Get the Rest of Your Org on the 'Front Lines' with Your CX Agents Fin Analytics

Get the Rest of Your Org on the 'Front Lines' with Your CX Agents

We are huge proponents of shadowing of all kinds as a way to facilitate better communication between front line agents and every other part of an organization. The Fin Analytics video stream opens up new types of shadowing that can dramatically increase your team's efficiency and pace of improvement in tools and processes.

Fin Analytics provides a few different key data assets: (1) It gives you individual and organizational level browsing data, which you can use to understand the complete set of resources your team uses, inside and outside of your core CRM and admin tools. (2) It also provides you a full screen video and audio stream for all work done by your team.

Making use of the time spent / browsing data is fairly straightforward, but we get lots of questions from customers about the best ways to make use of this screen video data, so in this post, we’ll talk about some of our favorite ways to use video assets to drive improvement across your organization.

It’s All About Shadowing

One of my favorite conversations I have had with the head of any CX org was with a woman running the customer support operations for a marketplace business. We were talking best practices for scaling ops teams, and she told me that one of the most important policies she implemented everywhere she worked was a quarterly shadowing day mandatory for all leadership.

One of the obvious benefits of this practice is the first hand education of execs about specific problems customers are encountering and the processes and work the CX org is doing to solve them.

I learned one of the less obvious benefits of this practice from talking to the front line agents about why they liked these shadowing days.

In many organizations where the operations team (and individuals on it) measure their performance with a set of metrics, there is a concern from the front line agents that everyone else in the organization–execs, the QA team, managers, engineering–sees them only as a set of abstract numbers.

What many agents love about shadowing is showing other members of the organization the set of problems and frustrations they must deal with every day as part of their job: irate customers, broken or slow tools, inefficient or unclear processes, etc.

Shadowing is a critical feedback channel agents can use to communicate these frustrations to various other members of the organization that can help solve them.

In this post, I’ll talk in detail about several distinct types of shadowing (some of them only possible with Fin Analytics):

  1. Traditional, In-Person Shadowing
  2. Reverse Shadowing
  3. Spot Review Shadowing
  4. Targeted, Virtual Shadowing
  5. Eng Debug Shadowing

Traditional, In-Person Shadowing

Traditionally, when people talk about shadowing an operations team, they refer to sitting next to someone and watching them do their job.

While this has the nice benefit of getting you some face time and personal rapport with someone, there are a few major drawbacks:

  1. You may need to fly to a different state or country, which adds a huge amount of overhead
  2. You can only shadow at ‘real time’ (not faster than real time)
  3. You are subject to seeing the random cases that a person happens to pull up throughout the day (vs a more focused subset of cases)
  4. The agent may behave differently when you’re sitting next to them (eg, your presence may distract them or make them nervous)

Reverse Shadowing

Reverse shadowing is a bit outside the scope of this post, but worth mentioning for the sake of completeness. This is more often performed in the context of training new agents than it is performed across functions, but the basic idea of reverse shadowing is to have the more experienced agent watch and advise, while the less experienced person ‘drives’ the tools and interactions.

Spot Review Shadowing

Many QA teams employ a spot review process, where a team reviews some percentage or number of cases worked by each agent per week or month.

Normally, the spot reviewer has access to a CRM artifact (chat transcript) and maybe a call log if an audio recording exists.

These often, however, do not tell the complete story of why a particular case took 6x longer than the average for the case type. Or, getting to the root cause using the typical artifacts, if it is possible at all, is incredibly time consuming.

One key use of Fin Analytics is super-empowering QA teams with full screen recordings of every agent interaction. Pulling up the screen video and watching it at 4x speed can often be a much more direct path to figuring out where a particular agent got stuck in their process.

Targeted, Virtual Shadowing

In-person, traditional shadowing is pretty much always subject to a random sampling of cases–whatever the agent pulls from the queue next. Similarly, spot reviews are also often randomly sampled. When there is limited QA bandwidth, however, it may be more effective to do more targeted shadowing of specific subsets of cases.

Rather than shadowing completely random cases to uncover process and tools problems, you can target your shadowing sessions to those likely to be correlated with issues: eg, you might choose to shadow:

  • only cases where a customer complained / gave a low CSAT survey score
  • or, only cases that are the fastest (p95) or slowest (p10) handle times for a particular workflow
  • or, only cases from your highest variance workflow

Prioritizing your shadowing time in this way is a far more efficient way to uncover problems than random shadowing.

NB: we only recommend prioritizing your shadowing time when the goal of QA / shadowing is process improvement, not when you are scoring agent performance. When scoring agent performance, we recommend metrics that cover every interaction or a random sample, if you must sample.

Eng Debug Shadowing

A final shadowing case to cover is the shadowing done by engineering teams building the internal tools used by operations teams.

This type of shadowing benefits from the same ability to filter down with Fin Analytics to targeted sessions in the way discussed above.

The additional workflow Fin Analytics enables for this type of shadowing is the bug reporting feature of the Fin Chrome Plugin:

report bug

With a few taps, agents with the Fin Chrome Plugin can log a bug that will automatically include the URL they were on when the bug occurred, along with a pointer to their video stream of when the bug occurred.

This means that agents don’t have to waste time going to some other tool to file a bug report, trying to describe in prose the sequence of actions that occurred that led to the bug, or trying to reproduce the bug so that they can record it with some other tool.

This returns tons of time to agents they can use to spend working on customer cases, and the video attachments of bugs ‘in the wild’ give the engineering team an invaluable tool they can use to resolve bugs more quickly for users of their internal tools.


We are huge proponents of shadowing of all kinds as a way to facilitate better communication between front line agents and every other part of an organization. The Fin Analytics video stream opens up new types of shadowing that can dramatically increase your team’s efficiency and pace of improvement in tools and processes.


Fin Analytics gives your team ‘full funnel’ insights into your team’s work. Continuous live video and action logging you get the insights you need to provide better coaching and training, and the analytics you need to know where to focus process and engineering resources

We are happy to share with you industry specific case studies, and give you a custom walkthrough of the tool, or you can review our