Sheri Greenhaus, Managing Partner of CrmXchange, recently had a conversation with Charlene Wang, VP, Head of Marketing, Fin (Fin.com) to discuss Fin’s solution for enabling more productive and effective CX teams. You can visit FIN at CCW, booth #220
This is a reprint of the original interview on CrmXchange.
Tell us about Fin.
Fin is a Work Insights Platform. We empower companies to achieve better CX outcomes by providing comprehensive visibility into the agent journey, surfacing insights that improve agent and customer experiences.
Fin instantly pulls in data across all browser applications to paint an end-to-end picture of what the agent journey looks like. This uncovers insights, beyond just the CRM or ticketing system, into how time is actually spent, the “golden path” for optimal outcomes, and specific ways to improve coaching, processes, and technology.
How did Fin start?
Fin started as an internal tool. The original founders of Fin were the first VP of Product from Facebook and the Co-Founder of Venmo. They created a virtual AI assistant. They ended up with a huge support team of hundreds of people across sites around the country to help manage the requests from customer issues and challenges. It quickly became a management issue.
They needed to understand what was happening with the team, how to retain and enable the team to be better, and how to drive more operational efficiency amidst changing customer and agent needs.
The founders’ key insight was that agents were primarily using SaaS applications. All of the work was happening within the browser. With a simple browser plugin, we were able to access almost all the data on agent behavior across applications. We then structured the data to reveal the story of an agent’s day-to-day experience. We looked at how to optimize processes. We looked at the handle time spent on different types of tickets, knowledge bases that are working, missing knowledge articles, how internet load speeds on frequently used pages impacted outcomes, and even where to make agent coaching better, based on what we observed actually working, not just our best guess of what works.
With this knowledge, we personalized coaching, adjusted processes, and improved our technology stack. We looked at the metrics around how tickets are resolved to find the best way to handle those types of tickets. From there, we were able to look at how the best responses could be replicated for other agents.
What data are you looking at? Are you looking at agent data, ticket data, etc.?
All of that data. We organize workflows by tickets, but we know the agent, we know the customer, the types of tickets. We take any activity in the browser and extract that data to understand what is happening. We can layer in things like NPS scores as well as what kind of tickets resulted in what handle times, reopened ticket rates, even whether agents end up staying at the company or leaving, and more. Most of this data is available out-of-the-box on day one. All this data is tied together to paint a complete picture of the agent experience.
If I am a customer starting on the web, progressing to a call, does Fin see and understand that?
Yes, as long as a record of the activity exists in a system of record in a SaaS application, we can provide insights into what’s happening. One of the metrics we look at quite a lot is ticket reopens (alternatively, we look at first time resolution) which gives us insights into the effectiveness of a resolution, no matter which channels the initial and follow up activities happen in.
Are you a data analytics company? Do you help with automation?
We are an analytics or data insights company, and we also enable many other types of solutions, such as automation or RPA solutions. Many companies want to automate parts of the agent journey, but the problem is that it’s hard to understand the real customer journey. What underpins all of that is the ability to identify where automation would best serve the organization. Often, companies have an idea of where things can break down, but don’t actually know where the real breakdowns happen and what the most repeatable processes are. Having the data to back up the hypothesis of what needs to be automated is helpful and necessary.
Another thing that we enable companies to do is A/B test how operational changes impact actual outcome metrics. For example, if I am not sure that a change in my knowledge base will impact resolution time for a ticket, I can test it and do a side-by-side comparison. This A/B testing can also be applied to any RPA solutions that a company introduces. This helps to both identify the impact of a process or technology change on outcomes and make a more ROI-based business case for people, development resources, etc.
Let’s dig deeper into how to assist with coaching agents.
For coaching and training we first look at what is actually working – who is doing a good job, what are some of the behaviors that drive a good outcome? We have a dashboard of process metrics that helps guide what SOPs should look like, where there are opportunities for more QA, and what steps are agents doing that need to be adjusted.
The next area is technology. For example, Airbnb has a product team that builds applications to enable their associates and contact centers. They use Fin to understand if their associates are using the applications that they’ve built and if it’s helping impact the metrics.
We identify bottlenecks that are frustrating agents. We found in one case for one of our customers, agents were doing large amounts of copy and paste due to a bad SOP – this was a huge waste of time. In one instance a company’s agents were taking customer data and documents and pasting it into Google translate. This was introducing risks to the business. Because of Fin, they were able to identify the problem and figure out better ways to enable their agents to avoid this kind of behavior.
You mentioned that you can help with the reduction of agent churn.
We've helped some of our companies predict when agents are about to churn based on behavioral data. One company had their HR database set up, and we were able to tie that data to the data in Fin and see that the risk factors for churn included behaviors like when agents stopped engaging with the CRM, if they were spending time on Facebook, etc. All these factors together let us build a data-driven profile of agents who have a greater chance of leaving the company. Based on that, we were able to identify teams at higher risk of churn and some of the factors that can be rectified.
We’ve found that some of the top reasons why agents choose to leave are poor enablement and burnout. As the Great Resignation continues, companies can’t afford to lose their best employees. We try to identify how to make the agent experience better and less frustrating overall and help companies target the specific teams that data suggest have the greatest risk of turnover.
Many teams are now remote. Does looking at the data help manage the agents?
Yes, we help manage remote teams by providing objective, data-based ways for companies to understand remote agents, manage the entire team towards better outcomes, and create better experiences. When the pandemic started, Coinbase suddenly sent all of their agents home and struggled to understand the experience of these newly remote agents. Coinbase has been using Fin to gain visibility into what their remote agents need and how to enable their success, especially as the team has grown rapidly in the last couple of years.
For companies who request it, we also offer screen recording. For some managers, no longer being in the office means that they can’t see what their agents are dealing with. We’ve had companies use the screen recording feature in lieu of “walking the floor” as they would have when agents worked onsite. In many cases they use these screen recordings as training videos – to show an improved way to do a task that one agent has discovered and that others should emulate.
Finally, for some companies in highly regulated spaces, they have strict requirements around data privacy, auditing, and compliance. In some cases, they need to see if agents are copy and pasting sensitive data. If there is a lot of copy and paste, they want to identify what drove agents to do this action. Fin helps companies identify potential sources of data privacy risks and implement procedures to ensure that companies stay compliant.
How do you help with capacity planning?
We give a level of insight that provides a highly granular ability to predict exactly how many agents (or how much BPO capacity) is needed, especially given changing needs from customers and the business.
Some companies struggle with how much time it takes for agents to work with certain types of tickets. By helping understand the exact handle times spent on specific types of tasks and how much inefficiency can realistically be reduced, we help identify precisely how many agents are needed to support a company’s specific requirements.
During the pandemic, many of our ecommerce customers suddenly and unexpectedly saw their businesses double or even triple overnight. They needed a better handle on how much resources they required to support these new customers. Using Fin, these companies were able to precisely forecast the number of agents needed. Additionally, without enough resources to staff up immediately, they were able to find creative ways to enable the existing team to handle the spike in demand through automation, training, better knowledge base articles, etc. This would not have been possible without the level of insights that Fin gave into the exact ways in which agent capacity was being used and the top capacity bottlenecks.
Are the reports and insights from Fin available out-of-the-box?
We built Fin to be extremely easy to install. Most customers only need their team to download the browser plugin, and with minimal setup, Fin immediately starts collecting data, which is then structured into out-of-the-box reports.
We have many out-of-the-box dashboards of common pain points and common metrics. These dashboards were created from our firsthand experience building and growing a large support team and the kinds of insights that we needed. We’ve also continued to refine and improve our out-of-the-box reporting based on the needs of our customers. From the feedback of customers, we’ve developed a variety of solutions-based dashboards that help with everything from capacity planning, technology monitoring, agent coaching, BPO management, etc. All of our out-of-the-box dashboards are available immediately and do not require any custom configuration.
For those who have more advanced requirements, the product is extremely configurable so that you can do what you want with the data. We have a Customer Solutions team who works with some of our customers to build custom integrations, reporting, and insights for their specific needs.
When looking at the reports can you drill down for more information?
Yes, the platform lets you drill down as much as you need to. In our overview dashboards, we aggregate the data to help show an overview of all the different paths of a ticket. You can then drill down to the specific individual and specific paths. If you have screen recording enabled, you can even review the video, which is timestamped and tagged at the different stages.
Who are your best customers?
They are companies that have a large customer base who call into their contact centers frequently. Many are consumer facing. These companies have a high volume of requests and a short period of time to get them right. Their customers have changing needs and require complex operations to support them, and the way in which customer requests are resolved can make or break the customer experience and how competitive these companies are in highly dynamic markets. They need to stay on top of what is happening and adjust accordingly. And, they have to be very efficient. Our customers handle a lot of operational complexity, often experience constant change, and do so in an environment in which both efficiency and outcomes matter.
When you talk about efficiency, what are 3 best practices to enhance efficiency?
Every year, we analyze tens of millions of hours of agent work data and provide an in-depth analysis of best practices and benchmarks in whitepapers that we publish, including in our annual benchmark report. Here are some highlights:
1. Have a CRM that surfaces the exact info that agents need. CRMs that are set up correctly with the right data available to the agents is key. In our research, we’ve seen a strong correlation between time spent in the CRM and the effectiveness of ticket resolutions.
2. Understand what is happening in the knowledge base. Often customers don’t know what needs to be in the knowledge base and how it should be configured. Most of our customers immediately find something that they can optimize in their knowledge base, and a better knowledge base is one of the biggest contributors to a 16% increase in agent productivity that we see across Fin users.
3. Use data to streamline processes and applications. We’ve helped our average customers reduce handle times by 25% simply by identifying more efficient paths to resolve most tickets. Companies need to be able to identify the “golden path,” i.e. the path that produces the best results. The best way to do this is by looking at the data of what actually works, not just what you believe should work.
To read our latest research, visit fin.com/documentation
What else should we know about Fin?
The principle of applying analytics, A/B testing, and instrumenting measurement has existed in product development and marketing for decades, but is not yet prevalent in the operations space. Historically, the data on people, processes, and technology has been hard to collect and harder to understand. In today’s world, knowledge work is critical and only becoming more critical over time to stay competitive. Having data-driven insights on knowledge work and being able to objectively understand what’s driving outcomes and identify improvements will eventually be the de facto standard that every company expects. We're now right on the precipice of a more data-based understanding of how people and operations work. The analytics technology finally exists to support continuous improvement in operations work, the way that it has enabled marketers and product developers for decades.
Fin gives companies an end-to-end view of operations work at a level of detail that allows you to actually troubleshoot the problems, instead of just identifying that they exist. As far as I've seen and as far as all the conversations we've had, there are no other solutions giving this level of insight, across applications, to CX and operations leaders. I’m a data nerd, and I personally find it very exciting to empower operations and support leaders with the confidence to take their seat at the table, armed with knowledge on exactly how they can move the needle for the organization.