We connect to the source
Vendor warehouses, secure file drops and direct database links, kept running every night across five POS platforms.
For furniture retailers, by a furniture retailer
Nightly reports in your inbox with an AI read on what they mean. Hourly updates from the floor on your phone. Score Cards, reorder lists and price tags that build themselves. Your team stops chasing numbers and starts using them.
Sales
Margin $
Margin %
Average Sale
Traffic
Success %
Intraday Report Complete
nowResults as of 2:05 PM. $24,650 so far, 12% ahead of goal.
200+
storefronts supported
$1B+
in retail sales represented
5
POS platforms connected
2009
when the first tool was built, inside a working store
Retailers using Tools2Win include Scholet Furniture, Kloss Furniture, Coconis Furniture, Montgomery’s Furniture, Miller Waldrop Furniture & Decor, Old Brick Furniture, Indian River Furniture, Michael Alan Furniture & Design.
Let’s talk about AI
Everyone’s asking whether AI can just handle this now. We use it every day, and it can’t. Hand it your POS data and you’ll get a fast, confident answer. Whether that answer is right depends on things it has no way of knowing.
The confident answer
Average the two stores
35%
Store A closes 50%. Store B closes 20%. Average the two and you get 35%, no matter how many people walked in.
The right answer
Count the actual ups. Drag them.
21.4%
We define each rate once, then rebuild it from its parts, every time.
A good AI can avoid any one of these once you tell it to. But you’d have to know to tell it, every time, for every question, across everyone on your team.
Vendor warehouses, secure file drops and direct database links, kept running every night across five POS platforms.
What counts as protection, which buildings count as stock, which orders count as clearance. At last count, 100 client-specific rules across 50 retailers.
Ups, written business, nailed vs. available, same-weekday comparisons. It’s built into the numbers, so nobody has to explain it in a prompt.
A chatbot can write you a re-tagging plan. We produce the tags, keep your website current and send protection registrations to the provider.
People who know furniture retail train your team and help you decide what to do next. When a number looks wrong, it’s our problem to chase.
So we put AI where it’s actually useful
AI analysis on your nightly reports. Your reports arrive with a plain-English read in the email: what’s working, what isn’t, and what to do this week. It works from your report’s numbers and furniture rules, like not judging a clearance center against a retail store. Each one is labeled as AI, because it can make mistakes.
A personal note for each salesperson. Where it’s turned on, each one gets a note written to them, measured against the company’s numbers.
Luma, your AI analyst. Ask in plain English and get charts, tables, dashboards and PDFs from one set of governed definitions. It’s instructed to state only numbers its queries return, and to tell you when the data can’t answer.
Or bring your own. The Data Studio connector lets Claude, ChatGPT, Gemini or Grok read your Tools2Win data: same definitions, your company only, read-only.
Luma and the connector are available to account admins today.
Sales Report Daily: Wednesday
Sample dataFrom Tools2Win Reports, delivered overnight
AI Generated Analysis
WatchMonth to date you’re 6% ahead of last year, but margin has slipped 1.1 points, and most of that is Motion at Northside. Discounting on recliners is the biggest single driver.
AI-generated insights may contain errors or omissions. Check them against the attached report.
A day with Tools2Win
Drag through a normal Tuesday and see what shows up, without anyone pulling a report.
11:05 AM
Hourly updates show each store against its goal, with margin, traffic and close rate where you have them. You can be across town, or at Market, and still know.
Intraday Report Complete
Results as of 11:05 AM
This hour: $4,310, 3 tickets
Downtown
+12%$7,450
Goal $6,650 · Margin 47.2%
Northside
−21%$2,180
Goal $2,760 · Margin 44.8%
Clearance Center
+4%$1,640
Goal $1,580 · Margin 38.1%
Sample screens, with invented stores, people and figures. Times are examples. Intraday updates depend on what your POS can provide, and AI analysis and tools are set per company.
The Score Card
Week to date, month to date and year to date, by store and by category, compared on the same weekdays as last year. Gold beats goal. Green beats last year. Red means look here first.
| % vs last year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct |
|---|---|---|---|---|---|---|---|---|---|---|
| Sales | +3 | −2 | +5 | +8 | +7 | +1 | −3 | +4 | +9 | +11 |
| Margin $ | +2 | −1 | +7 | +9 | +5 | +2 | −4 | +6 | +10 | +12 |
| Traffic | −4 | −6 | −1 | +1 | +3 | −2 | −5 | −1 | +2 | +3 |
| Success rate | +4 | +2 | +3 | +6 | +2 | +1 | +1 | +3 | +5 | +6 |
| Average sale | +3 | +2 | +3 | +2 | +3 | +2 | +1 | +2 | +3 | +2 |
| Protection | +6 | +1 | −2 | +4 | +7 | +8 | +3 | −1 | +6 | +9 |
Traffic × Close rate × Average sale
The Score Card tracks each part, so you know which lever to pull. Move them on a sample store and see what it’s worth.
Margin dollars vs. the sample store today
+$69,120
a year, on $4,464,000 in sales.
Arithmetic on a made-up store (8,000 guests, 30% close, $1,800 average sale, 48% margin), not a forecast. The right levers for you are what the Score Card is there to show.
One platform, every seat
Share change (points)
Share of Sales by Year
Vendor Sales by Year
Margin % of Sales by Year
And there’s a lot more
Everything we offer exists because a retailer needed it. Pick a part of your business and see the questions you’d be able to answer.
We’ll set you up around your POS, your stores and the problems you actually have. Talk it through with us
Run your own numbers
Change the numbers to match your stores. Switch off anything you’ve already solved.
Estimated labor you could redeploy
$63,840
a year. That’s 190 hours a month, or about 1.2 full-time people.
This is time, and it only becomes money if you put it to work. Hour figures are Tools2Win’s estimates, and the price-tag figure assumes a 40,000 sq ft showroom. Ordering assumes Auto Order saves up to 75% of routine time. Yours will differ. This doesn’t include software cost or any margin or sales gain.
Our story
Most retail software is built by people who have read about your business. Ours started inside a furniture store, with an owner’s own money on the line. It still shows in what we build and what we ask you on the first call.
Jamie Winter grows up in a family furniture business in Emporia, Kansas, then leaves for engineering at Motorola and builds a factory in China from scratch to 1,300 people and $500M in sales.
Jamie comes home and puts life savings into the family business, now growing in Topeka. There’s no data to run it on and no way to know if the investment will pay.
So Jamie pulls the data out of the POS and builds the tools the store needs. An auto-order tool cuts ordering time by a factor of ten. Market tools show which categories and vendors to grow or shrink.
Other retailers in Jamie’s performance group ask for the same tools. A formal program launches with the Furniture First buying group, and a small engineering team forms.
Tools2Win supports more than 200 storefronts, inside and outside Furniture First. And it’s still built by people who know what a Saturday on the floor looks like.
From the people running the stores
“We have a trackable return of nearly $200,000 annually”
“biggest, most important tool and success driver … in my 40-year career”
“you are leaving time and money on the table”
“not many investments that can buy back my time”
“Our entire team lives and breathes with this program.”
“I don’t have to run any reports! How easy is that?”
“a best-selling occasional table set … we didn’t show at our other location”
Retailers’ results, in their own words. Yours depend on your business and on what you do with the data. Read the full testimonials
Straight talk
You can, and for some things you should. But your AI only knows what you hand it. It won’t pull clean data from your POS every night, apply your company’s rules, catch a broken feed, re-tag your floor or pick up the phone. That’s the part we do. Then you can point your AI at the result.
No, and neither is anyone else’s. It’s why our AI analysis is labeled as AI, sits next to the report it came from, and tells you to check it. Use it as a sharp assistant who read everything overnight, and let your judgment make the call.
No. We work on top of it. Today that’s STORIS, Profit Systems, Myriad, FurnServe and TylerNet. On something else? Ask us before you assume either way.
Yes. Nightly and weekly reports arrive as Excel and PDF, and the client portal puts the same kind of view in your browser. Use whichever fits how you work.
We can’t promise that, and you should be wary of anyone who does. We can show you where the money is and take the busywork off your team. Clients have reported better margin, less unproductive inventory and real labor savings, but they’re the ones who acted on what they saw.
Reports refresh nightly, so you start the day with yesterday’s full picture. Hourly updates come from POS systems that can provide them. It isn’t a live feed of every ticket, and we won’t tell you it is.
No. It builds the order sheet, one tab per vendor, and your buyer stays in charge of what actually goes out.
Not yet. Luma is available to account admins today. AI analysis on reports is set up per company.
No. Each company’s data is kept separate, and access inside your company is set by user and by permission.
Both depend on your POS, your store count and which tools you want. We’d rather give you a real answer than a brochure answer, so we’ll cover both on the first call.
Yes, home furnishings is what we know. Being this specific is why the tools work the way your store does. If you sell something else, we’re probably not your people.
Tell us what you can’t see in your business today. We’ll tell you honestly whether we can help.