Interview with Ryan Esteb, VP of Sales at Shiftlab on optimizing employee engagement in retail

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Darius: Welcome to the Retail Tech Podcast. My name is Darius Vasefi, and today I am joined by Ryan Esteb, VP of Sales at Shiftlab. Hi Ryan.

Ryan: Hey Darius, thanks for having me.

Darius: Thank you for joining me. Let’s start with a brief bio on your own background and how you got to Shiftlab.

Ryan: Yeah, absolutely. So, you know, I'm kind of dating myself here, but started working at Cingular Wireless many moons ago and eventually was part of the acquisition where AT&T took over. So I worked there for a bit, worked for Verizon Corporate for a while, and ended up at Avis Budget Rental Car. I had a good career going there, and then COVID kind of changed the way rental car was going, so it led me to look for an opportunity and I met Devin Trake, who was the founder and CEO of Shiftlab. We hit it off and, you know, I started leading sales here at Shiftlab in 2022. And yeah, the rest has been history.

Darius: Wow, that’s a pretty interesting mix of experiences from cellular to rental and now employment management. So that's pretty good mix.

Ryan: Yeah, it's been good. You know, I like to lean on my experiences because Shiftlab obviously looks to automate a lot of these processes and bring in the data to make informed decisions. Back when I was managing wireless stores and rental car counters, I was manually staffing, looking at my printouts of traffic and trying to do the conversion metrics and put them where I thought they needed to be. So it's definitely an interesting mix.

What is Shiftlab?

Darius: So let's talk a little bit about what Shiftlab does.

Ryan: Yeah, so Shiftlab is a workforce optimization platform. So we bring in point-of-sale data, we bring in traffic data, and we have a lot of back-end settings that are administration-level. So we are able to rank employees off of key performance indicators (KPIs) that are important to the organization. So we ensure that we are putting your right people in the right shift at the right time. You know, we want to put the top performers in the most high-volume shifts. We want to drive conversion. We want to make sure, you know, in the middle of the week, we don't have four or five people just standing around. We want to flex that staffing model to mirror traffic. So we use machine learning to forecast out what that traffic pattern and what that labor is going to look like based on your sales history and your traffic history.

Note: Shiftlab also includes a time clock solution built to combat "time theft" in retail, featuring break attestations, early punch prevention, and auto-clock out reconciliation.

Solving Scheduling Consistency

Darius: So let’s start by one of my biggest questions about retail staffing, and that is why can't people get a consistent schedule?

Ryan: Yeah, you know, unfortunately, the way retail works, consistency—we're at the mercy of traffic flows, right? We're the ebbs and flows. That's one of the things that Shiftlab does really well is with our forecasting of traffic, we're able to make sure that people aren't standing around wasting their time. One of the metrics that we're working on is retention, because we do see a lot of people that are seeing the benefit of being in the store when the customer's in the store. So rather than standing around and waiting, they're actually there to help, you know, earn more commissions or drive more sales. But yeah, from a consistency on a schedule standpoint, we're at the mercy of the traffic trends.

Darius: I understand the traffic side, but to be honest, traffic can also be predictable. Like, you know weekends are going to be busy. You know, like lunchtime's going to be busy. Yeah, maybe there's 20% variation here and there, but 80% is—and it still is not a—and maybe this is something the new version of AI is going to fix, but I think that's like something that people have gotten used to, of course. But it's unpleasant. You can't like schedule your life around—like, you're already not making a ton of money as a retail frontline employee and this is just adds another level of uncertainty that I think I'm hoping it can be better.

Ryan: Yeah, the one thing I'll say about our forecasting and—you keep mentioning AI and our machine learning—is, you know, we may leverage somebody on a Tuesday for six hours, but then on a Saturday to your point, you know, we know the weekends are going to be busy, so we may actually have them flex up and work eight and a half or nine hours depending on what the organizational [model] will allow. But that gives—it definitely helps with that work-life balance versus a manager typically is just going to say, "Hey, I know I need to get Darius 40 hours, let me just do eight hours here, eight hours here." Our machine learning actually runs calculations by 15-minute increments. So it says, "Does it make sense to keep Ryan around for 15 more minutes based on a profitability scale?" And if it does, it'll extend it; if not, it'll cut the shift short and just repurpose those hours when traffic trends are needed.

Market Trends & Efficiency

Darius: So let's talk about what are some of the like the major shifts that you see coming in the space as far as employment? Like layoffs or tariffs and there's so many variables now.

Ryan: Yeah, I think the most unfortunate one, you know, is the layoffs. I think Verizon recently announced a mass layoff; they liquidated a few of their corporate stores. You know, we're getting into these times where you're expected to do more with less. You know, profitability is becoming more and more [important] due to things like tariffs and product availability, and so I think those margins are getting harder and harder and harder. So managing obviously labor is one of your biggest expense items, so managing that and making sure that you're optimizing that as much as possible is definitely going to be key to kind of overcome some of these things.

Darius: In a way, you can actually help them become more efficient and less—I guess per unit of work the cost could be lower.

Ryan: Yeah, we typically see a gross profit increase—gross profit per labor hour. You know, one of our best use cases within the first 30 days of a launch, we saw a $7 per employee per hour lift in gross profit. And that was just, you know, the organization was over-scheduling; middle of the week, we had three or four associates just kind of standing around, so we created an automation around kind of their historicals and, you know, they came back to us 30 days later with a big smile on their face.

The Technology: Data & App Experience

Darius: What kind of data do you use to do this automation?

Ryan: So we partner with a lot of different point-of-sale systems. You know, we just need point-of-sale data to get your sales transactions and your historicals brought into the platform. Traffic data—so we partner with tons of different traffic providers as well. We bring that in, we run it through our machine learning and our forecasting, and then we sit down with the customer and say, "Hey, how aggressive, how lean," you know, answer a few of these questions, and then we can kind of build that out in a matter of seconds to fully optimize.

Darius: How do you gauge how they [the employees] like the product?

Ryan: So we are currently we are a web app. So everything, you know, we're iPad, Samsung, everything friendly. We will have a native app by the end of the year. We're in the final review process in the app stores. But honestly, the feedback has been really great. Employees like having a device-friendly [way]—they can actually look at their schedule, they can punch in and out. And again, we have multiple ways to go about this, but you know, we have IP verification. So if you want to punch in from your phone, you walk in, it verifies the IP address is good, it allows you to punch in. You know, we have a couple other features—shift swaps—so if, you know, I don't want to work this Friday, I can put that up, but that can all be done from mobile.

Onboarding and Support

Darius: What’s the startup and getting set up process like?

Ryan: Honestly, this is my favorite part about working with Shiftlab. You know, here at Shiftlab, we're a jet ski, we're not a cruise ship. So we can go as quickly as you can get us data. You know, we can set up a couple data feeds and get us an employee feed—in a matter of two weeks we could have your account live. We typically handle training. You know, we would train your field or, you know, if you have a trainer, we could train your trainer and then we launch. You know, it's a fairly user-friendly system.

Darius: Support as the new customer is getting started is critical and these times, yeah.

Ryan: Yeah, and from a support perspective, we do all the support in-house. On our mobile app, there's a—there's a chat bubble, and if you pop that up, it goes straight to our team. It hits my phone, it hits our VP of Ops' phone. So typically you have a response pretty quickly.

 

Key Features of the Shiftlab Platform

Workforce Optimization: Shiftlab is a platform designed to optimize retail staffing by aligning employee schedules with real-time business needs.

Data-Driven Scheduling: The system ingests point-of-sale (POS) data and foot traffic data to understand historical sales patterns and customer flow.

Machine Learning Forecasting: It uses machine learning to forecast traffic and labor requirements in 15-minute increments, determining exactly when a staff member is needed based on a profitability scale.

Performance-Based Ranking: Managers can rank employees based on specific Key Performance Indicators (KPIs), ensuring that top performers are assigned to high-volume shifts to maximize conversion and sales.

Integrated Time Clock: The platform includes a time clock solution featuring IP verification (preventing clock-ins from outside the store), break attestations, and early punch prevention.

Employee Flexibility: Through the web app (and upcoming native app), employees can view their schedules, punch in/out, and perform shift swaps directly from their mobile devices.

Rapid Implementation: Shiftlab can go live for a new account in as little as two weeks, depending on how quickly the client can provide their data feeds.

 

Impacting business metrics

Implementing Shiftlab can yield significant financial and operational improvements for retail organizations, according to Ryan Estab's interview:

Increased Profitability: Companies typically see an 18% lift in profit per hour.

Gross Profit Growth: One notable use case achieved a $7 lift in gross profit per employee per hour within just 30 days of implementation.

Reduced Labor Downtime: There is a typical 6% reduction in employee downtime, ensuring staff are active and productive rather than just "standing around".

Enhanced Customer Experience: Organizations often see a 15% improvement in the guest experience, as proper staffing levels lead to reduced wait times and more attentive service.

Forecasting Accuracy: The platform's predictive algorithms can forecast business needs with over 97% accuracy, allowing for highly precise labor optimization.

 

 

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