Eight years ago, newlyweds Colby and McKenzie Bauer showed up at a farmers market in Hawaii to gauge demand for their offhand invention: an elastic wallet. The product’s super-slim profile raised eyebrows among adventure-seekers as a convenient way to carry essentials.
The duo printed the wallets with colorful patterns, started a Kickstarter campaign and later launched a direct-to-consumer ecommerce site. Today, Thread is a national business that will see more than $15 million in revenue this year. It’s now moving beyond its signature wallet into lanyards, bags and other accessories that let individualists approach the everyday with style.
Get an overview of Thread's company story:
New Sales Channels Require a New Business System
Thread expanded beyond D2C into wholesale in 2020, overcoming pandemic-related obstacles to build a channel that now represents about 25% of sales. It also launched some of its own retail locations in the form of custom-built, uniquely branded mall kiosks. These initiatives contributed to revenue growth of more than 1,000% over a three-year span, earning Thread a spot on the Inc. 5000 list of fastest-growing private companies in 2020 and 2021.
With these new initiatives, Thread needed to refine its demand forecasting by getting all data from each sales channel into one easily accessible system – with the ability to segment that data, said COO Mitch Sanders. Thread wanted to stay on the cutting edge, and its mix of QuickBooks and Finale Inventory wouldn’t keep it there.
Sanders turned to NetSuite as a known “leader in the space.” He had been attending product demos for years and “knew that was the route Thread wanted to go” for its ERP system.
A Reliable Data Warehouse
Shortly after implementing NetSuite ERP(opens in new tab), Thread also replaced its business intelligence software, Grow. The software had proved incapable of pulling in Thread’s data from multiple Shopify instances, Google Analytics, Google Ads and other sources.
“The complexity led to some breakdowns in data integrity,” Sanders said. “We were trying to do calculations off of incomplete data.”
Thread needed a solution where it could pipe in data without complications. It chose NetSuite Analytics Warehouse(opens in new tab), a prebuilt data warehouse and business intelligence solution built specifically for NetSuite transaction data.
After an easy implementation with NetSuite partner Myers-Holum, Thread now uses the solution’s prebuilt data pipelines to combine data from NetSuite, Shopify and Google Sheets, which it uses for forecasting. Gone are the days of troubleshooting faulty integrations and questioning data accuracy.
NetSuite Analytics Warehouse is more reliable than Thread’s previous BI solution, Sanders said.
“We know that if our data is [inputted] in NetSuite correctly, it's going to be reflected in the data warehouse correctly,” he said. Plus, "I was surprised how easily we could manipulate the data flows to what we needed, then augment the data with multiple sources."
COO Mitch Sanders shares about Thread's experience with NetSuite Analytics Warehouse:
Demand Forecasting Gets Granular
Thread now uses NetSuite Analytics Warehouse’s machine learning capabilities when forecasting demand. The system’s algorithms analyze past sales data, picking up on seasonal trends the team might not notice on its own.
For example, it’s easy for teams to conclude that demand spikes during summer and the holiday season, Sanders said. But identifying trends on a product level per season is harder: How much do sales of bifold wallets spike on Black Friday in the D2C channel, specifically? And do bifold wallets see the same Black Friday spike as crossbody bags? In the data warehouse, machine learning analyzes years’ worth of Thread’s Shopify and NetSuite data to forecast with this level of granularity.
Then, Sanders gathers qualitative insights from his sales channel heads. Perhaps crossbody bags are en vogue right now and demand is shifting, which will likely push sales above the data warehouse’s forecasted number.
Using both these machine and human inputs, Thread places product orders for the upcoming season. As a result, it more often orders the right amount of product – not so much that cash flow slows and not so little that stockouts become a risk.
Addressing Shortfalls With Action Plans
Even better than more accurately forecasting demand, Thread can now confidently create action plans when it inevitably misses those forecasts, Sanders said.
For example, inflation and general economic uncertainty mean that many businesses have ordered too much product in recent months, he added. With the data warehouse, Thread has a leg up in solving the problem:
“I can see, down to the unit number [by sales channel], how many more AirPod cases we need to sell in order to reach our forecast,” Sanders said. And “I can show my teams exactly how much money we have tied up in those units of excess inventory.”
Thread might then decide to change up its marketing campaigns or run a sale – armed with a clear picture of which product it needs to move, in which sales channel, and at what volume.
“NetSuite Analytics Warehouse has helped us get closer to perfection,” Sanders said. “I mean, we're never going to get to perfection. But when we fall short, it's showing us how to deal with that.”
Insights Delivered Across Departments
In the past, similar inventory insights lived in a spreadsheet on Sanders’s desktop. The sales or finance teams might not know the particulars of the excess stock problem, for example, until he relayed the info. Now, those teams simply log in to NetSuite Analytics Warehouse and view those insights for themselves – removing pressure from Sanders and his team.
Other departments use the data warehouse in their everyday work, too. Marketing, for example, looks at the same inventory data as sales to align its efforts with forecasts: If the team runs a promotion on flower-print wrist lanyards in June, will it have enough product on hand to meet forecasted demand in July?
“Nothing makes me happier than going to our marketing and creative teams and seeing their dashboards open,” Sanders said. “These are people that previously didn’t look at the data all that much. But now, because we provided it to them in an easily digestible way, they log in and see what's going on.”
External Sales Force Gets in the Data Game
Thread also uses NetSuite Analytics Warehouse when working with its network of external sales reps. A wholesale sales dashboard combines NetSuite and Google Sheets data to compare forecasted sales versus net sales per individual rep, for example.
Thread’s sales manager checks in with reps who are in jeopardy of missing their monthly numbers. The ensuing conversations have sparked strategy switchups: Maybe a rep is missing her goal with a major retailer and suggests that installing window displays would help. Equipped with data, Thread’s marketing team might seriously consider that option, Sanders said.
Expansion and Analysis Ahead
Thread will continue to expand its brand and product line from simply wallets into “all things carry,” debuting its fourth bag design later this year. Working with bigger-name retailers in its wholesale channel will fuel brand awareness, as will continued work on its own branded retail locations.
Behind the scenes, Thread is planning to bring Google Analytics data into the data warehouse so its ecommerce team can further analyze website metrics related to sessions, traffic and conversion rates.
Sanders sees endless applications of NetSuite Analytics Warehouse at Thread. Ideas include piping in weather-related data and analyzing it alongside performance of Thread’s mall kiosks, some of which are outdoor. All it would take is some creative work with the NetSuite team.
“We've had a lot of ideas,” he said. “And I feel confident that we can find ways to do whatever we want in NetSuite Analytics Warehouse.”