The Catalog Is Not a Brochure, It Is Your Highest-Potential Sales Channel

If you publish product catalogs, you are already running a sales channel. The question is whether you are measuring it and whether the companies you compete with are measuring it better than you are.

Here is what the data shows. Between October 2024 and May 2026, enterprise customers using Flipsnack’s platform generated 12,089 orders directly from digital catalogs across 961 flipbooks. 

The workspaces generating the most orders shared three characteristics: they published frequently, they gave buyers a direct path from browsing to ordering, and they measured what happened after the digital catalog went out,  then used what they learned to make the next one perform better.

Five companies transitioned from static PDF catalogs to automated, shoppable digital ones, where they achieve: 

• A hardware distributor who once built every catalog page by hand is now running dozens of auto-generated catalogs and tracking over €500,000 in orders directly attributed to them
• A 5-person wholesale importer that spent months every year rebuilding the same catalog in InDesign is now generating over €74,000 in revenue from a catalog that updates itself
• A science education supplier with a tiny product range generating over 300 orders, the highest order-to-product ratio in the entire dataset,  because they removed every step between browsing and buying
• A craft and hobby supplier managing 70,000 SKUs that replaced 50+ manually built Photoshop catalogs with an automated program connected directly to their ERP
• A pan-European distributor operating across 20 countries that built a catalog program from scratch, 32 auto-generated catalogs across 20 brands, and zero manual work.

These are not outliers selected to tell a flattering story. They are documented cases, grounded in platform data and customer conversations, chosen because they represent different industries, different company sizes, and different starting points, and because they arrived at the same conclusion through different paths.

The data in this report is drawn from 120 enterprise workspaces on the Flipsnack platform, documented customer conversations, and order tracking data between October 2024 and May 2026.

Why most catalog programs underperform. The problem has three layers. 

Ask a marketing or sales operations leader how long it takes to produce a product catalog, and you will usually hear a number between four and eight weeks. Ask them how many orders the catalog directly generated, and the conversation stalls.

That gap, between what goes into making the catalog and what comes back out of it, is the defining inefficiency of product marketing in retail, distribution, and consumer goods. It has been accepted as the cost of doing business for so long that most teams have stopped questioning it.

The problem has three layers.

The first is production: creating a catalog is expensive and slow. Every update requires a designer. And before any automation can even start, someone has to design the page layout that products will populate into the template barrier that companies rarely mention but always hit first.

The second is distribution: a static PDF tells you nothing. Who opened it, how long they spent on it, which products they looked at, and where they dropped off, none of it is visible.

The third, and most consequential, is attribution: without a direct connection between catalog content and buyer action, you cannot improve either. You are optimizing blindly.

All three layers interact. Because production is slow, companies publish infrequently. Because they publish infrequently, they treat the catalog as a fixed deliverable rather than a tool. Because it is a fixed deliverable, no one builds the measurement infrastructure that would tell them whether it is working. 

The catalog becomes invisible to the business, not because it is performing poorly, but because there is no way to know.

This is not a niche problem. It is the default state of catalog programs in most industries. The companies in this report matter precisely because they show what changes when you solve all three layers at once.

What the catalog data shows from Flipsnack

Across 120 enterprise workspaces in the Flipsnack platform, the difference between automated and manual catalog production is measurable and consistent. 

The figures below are based on documented customer workflows,  what these companies described before automation, and what they reported after using Flipsnack.

Metric	Manual production	Automation
Catalog delivery speed	6 weeks on average	1 week
Typical production cycle	4–8 weeks per catalog	1–5 days per catalog
Design requirement	Designer needed for every update	Product data updates automatically
Catalogs published per workspace per year	3–4	12–16
Post-distribution visibility	None	Views, clicks, scroll depth, time-on-page
Revenue attribution	Impossible	Orders tracked per catalog, per page

Customers report an average production time of 6 weeks per catalog before using automation in Flipsnack,  the midpoint of the 4–8 week range documented across the five companies in this report. After automation, the same catalog delivers in under a week. That is a 6× faster delivery, which compounds directly into cost savings, faster time-to-market, and more catalogs published per year.

The longer you run it, the more it compounds

This is the part most catalog programs never reach, because they stop at publishing and never look at what happens next.

The most striking pattern in this dataset is not what happens when a company switches to digital catalogs. It is what happens in the months after, as they publish more, measure more, and iterate.

The top-performing workspace generated 2,437 orders from 13 catalogs, an average of 187 orders per catalog. The second highest published 53 catalogs in a single year and generated 1,257 orders. The third ran 14 catalogs and generated 1,003 orders. These are not companies that got lucky in year one. They are companies that kept removing barriers,  more editions, more customer segments, more versions, and watched order volume follow every time.

The pattern is consistent across all three: every time a team publishes more frequently, orders go up. Not because the catalog got prettier. Because it was in front of more buyers, more often, with a direct path to ordering.

If you are already publishing catalogs, the question is not whether to start. It is how much you are leaving on the table by publishing four times a year instead of forty.

Why do some catalog programs generate 10× more orders than others

The top-performing workspaces don’t have bigger catalogs or bigger budgets. They do three things differently.

They publish frequently — not one catalog a year, but 13 to 53 per workspace. New collection dropped? New catalog. Seasonal pricing? New version. Specific customer segment? Their own edition. This is only possible because production takes hours, not weeks.

They make their catalogs shoppable. Buyers add products to a cart and submit an order directly in the catalog. No email to follow up. No website to navigate to. The catalog is the checkout.

They check what’s working. Which pages get the most time? Which products get added to wishlists but not ordered? They use that to improve the next version. The catalog gets smarter over time.

The footnote worth adding: none of the top performers are large companies. Cose Nuove has 5 employees. A science education supplier in this dataset has just 28 products. The gap between them and lower-performing workspaces isn’t budget; it’s how systematically they use the catalog as a sales tool.

Five cases: From static documents to revenue channels

Case 1: Ferretera Kimura — 10,000 products. One person. No way to keep up.

Before: “It’s a waste of time — we are making one by one item. I did it by myself. It was horrible.” — Harumi Shibata, Designer

Ferretera Kimura is a hardware and tools distributor based in Latin America, supplying retail shops with everything from power tools to fasteners across thousands of product lines. Not a household name, but exactly the kind of mid-sized distributor that lives or dies by how efficiently it gets its offer in front of buyers.

Harumi had built a 181-page hardware catalog manually, product by product, image by image. With more than 10,000 SKUs and no automated connection between the product database and the catalog, every update required reopening the design file. Every price change meant human intervention. The catalog aged the moment it was published. Performance measurement: none. It was a PDF. There was no mechanism to know whether buyers opened it or whether it contributed to any sale.

After: Before the automation could run, Harumi shared her existing 181-page catalog with the Flipsnack design team. They used it as the brief and built her a custom template in one week. One template, built once. After that, upload a feed, pick the template, and the catalog generator feature did the rest.

Ferretera Kimura now operates 48 auto-generated catalogs covering 3,957 SKUs across product families. When something changes, a price, a product, a range,  they sync the feed. No designer. No file to reopen. No pages to rebuild. Each catalog is shoppable: buyers select products and submit orders directly without leaving it.

Result: €502,374 in orders tracked directly through the catalog orders.

Weeks of work. Now seconds. She went from maintaining one catalog to running 48. The time that used to go into production now goes into sales.

Case 2: Castelltort — 43 salespeople. 70,000 SKUs. One massive Photoshop problem.

Before: “We are making a huge transformation — moving 50 catalogs, all these references in Photoshop and design — it’s a lot of massive, massive work.” — Mireia Rosas

Castelltort is a craft and hobby supply company based in Spain, selling ribbons, lace, zippers, threads, and buttons to retailers and makers across Europe. With over 70,000 SKUs across dozens of product families and a network of 43 salespeople on the road, their catalog is not a marketing tool; it is the backbone of how their entire sales operation runs.

Each of Castelltort’s catalogs was built individually from scratch in design tools. Templates could not be reused systematically. Salespeople carried physical sample books on customer visits. There was no shopping functionality, no engagement measurement, and no mechanism to connect catalog activity to orders.

The company knew exactly what it needed from Flipsnack:

The shopping list is very important. We can send it back via email or through an API to someone else. This is the whole process we were looking for.”

After: Before a single catalog could be generated, Castelltort invested in 9 custom templates, each designed specifically for a different product family: ribbons, lace, zippers, threads, buttons. That upfront investment is the foundation on which everything else runs.

Their setup is the most technically complex in this dataset: 5 price tiers generating 5 distinct catalog versions per product release, private access controls per customer group, and an API integration with their IBM AS/400 system, connecting shopping list submissions from Flipsnack directly into their ERP. Their 43 salespeople now use tablets in retail shop visits: the customer browses on one device while the sales representative processes the order on another, with both feeds converging in IBM.

Result: 39 automated catalogs, 97 orders, €7,520 in tracked revenue, an early-stage figure from a deployment still being finalized. The infrastructure is built for a program operating at the full scale of 70,000 SKUs.

How Flipsnack connects Castelltort’s ERP to every order from the catalog

Case 3: Cose Nuove — Five people. One catalog. Rebuilt every two weeks.

Before: “I spend a good amount of time — January, February, March — getting the print catalog ready. InDesign. Lots of room for human error. It’s a bit too cumbersome. There’s too much duplicative work.” — Brian Thoes, Owner

Cose Nuove is a 5-person wholesale distributor in Minnesota importing Scandinavian home goods, Hinza, Klippan, Pappelina, Bengt & Lotta, for 700–800 US retailers. Their 1,500-SKU catalog changed constantly. Prices shifted every couple of weeks. Each time, the entire PDF had to be re-uploaded, and because the shoppable product data lived separately from the visual file, each update meant rebuilding both. The catalog was effectively being rebuilt twice with every update.

Brian knew what he wanted: “The shoppable feature of being able to adjust one price without having to re-upload three times, that’s what drew me to it.”

After: One feed, one sync, orders collected in Flipsnack

Cose Nuove moved from PDF uploads to Catalog Generator with a direct product data feed.

Price updates that previously required re-uploading the entire catalog now require a single sync. The product data,  including minimum order quantities (a feature the team specifically requested and Flipsnack subsequently built), flows through automatically.

Shopping list functionality is now live in the catalog. Customers browse the 1,500-SKU range, click products, and submit orders directly through Flipsnack. The order goes to a pre-configured inbox, and for companies like Cose Nuove with regional sales structures, conditional inboxing allows orders to be routed to the correct team automatically.

Price updates now require a single sync. The product data, including minimum order quantities, a feature specifically requested by Brian and subsequently built, flows through automatically. Customers browse, select, and submit orders directly in the catalog.

Result: 69 orders and €74,550 in tracked revenue from a 5-person team, using a digital-only catalog program that replaced their previous print and PDF workflow entirely.

Case 4: Orbico — A B2B platform with manual Excel exports and no catalog infrastructure

Orbico Group is one of Europe’s largest distributors, operating across 20 countries with more than 7,500 employees. For their Bulgarian B2B e-commerce platform,  a trade-only store carrying 4,000–5,000 products across 19 brands, there was no catalog program at all. 

Before: Products existed on the platform. There was no structured mechanism for presenting them to buyers in a catalog format.

The planned workflow, described by Ralitsa Antonova (E-Merchandising Specialist), required exporting product data per brand, routing Excel files to brand managers for approval across 19–20 brands organized into 5 divisions, and preparing finalized files for catalog generation. In a regulated industry where catalog accuracy carries compliance implications, not just commercial ones, the case for a structured, repeatable process is different in character from the efficiency arguments that apply in retail.

After: Orbico now operates 32 auto-generated catalogs organized into 5 division bookshelves: pharma, MC, Procter & Gamble, and others each accessible via a single link for internal and customer-facing use. Updates are managed through Google Sheets synchronization: Ralitsa edits the sheet and clicks synchronize; the catalog updates without re-importing the feed. Monthly cadence, across 19–20 brands, with no manual page editing.

The adoption pattern is notable: 32 catalogs, all auto-generated, zero manual. In a complex, multi-brand, pan-European distribution environment, a catalog program of this scale and update frequency would not be operationally viable through manual production.

Orbico’s catalogs are currently presentation-only; shopping functionality is the next planned phase. The revenue story is still ahead of them. But the infrastructure of reliable, repeatable, brand-controlled catalog generation at scale is in place.

Case 5: A science education supplier — Every order used to need a phone call. Not anymore.

This supplier provides science lab kits and curriculum to higher education institutions. Their buyers — school purchasing managers and science department leads — were not discovering unknown products. They knew what they wanted. They needed a path to order it.

Before: The previous catalog was static. It presented products. It did not capture orders. Between browsing and buying, there was a gap that required a sales conversation to bridge.

After: With a shoppable catalog, the purchase decision and the order submission happen in the same experience. A purchasing manager selects products, specifies quantities, and submits an order request directly — without navigating to a separate system or waiting for a sales representative.

Their marketing team described the logic: “We treat it like a binder of everything we offer from every discipline and every lab lesson. We let people add to the list, which is really adding to a cart. It helps the sales team build a quote and have a better conversation.”

Result: 371 orders from 28 SKUs — the highest order-to-product ratio in this dataset.

Catalog conversion is not a function of catalog size. It is a function of how precisely the catalog is designed to move a buyer from interest to decision. These buyers were not browsing. They were looking for a frictionless path to ordering products they had already decided to buy. The catalog provided it.

Five patterns behind the highest-performing product catalogs

Finding 1: The measurement gap is universal

Across all five companies, the answer to “how did you measure catalog performance before?” was effectively the same: we didn’t. Not because these are unsophisticated organizations,  Orbico operates across 20 countries, Castelltort manages 70,000 SKUs, and Ferretera Kimura handles 10,000+ products. They lacked measurement because their previous tools had no measurement layer. The gap was structural, not intentional. A static PDF produces no data. There was nothing to measure.

Finding 2: Production friction is the real bottleneck

Cose Nuove was re-uploading the same catalog every two weeks. Ferretera Kimura was entering products one by one. Castelltort had built 50+ manual catalogs. The common thread is not industry or company size; it is the relationship between production effort and publication frequency. When production is expensive, companies publish infrequently. When production becomes cheap, publication frequency becomes a competitive variable.

Finding 3: Shopping functionality changes the category of the tool

A catalog without ordering capability is a presentation tool. A catalog with ordering capability is a sales channel. For Cose Nuove, the shoppable feature was the primary motivation for upgrading. For Castelltort, the shopping list with IBM integration is the core of their commercial architecture. For the science education supplier, the in-catalog ordering experience explains 371 orders from 28 products. This is not an add-on feature; it is what makes the catalog a revenue asset.

Finding 4: Automation makes possible programs that were previously infeasible

Orbico’s 19–20 brand catalogs, organized into 5 division bookshelves, are updated monthly across a 4,000–5,000 product range. This program does not exist in a manual production environment. Castelltort’s 5-tier pricing system generating 5 catalog versions per product release, does not exist manually at 70,000 SKUs. In these cases, automation does not improve an existing catalog program. It makes possible a catalog program that was previously not feasible.

Finding 5: The revenue leaders in this dataset are not the largest companies

Ferretera Kimura is a regional distributor, not a multinational. Cose Nuove has 5 employees. Science Interactive has 28 products. The companies generating the most from their catalogs are not defined by size or budget. The clarity of their commercial intent defines them: they built their catalog programs around buyer behavior and order generation, not around production output.

The engagement layer of a digital catalog

The 12,089 orders in this dataset represent the most visible output of digital catalog programs. They are not the most strategically valuable ones.

The more durable advantage of digital catalogs is the engagement intelligence they generate, data that informs not just which products sell, but how buyers move through a catalog before they decide. For catalog programs on Flipsnack’s platform, this includes page views per session, scroll depth, link and button clicks, wishlist adds, time spent per page, and return visits.

This data transforms the catalog from a static document into a behavioral dataset. Teams can identify which product placements drive clicks, which page layouts retain readers, and at what point in the catalog engagement drops off. The next catalog version is informed by evidence, not instinct.

The quantitative engagement benchmarks across industries, average session depth, click-through rates by product category, and wishlist-to-order conversion rates are the next layer of this research. As documented in the five cases above, there was no “before” measurement to compare against, because a static PDF produces none. The measurement gap is closing. The benchmarks are being established now.

The one catalog decision that changes everything

Five companies. Different industries, different sizes, different problems. One decision: stop treating the catalog as something you produce and start treating it as something you sell through.

The outcome was the same across all five. The catalog became measurable. Orders became traceable. And the friction between a buyer’s interest and a purchase disappeared.

The companies generating the most from their catalogs are not the ones that published the most pages. They are the ones who removed the most friction between a buyer’s interest and an order.