PenPath

We worked with an ecom brand whose ROAS was dropping significantly, well below their breakeven point.

We’ve all been there. But this customer felt defeated and unsure where to go next.

So, we took a look at the data…

We identified a few critical bottlenecks causing the issue:

The agency they were using wasn’t retargeting on Meta
Their ad spend was spread across too many platforms (given their budget)
Products that performed best for customer acquisition weren’t being promoted
These are just a few of the many things we supported them with. Some may seem obvious, but this is pretty standard—we see even “fancy” agencies miss basic opportunities.

Another big gap? A proper measurement strategy—there wasn’t much of one.

As they started addressing these issues, things began to turn around.

Here’s what helped:

Action: They chipped away at the obvious opportunities

Measurement Strategy: Helped them focus on what mattered

Priorities: The data gave them clarity to make tough decisions

The point is: Having relevant data gives you the ability to step back, analyze, and take action.

If you’re an eCommerce brand and you’ve felt stuck, what did you do to turn things around?

We surveyed ecommerce leaders to understand how they feel about their UTM process and insights. What we found was interesting:

28% of leaders noted they lacked a formal UTM tracking process. They said this is causing challenges such as a lack of clarity when allocating across platforms, audiences, and creative efforts, which slows down ROAS efforts.

Frankly, too many agencies are not following best practices here either. They run generic ads or use too many variables that make it difficult to diagnose or understand.

Recently, a home goods brand came to us with this issue. Their inconsistent UTMs made it challenging to understand performance across Pinterest or Facebook campaigns, and which was most responsible for driving newly found growth.

Simplifying their UTM structure unlocked answers. We started focusing on three basic aspects:

Channel (e.g., utm_source=facebook) → We keep the standard naming that each platform recommends at the source level

Audience Segmentations (e.g., utm_term=30-day-visitors) → We added Ad Group details on who we retargeted at the Term level. We are keeping this example simple for brevity.

Creative Objective (e.g., utm_campaign=giveaway_home-decor_UCG) → Segmenting by hook, product, and creative details

With PenPath's platform and services, they streamlined their UTM process and had all the critical insights with just a couple of clicks. They realized, for example, that targeting returning customers converted 40% better from Pinterest than Facebook with the giveaway promotion content.

This process is simple if you prepare correctly.

We just published a new blog post covering three essential steps to help ecommerce operators get this right. If you need help with UTMs and your process, check it out. We'll leave the link in the comments.

How do you feel about using UTMs to help you identify insights? Are you happy with what you have? Would love to know.

Before launching another campaign, there's one place worth checking first:

The parts of your business already doing better than everything else.

Ecommerce teams are always looking for something new.

A new channel. A new audience. A new offer. A new creative.

But sometimes the easiest growth opportunity is already there.

You just haven't found it yet.

Maybe:

→ One product brings in new customers at a much lower CAC

→ Returning customers convert much better on one channel

→ One creative drives far more purchase intent

→ Mobile traffic is growing, but checkout is holding it back

→ One category has a much higher AOV

These aren't just numbers.

They're clues.

For one brand, cleaning up the UTM structure uncovered something useful: returning customers converted 40% better from Pinterest than Facebook for a giveaway promotion.

That insight can help decide where the next marketing dollar should go.

Before adding something new:

Find the outliers. Understand why they're happening. Then test if you can do more of what already works.

Sometimes the next growth opportunity isn't new at all.

Revenue drops 15%.

Most teams immediately look for ways to bring it back up.

But the first place to look isn't revenue. It's the metric that changed before revenue did.

Maybe traffic started falling two weeks ago. Maybe add-to-cart rate dropped.

Maybe more customers reached checkout but didn't buy.

Maybe one paid channel suddenly started sending less traffic.

This is where working backward helps. Start with:

Revenue ↓

Did orders fall?

If yes, did conversion rate fall?

If conversion rate looks normal, did traffic fall?

If traffic is healthy, move through the buying journey:

Product View → Add to Cart → Checkout → Purchase

Find where the first meaningful change happened.

Sales are a lagging indicator. PenPath uses leading indicators like sessions, purchase intent, cart activity, and conversion rate to help find what changed earlier.

Don't start by fixing the number that changed last.

Find the number that changed first.

Your store has a 3% conversion rate. Sounds pretty healthy.

Until you break down that number. Maybe the real numbers look like this:

Returning customers: 6.2%
New customers: 1.4%

Desktop: 4.8%
Mobile: 1.9%

Branded traffic: 7.1%
Prospecting traffic: 0.9%

Now the 3% average tells a very different story. New customers may be struggling to buy.

Mobile shoppers may be hitting friction. Prospecting traffic may not be finding what it expected.

That's why blended numbers are useful for spotting a change, but not always for explaining it.

Once something looks unusual, segment it. Break performance down by:

→ Customer type
→ Device
→ Channel
→ Campaign
→ Product
→ Funnel stage

PenPath uses the same approach with ROAS because one blended number can hide very different results across TOF, M*F, and BOF.

The average shows the result. The segments show where to look next.

Revenue is up 20%. That sounds like great news. But before celebrating, look at what happened underneath that growth.

Maybe:

→ CAC increased 30%
→ Gross profit margin dropped
→ More sales came from discounts
→ New customer acquisition slowed
→ Returning customers drove most of the increase

The business generated more revenue, but it may have become more expensive to grow.

This is why revenue shouldn't be analyzed alone.

At PenPath, we like looking at the metrics that explain the quality of that growth.

Start with:

Revenue: Are sales growing?

Gross Profit: Is more money actually being made?

CAC: Is acquiring each new customer getting more expensive?

New vs. Returning Customers: Where is the growth coming from?

LTV: Are those customers becoming more valuable over time?

Growth is good.

But profitable, repeatable growth is better.

Don't just ask whether revenue increased. Understand what created that growth and what it cost.

Revenue drops 15%.

Where should the team look first?

That answer shouldn't require opening six platforms and randomly checking 50 metrics.

Build the path before the problem happens.

For example:

Revenue ↓

Did traffic fall?

If yes → Which channel?

If no → Did conversion rate fall?

If CVR fell → Where are customers dropping off?

Then keep drilling down:

→ New or returning customers?
→ Which product?
→ Which channel?
→ Which campaign?
→ Which creative?

Every important KPI should have 2-3 supporting metrics that help diagnose changes.

This diagnostic approach is one of the pillars of PenPath's data-led ecom growth system.

That gives the team a repeatable path from:

Something changed to here's what needs attention.

When performance drops, don't start searching.

Know where to look.

Your best-selling product isn't always your best product for growth.

Sounds weird, but revenue only tells you part of the story.

Let's say Product A generates $500K in sales.

Great.

But then you dig deeper and find:

→ It has your highest customer acquisition cost
→ Most sales happen during promotions
→ Customers rarely come back and buy again
→ Margins are lower than other categories

Meanwhile, Product B only generates $300K.

But it brings in new customers at half the cost, requires fewer discounts, and those customers come back and buy other products.

Which one deserves more attention?

This is why we encourage ecommerce leaders to segment before making decisions.

Look beyond total product revenue. Compare:

• New vs. returning customers
• CAC by product/category
• AOV
• Conversion rate
• Repeat purchases
• Profitability

The goal isn't to find the product making the most money today.

It's to understand which products are actually helping you grow.

Most ecommerce reports answer one question:

“What happened?”

Revenue was $1.2M.

ROAS was 3.4X.

Conversion rate was 2.8%.

Useful information.

But none of those numbers tells the team what to do next.

Try changing the questions.

Instead of:

“What was our ROAS?”

Ask:

“Where can we increase spend without hurting efficiency?”

Instead of:

“What was our conversion rate?”

Ask:

“Where are customers dropping out of the buying journey?”

Instead of:

“Which product generated the most revenue?”

Ask:

“Which products are bringing in profitable new customers?”

That's the difference between reporting and decision-making.

Reports should explain what happened.

Insights should help determine what happens next.

By the time revenue drops, something else may have been going wrong for weeks.

Traffic might have slowed.

Customer acquisition cost might have increased.

Conversion rate might have started falling.

New customer acquisition might have declined.

Revenue is often where the problem finally becomes obvious.

That's why ecommerce teams shouldn't only monitor outcomes.

If revenue is an important KPI, identify the 2-3 metrics that influence it most.

For example:

Revenue
↓
Sessions
Conversion Rate
AOV

Then identify the metrics influencing those numbers.

Now you're building an early warning system.

Instead of discovering a problem after revenue falls 15%, the team has a better chance of spotting what is changing before it reaches the bottom line.

Don't only measure outcomes. Measure what leads to them.