Death by In-App Attribution: These Marketing Metrics Can Kill You

June 20, 2024
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Story time.

You're a marketing executive at a major B2C company.

You've been pouring money into ads on Google, Meta, and other platforms.

Your in-app metrics are telling you everything is going great.

ROAS is up, CPA is down.

You're feeling pretty good.

But then, the quarterly numbers come out.

Profits are down.

New customer growth has stagnated.

You're not hitting your targets.

What went wrong?

Here's the scary truth:

You've been flying blind, trusting your in-app attribution data like a pilot trusting a malfunctioning instrument panel.

Those convenient, seemingly clear-cut metrics have been leading you astray.

They don’t capture the full complexity of your customer journey and marketing performance.

You're not alone.

It’s a common problem.

Countless marketers are making high-stakes decisions based on incomplete, often misleading data from platform attribution models.

They're optimizing towards metrics that paint a rosy picture in the short term but don't necessarily translate to long-term business success.

The consequences can be dire—

  • Misallocated budgets
  • Incorrect prioritization
  • Missed growth opportunities

There’s a disconnect between your marketing efforts and your business bottom line.

In the worst cases, you could be pouring good money after bad, doubling down on strategies that aren't actually working.

Every marketer's worst fear.

Realizing too late that you've been steering your campaigns in the wrong direction, guided by a faulty compass.

But there is a way out of this attributed attribution nightmare.

The solution lies in evolving your measurement approach to focus on more holistic, business-centric KPIs.

It means looking beyond the narrow view provided by in-app data and illuminating your full marketing funnel.

The Hidden Pitfalls of In-App Attribution

In-app attribution models are like fun house mirrors.

They distort reality, showing you a warped, incomplete picture of your marketing performance.

Let's say you're running YouTube ads for your ecommerce store.

A customer sees your video, gets intrigued, but doesn't click right away.

A week later, after some Googling and browsing on your site, they come back and make a purchase through a retargeting ad.

In-app attribution would give all the credit to that last-click retargeting ad, completely ignoring the crucial role your YouTube ad played in the journey.

As John Moran, Head of Traffic Strategy at Tier 11, puts it:

"Attribution in-app is incorrect. It overlaps attribution between platforms... think about TikTok, Snapchat, Meta, Instagram, Facebook, Google, YouTube, organic, Amazon...It's insane.”

In-app data often mis-attributes conversions and can lead you to undervalue certain key channels or touchpoints.

You might see a high ROAS for your Google Search ads and conclude that's where you should be investing more.

But what you're not seeing is how your Facebook video ads are driving a ton of initial brand awareness and search demand—even if they’re not directly generating last-click conversions.

Or maybe you attribute a surge of purchases to your latest promotional email campaign.

But what about that recent PR mention and an influential Instagram post?

Maybe that’s what really got those customers to your site in the first place.

Bottom line?

You're making decisions based on a myopic, siloed view of your customer interactions.

If you’re over-relying on in-app data, you're not accounting for the complex, cross-channel journeys that define modern consumer behavior.

Siloes are dangerous.

When each ad platform takes credit for conversions, it creates a distorted, fragmented view of your marketing funnel.

Facebook is telling you one thing, Google another.

It's like you're trying to assemble a jigsaw puzzle with pieces from different boxes.

This siloed thinking can lead to some deadly decisions.

You might cut back on your upper funnel spend because it looks like it's "underperforming" in-app.

But, in reality, it's playing a vital role in driving awareness and priming conversions down the line.

Attribution Horror Stories

Theories are nice, but real life stories are more relatable.

Unfortunately this is all too common, so examples are easy to find.

Let's look at a few real-world examples.

Retargeting ROAS vs. DTC furniture brand

Danny, a marketing director at a trendy DTC furniture brand, was thrilled when his retargeting campaigns started showing sky-high ROAS.

He doubled down on retargeting spend, expecting to see a big bump in overall sales.

But while more purchases were being attributed to retargeting, total revenue growth was sluggish.

Danny had fallen into the last-click attribution trap, not realizing that his retargeting ads were getting credit for a lot of sales that would've happened anyway.

By over-investing in bottom-funnel tactics, he was neglecting the upper-funnel efforts needed to grow his customer base.

"You can’t scale retargeting. You can only scale new customers." -John Moran, Head of Traffic Strategy, Tier 11

I wish Danny were alone. He’s not—not by a longshot.

Another classic example…

YouTube conversions vs. DTC apparel retailer

Lisa is a VP of Ecommerce for a popular apparel retailer.

She and her team noticed low conversions in Google Analytics coming from their YouTube campaigns.

So what does she do?

She slashed her YouTube ad budget, of course.

Uh oh.

Lisa’s team didn't realize that their YouTube ads were driving A TON of brand searches— which then converted through organic and direct traffic.

By cutting YouTube, they dried up their own funnel.

These are just a couple of the many attribution horror stories we've heard.

And they all point to the same underlying issue:

Thinking too narrowly about the customer journey and the limitations of in-app measurement.

The Cost of In-App Tunnel Vision

When you're too focused on in-app metrics, you're not just getting an incomplete picture.

You could be actively hurting your marketing performance. (You probably are.)

Some common pitfalls:

Misallocating budgets

By undervaluing certain channels, you could be wasting your ad spend in places that don’t have a material effect on your business.

Missing optimization opportunities

Without a full-funnel view, you can't effectively optimize for the metrics that truly matter.

Misreading ROI

In-app data often overstates the impact of some tactics while understating others, painting a skewed picture of your ROI.

Escaping the In-App Attribution Trap

So, how do you avoid becoming another cautionary tale?

How do you escape the in-app attribution trap and start making marketing decisions with eyes wide open?

It starts with a fundamental mindset shift.

You have to let go of the idea that any single attribution model or in-app dashboard is going to give you the full truth about your marketing performance.

You have to embrace complexity and seek out a more comprehensive, business-centric view.

Here’s how.

Setting Effective Benchmarks: What to Measure and Why

When establishing benchmarks, it's crucial to look beyond the standard in-app metrics and focus on KPIs that directly tie to business outcomes.

Some key metrics to consider:

New Customer Acquisition Cost (nCAC)

How much are you spending to acquire each new customer?

Marketing Efficiency Ratio (MER)

How much revenue are you generating for each dollar spent on marketing?

Lifetime Value (LTV) and LTV:CAC ratio

How much is each customer worth over their lifetime, and how does that compare to the cost of acquiring them?

Tracking these metrics over time and across channels will give you a more comprehensive view of your marketing performance than relying on in-app ROAS alone.

As Tier 11's John Moran puts it:

"Benchmarking is a simple snapshot during a time when the business is healthy.”

Of course, it's important to remember external factors like seasonality, market conditions, and competitive activity.

These things can impact performance anytime, including during your benchmarking period.

To account for this:

  • Outliers — Choose a benchmarking period that is representative of typical business conditions
  • Outlines — Look at year-over-year comparisons to normalize for seasonal effects
  • Outsiders — Consider external factors qualitatively when interpreting benchmarks

Here are some key steps for killer benchmarking:

Define your north star metrics

What are the ultimate business outcomes you're trying to drive? Revenue growth? Profit margins? Customer lifetime value? Make sure your KPIs ladder up to these overarching goals.

Embrace cross-channel measurement

Implement tracking and analytics that allow you to see how different touchpoints and channels work together to drive conversions. Tools like Data Suite and Google Analytics 4 can help provide a more unified view.

Establish smart benchmarks

Identify time periods where your key business metrics were strong, and use those as benchmarks for channel-level performance.

Experiment and iterate

No single attribution model is perfect. The key is to constantly test, learn, and refine your approach. Try out different attribution models, but always cross-reference with your north star business metrics.

Foster cross-functional collaboration

Break down silos between your various marketing functions, and make sure everyone is aligned around common goals and metrics. Regular, cross-team communication is essential.

Benchmarking > Attribution

For enterprise marketers in particular, the limitations of traditional attribution models have become increasingly apparent.

In a privacy-centric, cross-device world, tracking individual user journeys and assigning credit to specific touchpoints is completely unreliable.

Benchmarking is a privacy-safe way to measure the overall impact of your marketing efforts and optimize for business outcomes. (I.e. make more money!)

No one wants to piece together a patchwork of incomplete attribution data.

Benchmarking is better.

It allows you to assess your performance holistically and make optimizations that directly improve your bottom line.

So what to do about it?

New North Star

At Tier 11, we've pioneered a new approach to marketing measurement that we call the "Conversion Engine."

It's a holistic framework that looks at four key pillars:

  • Data
  • Creative
  • Traffic
  • Conversion

By optimizing each of these pillars and tracking overarching metrics like MER and nCAC, we help our clients escape the myopia of in-app attribution and make confident, data-driven decisions.

It's not about chasing vanity metrics or gaming a particular attribution model.

It's about aligning your marketing efforts with your core business objectives and building a sustainable, profitable growth engine.

As Nick Miller, Head of Media Buying at Tier 11, explains:

"...a successful full funnel approach is going to have to incorporate omni-channel strategy, tracking, and optimizing.”

True marketing success in today's landscape requires a comprehensive, adaptable approach that values each channel for its unique role in the customer journey.

The Truth is Out There—Keep Grinding.

If you're feeling lost in the fog of in-app attribution, you're not alone.

By evolving your measurement approach and embracing a more holistic, business-centric mindset, you can start navigating by a clearer, truer north star.

It won't happen overnight.

Escaping the gravitational pull of flawed attribution models takes time, effort, and organizational buy-in.

But the rewards—more effective campaigns, more efficient spend, and most importantly, real business impact—are well worth it.

Let's Talk

At Tier 11, we're passionate about helping B2C marketers make this transformation.

Our team of experts has deep experience implementing cross-channel measurement frameworks and optimizing for long-term, full-funnel success.

If you're ready to leave behind the nightmares of misleading metrics and start making confident, clear-eyed marketing decisions, we'd love to chat.

Because life's too short for attribution horror stories.

It's time to write your own tale of measurement success.

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