21 Oct Carhartt Wins in Omnichannel with Customer Focus, Location Intelligence

In 1889, Carhartt was founded in Detroit by Hamilton Carhartt with the goal of delivering durable products to railroad engineers. Using direct insight from his consumers, he began manufacturing purpose-built overalls, which would become one of his company’s most iconic styles.

More than 130 years later, the team at Carhartt still works to understand customer needs as intimately as its founder did. The task is more complicated in today’s omnichannel retail environment, but Carhartt is using location analytics and innovative thinking to satisfy a diverse customer base across a range of distribution channels.

Opening the Door to Omnichannel

In an industry with plenty of baggage—including outdated methods of going to market and untested assumptions about consumers—innovative retailers are becoming more data-centric. At Carhartt, a dedicated team of analysts uses location data to inform the company’s omnichannel strategy.

Over the past 15 years alone, Carhartt has redefined its business to accommodate the changing habits of customers. In that same period, the company has manufactured millions of garments—including more than 20 million pieces of product at its facilities in Kentucky and Tennessee—and sold them through online and offline channels, including its own brick-and-mortar stores, wholesale distributors, retail partners, and e-commerce sites.

Seeking innovation and increased brand awareness, Carhartt’s data engineering team first introduced location intelligence—the data-driven output of a geographic information system (GIS)—six years ago to better understand the types of shoppers who gravitate to the brand’s durability, fit, and style.

Today, the Carhartt team uses location data and analytics to assess new markets, understand behaviors across channels, and create a road map for company growth. “GIS lets you see things in a whole new way,” explains Erik Isaak, the company’s principal data engineer. “Salespeople can look at their territory and see all their stores and get data about the things around them. It’s something that you just can’t get out of a text-based report.”

Location Analytics Guides Strategic Decisions

Carhartt’s omnichannel evolution has been a stepwise process marked by thoughtful leadership and a dedication to striking the right balance among channels. When executives decided to expand e-commerce, for instance, the team spent months analyzing how online sales would impact the profits of retail partners that stock Carhartt products, as well as Carhartt’s own 33 store locations.

That exercise exemplified the company’s innovative mind-set. Instead of settling for a standard visualization of sales results, Carhartt used location analytics to go deeper. As the company broadened its reach into omnichannel retail, the data team delivered maps that showed executives not only how products were selling in certain channels, but how one channel’s performance sometimes impacted others’.

First, the team used GIS technology to map all 33 Carhartt stores and any wholesale partners within a 25-mile radius of each location. Then they overlaid purchase data on the map to understand each store’s sales performance and the kinds of customers that shopped those locations. Finally, they layered in online purchase and browsing behavior to understand how e-commerce was influencing customer spending in those areas over time.

Sales operations and analytics manager Steve Sapardanis says the analysis answered a question at the heart of omnichannel retail. “What we wanted to understand [was], were we just shifting dollars from our wholesale partners to our retail location to our online business? Or were we really seeing a shift in a dynamic of shopping behavior?”

The analysis revealed that the company’s online presence was actually elevating Carhartt brand awareness among customers and benefiting wholesale accounts as well—a retail phenomenon known as the halo effect. That information helped wholesale partners see the value of e-commerce expansion.

Location Analytics: A Revolutionary Form of Insight

Sapardanis remembers how impactful the analysis was, and the simplicity of showing sales results on a smart map. “You can literally see the numbers and the color coding that indicates whether it’s up, it’s down, it’s plus, or it’s minus. We had never looked at data and performance in that way at Carhartt before, so it’s been revolutionary.”

The team uses location intelligence and a similarly analytical approach when opening a retail location. “When we go into a market with a store, we want to make a splash,” says Steve Brennan, Carhartt’s vice president of data strategy and analytics. “We also want to make sure that we’re cognizant of the fact that our legacy is through our wholesale partners, so we can’t be myopic with those decisions.”

The team recently performed location analysis on a proposed Carhartt store in Denver, Sapardanis says. “I used the mapping tool to pull in the proposed location and the locations of our wholesale partners and shared the results with the leadership team,” he says. “Quickly, decision-makers saw how close the store would be to two key wholesale accounts. Executives ultimately decided to open the store in a different location in order to preserve a healthy relationship with partners and not oversaturate the proposed market with Carhartt product.”

Accelerating Digital Transformation during a Pandemic

In addition to shaping business strategy and growth, location intelligence has helped Carhartt manage through periods of uncertainty.

When the COVID-19 pandemic took hold earlier this year, the company relied on its crisis management team to guide key decisions. Like many business executives, Carhartt’s leaders sought daily and weekly updates showing the virus’s impacts on the health and safety of employees, sales channels, inventory, store closures, and revenue.

The data engineering team used GIS to visualize the spread of the virus and associated sales patterns. Their smart maps continue to help the team understand how COVID-19 is affecting sales at retail locations and among wholesale partners.

“We are using our real-time, empirical data. When we mapped it, we could see geographically where changes were happening,” Sapardanis explains. “We can look at the point of sale [POS] information each week to understand, Where are the sales continuing and where are they not? Who is staying open and where are the doors closing?”

He says Carhartt’s decision-makers have taken notice. “I can’t tell you how impressed leadership was when they saw the data displayed in that way,” Sapardanis says. “I knew that the tool was a huge win, but that really solidified it and took us to a new level.”

The team also uses GIS to support employee safety—an effort that relies on authoritative, near real-time data.

“We created an app that color-codes each county in the country and explains what stage of the epidemic that county is in—whether it’s under control, spreading, or a full-scale outbreak,” Isaak says. “We took that map and then layered our stores and where our salespeople are on top of that.”

The team hopes that by delivering those smart maps, they will help executives and sales managers make more informed, real-time decisions to protect employee health.

Enabling Intelligent Omnichannel Growth

In times of disruption and growth, Carhartt has come to rely on location analytics to make smart decisions for customers and for the company’s long-term health. But the technology didn’t turn heads immediately.

Dwayne Newsome, manager of data engineering at Carhartt, says colleagues saw the value of location intelligence over time.

“We would get a request from a salesperson asking us to look into retail partner prospects and the demographics of customers in a certain area,” Newsome says. The salesperson might ask what kinds of shoppers frequented particular sales channels, and what the predominant customer persona was in a particular area. “We would give them a set of maps and some data, and then they would take that and use it to talk to the customers. Fast-forward a bit, and every year we got a little more interest.”

Most recently, Carhartt has expanded its GIS use from analyzing current trends to also modeling future outcomes. Newsome calls it a natural extension of the company’s data-focused approach. It helps the team get more from the POS data they’ve gathered from hundreds of different sources including wholesale partners, website, retailers, brick-and-mortar stores, and Amazon. Newsome explains the team’s thinking: “We have all this data. Why don’t we try to model some of this and predict what’s going to happen?”

To perform that exercise, they rely on an advanced form of location analytics that crunches sales data from multiple channels along with information on consumer demographics to predict how a geographic market will perform. It represents the next stage of strategic planning for omnichannel retailers, and leaders like Carhartt are already pushing the boundaries.

Ultimately, Newsome says, location technology has been a unifying force at Carhartt, enabling all business units to work together on a single source of truth.

“I think it helped create a clearer picture,” Newsome says of the location intelligence generated by GIS. Because [the] retail [division] has its own leadership, wholesale has leadership, [e-commerce] has leadership. GIS provided them all with one set of data, displayed visually, so they can see what’s happening and make a better decision.”

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