What metrics to track if you’re a printing on demand company

Print-on-demand (POD) is not “just e-commerce.” It is e-commerce plus manufacturing plus logistics, with one extra trap: customers supply the raw asse, and you inherit the consequences.

Your KPI stack should reflect that reality. If you only track marketing metrics, you will miss why refunds happen. If you only track production metrics, you will miss why demand is expensive.

Below is a metric set for POD, with formulas, measurement cadence, and a few practical interventions.

How to choose metrics without drowning in dashboards

Good POD metrics share four traits:

1. They map to a decision. If the metric moves, you know what lever to pull.
2. They are ratios, not totals. Totals hide changes in quality, mix, and volume.
3. They can be read weekly, and some daily. Quarterly is for accounting, not operations.
4. They are defined once. Same formula, same data source, same owner.
5. Every core metric should be split by product category, traffic source, and supplier/fulfillment route. The “average” hides where the money is leaking.
   

POD is the one in the e-commerce field. So choosing the metrics for your own need you will consider customer, marketing and product sides - the holy trinity of every e-commerce business.

Metrics you should stop treating as “KPIs”

There are some metrics that aren’t as important as they look. These are so-called Vanity metrics.

You may count how many times people signed in to use your service, how many subscribers or page views but what else these numbers can give the deal is to keep them as your leads. You may have a good “downloads” rate or total usage of service, but does it really show is your product valuable?

BTW, so popular ‘Bounce’ metric is totally Vanity metric! For what sake do you need to know on what page people jump over to another website? It just means or your product is bad or your website is bad. If you don’t have any information what they exactly did on your website, but to track on what page they left, it's a waste of time.

The same story with Number of unique visitors.
It shows only how many people saw your website or your content. But what’s wrong? It tells you NOTHING about how their journey feels. Why these people left? Why they stuck around? How many of them actually did a purchase?

Total metrics are bad.

Just simply bad.
Why do you need to know how much e-mails have you sent totally since the very beginning?

What’s the point to count the total amount of your app downloads or total orders since the first day you launched?
To know the amounts is good in a limited period of time because you will see the dynamics. But to count it globally...very useless.

Lagging metrics

Lagging metric is a bad metric to follow. Why?
They are measured in big amounts of time. If you face a problem right now or want to deal with something in the nearest future, annual or quarter metrics are too big.
Better to portion them into a monthly or weekly or even daily measurement.

Average number metrics

Another lovely and meaningless metric. It would be useful if you make a research in a tiny segment or in a specific field. In other cases, John has 10 apples and Jack has 1. In average they have 5. Brilliant metric!

The core POD metrics that deserve a dashboard tile

Some good metrics are:

• Always a ratio or a rate. This is a constant. You will for sure know what you need to change to improve other metrics because of the dependence on one another.
• Leading because it simply predicts what’s going to happen.
• Understandable. In your company will always be a private and individual metric you follow.

And usually it’s called somehow strange and looks like a cypher from aliens.
Just make sure you and your colleagues understand what it means.

So what metrics exactly to follow?

Conversion rate

Conversion Rate is a simple quotation, how much people who visit your website actually make an order. The logic is easy. It shows how much revenue you visitors bring you on average.
By the way, it shows the customer order journey. How many of your customers accomplish the funnel: from landing page to view the products, from viewing the products - to make an order, from making an order - to make the order again?

For POD, conversion rate often drops for non-obvious reasons: low-res previews, unclear print quality expectations, or the customer noticing their design looks blurry on a mockup. If you see conversion rate dipping while traffic stays stable, check whether you also see an increase in “low-quality upload” volume (more on that below).

Value-per-customer

This metric shows the effectiveness of your marketing campaign.
It's calculated easily: the total website revenue is divided by total website visits.

Cost per acquisition

This metric measures by dividing the total cost you spent for conversion by the total number of conversions. In simple terms, it's the amount you pay per your customer according to your marketing efforts.

Return on ad spend (ROAS)

This one is one of the easiest revenue-based metrics to measure. It demonstrates you the amount of revenue you receive of each advertising dollar spent.
Here is vice versa count - the higher number you get the better it is.

Cost of production

If simply - the cost of materials you used and the labor to produce your products. In the POD reality - how much money do you per every item: the price of a garment, print, shipping + the cost for using third side help (Printify, Printful, etc.)

Return of investment (ROI)

POD also requires some money to spend on it but you need to be aware if it worth it or not. One of the main metrics of the whole marketing world. How to calculate?
Benefit of investment is divided by the cost of investment.

Volume produced per week/day/hour

Figure out how efficient and profitable your shop using these metrics.
Why do you need this? Because some days or even hours will be more engaging than others and you can use these numbers in planning your marketing campaign and optimize manufactures.

Top 5 largest customers

This metrics will help to figure who is your main targeting auditory is. Who is your persona that brings you money?

New customer orders vs. returning customer orders

Do you focus on customer acquisition? Or you cherish the old and loyal customers?
This metrics will show you that.
To gain new customers is more expensive than to keep the old one. So, attract and hook the new ones, but keep the old squad engaged as well.

Maybe something specifically for POD?

Metrics for POD are super individual and when you will be more experienced you will select for yourself on what to focus better.
The main metric for every POD business will be the level of satisfaction with your product - quality of garment and print.

But still we have something to recommend for you specifically for POD.

Image quality metrics

Here you will measure the average size of images and dimensions people upload to your website.
According to the image size will the customer be able to make an order? How the image size will influence the quality of the print or the product? Will the customer be satisfied with it?

But “average size” alone won’t help you fix anything. In POD, image issues show up as very specific outcomes: extra manual prepress work, more rejected files, more reprints, and more refunds. So it’s worth tracking image quality as a small set of operational rates, not a single average.

• Low-resolution upload rate: % of uploads below your print threshold (example: below what’s needed for 300 DPI at the chosen print size).
• Auto-fix rate: % of low-res uploads that you automatically improve enough to pass prepress checks.
• Print-quality complaint rate: support tickets mentioning “blurry,” “pixelated,” “low quality,” divided by total orders.
• Reprint rate caused by file issues: % of orders reprinted because the original file was not print-ready.

If low-quality uploads are a consistent source of refunds, support tickets, or manual prepress work, you can treat enhancement as part of your production pipeline. LetsEnhance is an AI image upscaler with six different AI models to handle different input types (photos, digital art, old photos, and more). In POD terms, it helps you convert borderline customer uploads into files that are more likely to print sharply, without forcing your team to manually fix every design.

For printing, many teams aim for 300+ DPI for the final print file. If your customers upload images that cannot support that at the selected size, you either downsize the print area, reject the upload, or upscale it. LetsEnhance can be used to upscale to a higher effective resolution and also has printing presets so teams can standardize outputs instead of guessing settings every time.

Preprocessing metrics

The specific of PODs is creating goods on a scale for shop owners. The customers of these shops want to get their orders ASAP. So, if your preprocess takes too much time, they will just leave!

Lots of refunds are caused because of people detest to wait. So, check how many operations do they do before actually make an order and how much time it takes. Less is more!

Make preprocessing measurable (so you can actually improve it):

• Time to print-ready file: from upload to a production-ready file (minutes).
• Manual touch time per order: how many minutes your team spends per order fixing customer files.
• Prepress backlog: how many orders are waiting for file fixes right now.
• First-pass prepress rate: % of orders that pass checks without manual edits.

If “manual touch time” is high, integrate LetsEnhance at upload or prepress stage to reduce the number of files that require human fixes. Then track whether your first-pass prepress rate goes up and whether your time to print-ready file goes down.

Final thoughts

The fastest way to make POD unprofitable is to optimize one side of the business while ignoring the rest.

• Marketing metrics without quality metrics create refunds.
• Quality metrics without unit economics create “high standards” and no profit.
• “Average” metrics without segmentation create false confidence.

Your dashboard should make it obvious, in one glance, whether you are buying bad demand, producing unreliable outcomes, or accepting files that cannot meet your print promise.

Reduce low-res file problems without adding headcount

If low-quality uploads are costing you time and refunds, try LetsEnhance as an operational fix. New accounts get 10 free credits, so you can test your real customer files and measure impact on preflight pass rate and manual prepress time.

FAQ

What are the most important KPIs for a print-on-demand business?

If you only track one layer, you will optimize the wrong thing. POD needs a mixed KPI set that covers demand, unit economics, and operations. On the demand side, conversion rate, CAC, and ROAS tell you whether traffic is turning into paid orders at an acceptable cost. On the business side, cost of production and ROI tell you whether those orders are actually profitable. On the operational side, refund rate, reprint rate, and delivery or turnaround time show whether your production and fulfillment are reliable enough to support repeat purchases.

What image resolution do I need for print-on-demand products?

Resolution is a relationship between pixel dimensions and the physical print size. “300 DPI” is a common target for sharp prints, but it only matters if the file has enough pixels for the chosen size. A small image can be set to 300 DPI in metadata and still print soft if the pixel count is low. The practical rule is to define print-size requirements per product (poster, hoodie, sticker, canvas), then treat anything below that threshold as a risk that needs intervention: resize the print area, reject the file, or enhance it.

Why do POD customers complain about blurry or pixelated prints?

Most complaints trace back to predictable file issues: not enough pixels for the print area, compression artifacts from social media screenshots, and edge degradation when logos or text are scaled beyond what the original file can support. POD makes this worse because customers upload whatever they have, often without understanding print requirements. If your store lets customers place large prints from low-res files, the failure mode is baked in before production starts.

How do I measure image quality problems in a way that’s actionable?

“Average image size” is not actionable because it hides the tail of bad uploads that drive the work. Instead, tie file quality to outcomes. Track what share of uploads fall below your print threshold, then connect that to what happens next: how many need manual prepress fixes, how many lead to print-quality complaints, and how many end up as refunds or reprints. Once you can quantify the chain from low-res upload to cost, it becomes a real operations problem you can improve, not a vague “customers upload bad images” complaint.

What is prepress in print-on-demand, and why should it be a KPI?

Prepress is the step where artwork is checked and prepared for production. In POD it usually means verifying resolution, dimensions, bleed and safe area, and file formats, then fixing issues if required. Prepress becomes a KPI when it consumes time and creates a queue. If files require manual work, your turnaround slows down and your cost per order climbs. That is why “manual prepress time per order” and “first-pass preflight rate” are two of the most revealing POD metrics you can track.

How can I reduce manual prepress work without hurting conversion?

Most teams start by adding a quality gate at upload. That can be as simple as warning customers when their file is below requirements for the selected product size, and offering safer size defaults. The next step is automation for the gray zone: files that are not ideal but not hopeless. Enhancing those files with AI tools like LetsEnhance reduces manual time and keeps customers from dropping off at the upload stage. The key is to measure the effect, not assume it. If your first-pass rate improves and file-related refunds drop, the automation is doing its job.

Should I reject low-resolution uploads or upscale them?

Upscaling can preserve conversion, but it must be controlled. The practical approach is a policy: reject files that are far below threshold, auto-enhance files that are close enough to recover, and default the print area to a size that matches what the input can support.

What is an AI upscaler in a POD workflow, and what problem does it actually solve?

An AI upscaler like LetsEnhance increases the effective resolution of an image while trying to preserve edges and detail. In POD, that translates into fewer “this print looks blurry” outcomes and fewer manual fixes by the team. It doesn't turn a tiny, heavily compressed image into a perfect studio file, but it can often recover borderline uploads enough to meet print expectations. The operational value is simple: you spend less time fixing files and you ship fewer disappointing prints.