Karla Fiske is a self-proclaimed “bridge builder.” Having previously led customer-centric product orgs at Experian, Arbonne, and Chipotle, she stepped in as the first VP of Product for Tebra’s Patient Experience division in June 2022 and quickly garnered cross-functional support for a unified product roadmap designed to mesh two merging companies into an end-to-end SaaS healthcare solution for SMBs.
In our conversation, Karla explains how she leverages personal relationships to flatten the learning curve of starting a new job in a new industry. She also describes how CX metrics such as NPS figure into her team’s decision-making process and how she uses a “digital placemat” to keep stakeholders abreast of product developments and progress.
In any new industry that I’ve jumped into, for the first three to six months, I’m in absorption mode. There’s a heavy learning curve when it comes to learning the business and understanding the business model. In a lot of these industries, they work very differently, so it’s about understanding how this business model works differently. What are the natural cycles of the business? How does GTM work differently in this industry than others?
An example of this was when I moved from fintech at Experian to direct selling at Arbonne. At Arbonne, you’ve got a B2B2C model happening in the direct selling space. At Experian, I was on the direct-to-consumer side. Direct selling turned out to be a very complicated business model. The way their compensation is structured is extremely complex and the way they sell is not straightforward, so there was a huge learning curve.
One of the primary tactics I used was to find what I call internal historians — subject matter experts who know all the things. I would tap into these historians and befriend them. They helped me understand why things did or didn’t happen and walked me through why things work the way they work. Finding those historians really helps you dive a little bit deeper and develop a greater understanding.
I consider myself a bridge builder. Coming into an organization, it’s really important to know my network and build my connections. One of the key pieces of that partnership is understanding their needs: what are they expecting of me and my team? What am I hoping I can expect of them?
It’s about building a set of expectations that we can align to. We want to determine what we need to be doing differently right now and also chart future vision for where we want this partnership to go.
Having real, candid conversations is important here. Maybe we can’t solve this in the next 30–60 days, but is it something we can work toward as we grow and as I settle into a new organization as a leader?
In a product role, often you’re managing stakeholder expectations and keeping stakeholders informed. When I was at Chipotle, there wasn’t a lot of process and there wasn’t a lot of communication with partners throughout the digital org. There were different executives that oversaw different parts of the digital journey, which already made it a bit complex. In addition, there wasn’t this cadence of sharing out what product was doing, when they would deliver, how it performed, etc.
One of the things I did in the first year came out of a conversation with my CTO. He communicated his concerns around internal escalations from key stakeholders, and not clearly communicated delivery dates. He wasn’t wrong. I needed to fix the process.
I had a digital product leader connection at Target. I asked her, how do you solve this problem at Target? And she was like, “Oh, I use this thing called a placemat.”
The “placemat” is a structured way to compartmentalize, bucket, and organize the work that’s going on and show the progress you’re making. So I Chipotle-tized it; in the span of about a week, I pulled together my peer group, did a pre-read with some of them, and just launched it to get something out there. It might be messy and imperfect, but at least it’s something, and then I’d learn:
The first meeting was like, what are we doing here? In the second meeting, I had a few more questions from the peer group. And by the third meeting, it started clicking. People began to trust it as a forum to have a conversation about the work that’s happening. As a result, escalations really slowed down.
I would publish the digital placemat on a monthly basis. It definitely took prep work to get it updated, but it’s not that much lift. And, ultimately, the value of having cross-functional partners aligned to knowing exactly what was happening behind the curtain. Now everyone knows everything that we’re working on. There are no secrets.
I had the opportunity at Experian to stand up customer experience management, which is the study of capturing, analyzing, and acting on voice-of-the-customer data. If there’s one thing I can recommend to product leaders, it’s to do a deep study in this area. It isn’t going to solve all your product problems by any means, but it will help you solve your biggest customer problems.
I consider Net Promoter Score to be a tool in my toolbox; it’s not the only analytics solution I’ll use, but it is one that I like to use. People sit in different camps on the NPS front, but I think it is still useful in judging how we’re doing and where we can find some of our biggest opportunities.
In my role in leading CX at Experian, I got to stand up a voice-of-the-customer framework, which captured NPS at different parts of the lifecycle. Capturing voice-of-the-customer at different stages and understanding the key drivers of NPS at each stage can help us understand where we have bigger problems.
For example, we were finding there were sticky parts of the product that users were frustrated with. This understanding actually led to an entirely new innovation around fintech, and then it led to a much bigger movement for Experian, which is very exciting. And it was around delivering needs for customers.
Customers would call Experian thinking they were talking to Experian, but Experian was big. So if you had a credit monitoring solution, you would call that credit monitoring solution to fix something on your credit report only to have to get a different phone number to call somewhere else in Experian.
I got to be part of the leadership group that formed the contact center and the backend infrastructure of people and process and technology to help solve that problem. Now, when a customer calls Experian, they’re calling Experian, and so that gives that singular Experian experience.
It just goes to show that deep-diving into each of these areas can help uncover a lot of customer needs and frustrations, as well as where you’re performing really well and maybe where you don’t need to be over indexing on.
The study of NPS is interesting because you can look at things like the age of the customer. For subscription software, you want to learn how long has this customer been with us? Are they a longtime customer or a brand new customer?
Diving into each part of their lifecycle can reveal different problems for different parts of the product lifecycle. There can be a male-female skew in some cases too, and for some products that can be a relevant data point to look at.
Here’s what we would see within different parts of the lifecycle: early on, in the case of subscription, there would be a free trial. Right after the free trial, you get billed. Of course that’s a pain point for customers who didn’t expect to be billed. So, how can we communicate and over-communicate that this billing moment was going to happen? And how can we make sure we build enough awareness so that it’s not a surprise?
When I came into Chipotle, COVID-19 was the catalyst for a lot of hockey-stick digital growth. The team that had built the initial digital offering had done an amazing job in a very early digital time, and they were working hard to keep up with the demands of the huge digital growth. The head of product knew there was an opportunity to uplevel the team, add process to mature the digital product org, and hired me to accomplish this.
In the particular case of Chipotle, what the head of product and I noticed was that we had lost our way a bit not always grounded on the core objectives we were trying to solve for. There was buy-in around the right things to do, but it wasn’t always fitting into a framework, if you will, and they weren’t always being measured in their entirety. So fitting them into that OKR framework to a degree — not being too rigid about it, but just reframing it a bit — was a challenge.
In addition, we had to figure out how to measure what we’re launching. We were so focused on just getting it out the door, to meet the digital demands we weren’t tracking all product analytics. That led into a bigger, deeper need for product analytics…
First and foremost, I wanted to make sure we knew why we were launching something. What are we hoping to achieve? Can we make sure we’re tracking it and its measurables as we’re launching? And then, finally, once it launches, let’s ensure that we’re measuring it and then reading that back out to the teams.
Once this stuff started happening, the cadence of sharing what we’ve learned about customer behavior increased. That was the big unlock. It motivated product managers in a way that it was like, OK, I know what I’m doing, I know why I’m doing this. It’s exciting to watch the fruits of my labor.
The loyalty team was really focused on usage, but we were learning that there was customer friction in the checkout funnel.
If you’re a Chipotle customer, let’s say you’ve earned free chips. You would have to add your free chips reward to your bag. If you hadn’t gone back and manually added the chips to the bag, you would get an error.
When we realized customers had to go backward to do something like that, we thought, shouldn’t we make this all flow together? If I’m adding that reward, shouldn’t it automatically add the item?
Digital experience analytics solutions can reveal anything from the basics of page views and visits to session replays.
I’ve talked about voice of customer, and that really is a great data point to really dig deeper and understand from a voice-of-customer perspective. And it’s not just NPS — it can also be customer effort score (CES), for instance. There are many ways that VOC metrics can be brought to life.
Employees are one of those overlooked areas. You’ve got these subject matter experts sitting all over the company, and they are hearing the same things over and over again. If you poll those folks, they’ll tell you what needs to change from a customer pain point perspective. That’s maybe a rather unusual analytics, but can be really, really interesting and usually pretty accurate UX metrics.
An area that we’re working on internally here at Tebra is the heart metrics: happiness, engagement, adoption, retention, and task success. These are really interesting ways to measure UX in a deeper way.
I see a few things. One, I see more internal enablement. I think the maturation of AI and machine learning to help be predictive is going to be so powerful. Often, there’s cycles that data can flow through, and if those things become understood through machine learning, it can be really powerful for understanding customer behavior.
And then just supporting staff. We’ve seen this in the customer service space where there are AI/machine learning support bots that help agents on the backend. Those same bots are now maturing to a place where I can put them in front of consumers. I think we’ve all interacted with a chatbot is less than helpful, but as that technology matures, it is serving a bigger purpose and helping supply a better end customer experience.
The way I look at AI is that it’s an internal enablement tool first, and once it matures, it’ll make sense to present it to an end consumer. I may not want to risk rolling out a less-than-ideal chatbot experience yet because it might cause my customers to never come back. So I think it’s important to watch this get to a level of maturity where companies feel comfortable putting it in front of consumers. You don’t want a robot that’s misrepresenting your brand.
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