

Improving Efficiency with Targeted Coaching

Coaching is critical to improvement across the entire contact center, but identifying the right training process, agent scripting, and spending time teaching the materials can be time consuming for both coaches and agents. If you're going to make the investment, it's best to be confident the training is effective.

"For example, if we noticed a trend where some of our associates were unclear on how they were describing a benefit in the policies, we could identify it and take action," says Fausel. "With Observe.AI, we would be able to see if it was only a few associates or the entire team that required clarification. Rather than wasting time and energy doing a broad team training, we can identify the associates that need more information. We can also learn additional topics to address in our new hire training."

Combating Cancellations

When someone calls to cancel Figo's pet insurance service, agents are trained to ask for a reason. With Observe.AI, Fausel is able to get nearly instantaneous insight into causes for cancellations, identify trends across the entire team, and then devise a plan to combat the ones with highest business impact.

"We can now understand the percentage of cancellations that are due to the cost of the premium being too high or whether it's being offered by their employer or maybe their pet passed away," says Fausel. "With Observe.AI, we're able to quickly identify that information straight from the consumer's mouth instead of waiting for the agent to submit a reason and trust they put in the right disposition."

Auto QA in combination with Reporting & Analytics Dashboards make business KPIs and agents easy to identify and track. This helps teams quickly prioritize the most urgent areas to intervene, coach, and take action in order to improve business outcomes.

Scoring Agents Fairly

Agents are the front line of your business—and we've all seen attrition and retention is a common challenge even in the best of times. If an agents feels they're being treated unfairly, it may be enough for them to look elsewhere.

"You could have an associate that is doing great 75% of the time, but we just happen to grab the 25% where they may have underperformed, which leaves them feeling unfairly judged," says Fausel. "With Auto QA, grading agents on a limited sample size is no longer possible because we're evaluating every call and we're coaching folks on an actual trend, not just a few instances."

Shifting Focus to Growth

Even a seasoned QA team is prone to human subjectivity and error, which can cause unnecessary tension between quality teams and operational teams as they debate whether an agent's score is warranted or an assessment needs better calibration.

"Getting every auditor and supervisor to score questions the exact same way all the time is impossible and that variance causes friction," says Fausel. "Because we don't have a QA team, we don't have to deal with that. Quality is not a person, it's a machine, and it's working as intended so that we can reduce human bias in the process."

This has allowed Fausel and his team to shift from debating the data to taking action on it: "Instead of supervisors focusing on why their agents should be scored differently, they can focus on coaching and development and moving their team forward quickly."

This image shows the contrast between manual vs. automated QA evaluations. With Auto QA, Figo was able to evaluate agent performance based on an exponentially higher volume of data that shows accurate, directional trends over time, instead of the spot-check manual method, giving them critical insights that drive business outcomes.

Automatically Detecting Compliance Violations

Different states have different regulations for selling pet insurance, and the risk of potential fines can keep business leaders up at night. With Observe.AI, Figo can use AI and automation to monitor and audit every interaction for potential issues.

"The traditional way to monitor compliance violations is to manually audit the interactions and hope the ones they chose were representative of the rest," says Fausel. "Observe.AI reduces that risk because Auto QA will evaluate 100% of interactions for us and flag any potential issues so we can correct them. We have confidence across the entire team and every interaction."

Delivering Org-Wide Value

Unlocking the treasure trove of information that is contact center customer conversations not only benefits the contact center, but also has implications for the entire organization. Adjacent business units can benefit from the insights contact center conversation intelligence provides.

"Take marketing, for example: We want to make marketing decisions based on what customers are actually saying, not based on what we think we know," says Fausel. "Instead of hypothesizing, I can say 'Hold on, let's go check the data and make sure we're making these decisions based on what's actually happening in the field."

When Figo's marketing team launched a "refer a friend" campaign, contact center leadership had concerns it might increase call volumes. Using Observe.AI, Fausel could monitor if incoming calls specifically referenced the campaign, but they did not. "With this information, our marketing team was given the green light to promote the refer a friend program as fast as they wanted because it didn't impact our contact center's ability to operate," said Fausel.

Achieving $700K Cost Savings Per Year with Auto QA

With Observe.AI, Figo is realizing $700k in savings with automation which is what it would have cost Figo if they were to analyze the entire volume of interactions coming into their contact center every year in order to get the level of visibility needed to run their business.

With Auto QA, Figo gets insights from every customer interaction. Based on Fausel's calculations, it would have cost them $700k per year to achieve this level of visibility.

"Observe.AI has become a part of every facet of our business. Whenever somebody wants to know what our customers are talking about, I'm able to look it up."

Want the downloadable version and more content about how Auto QA is helping contact center leaders drive business results? Download the Figo Pet Insurance Case Study PDF and more here.

Figo Pet Insurance offers premium pet insurance plans for dogs and cats.
Figo's contact center leaders had limited visibility into what was happening on the front lines, which was impacting compliance, agent coaching, and business decisions.
By using Auto QA by Observe.AI, Figo evaluated all customer interactions and provided the entire company with actionable insights that fueled automatic detection of compliance violations, agent coaching improvements, better business decisions, and improved operations.
Chicago, IL
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