How CMOs Can Use Conversion Tracking & Attribution For Smarter Paid Media Strategy

For chief marketing officers of retail brands and businesses, knowing which channels and campaigns deserve the marketing budget can directly impact the success and length of their tenure.

But in today’s omnichannel environment of walled gardens, customers engage with your campaigns (and other assets) multiple times before converting.

Since there is no perfect conversion tracking or attribution, you need a system to decide where to spend your money.

Too many marketers still rely on outdated or overly complex attribution models, incomplete data, or pure guesswork.

Common side effects include over-investing in either the upper or lower funnel, while underfunding channels and campaigns that balance demand generation and demand capture.

In this article, we’ll break down how CMOs and marketing leaders can use conversion tracking and attribution data to:

• Understand true channel performance.
• Make better budget decisions.
• Improve full-funnel efficiency.

Conversion Tracking In Google Ads: Limitations & Blind Spots

Running a Google Ads or paid media campaign without native conversion tracking is asking for trouble.

Not only will your account operate with blinders that prevent the system from finding improvements and patterns, but you won’t also have any in-platform metrics to measure your own database against.

I also see some accounts can take several weeks for reporting data to be attributed fully, primarily because of the click-to-purchase duration.

Google may not be fully accurate with all metrics, but you want it to understand what actions are meaningful to your business.

Lead Generation

• Online conversion actions: form fill, chat, phone call.
• Offline conversion stages: qualified lead, converted lead.
• Support tools: WhatConverts, HubSpot, or other CRM to track lead data + Zapier for connectivity.

With leads, there is a challenge in terms of reconciling what is recorded online and what happens outside of the Google ecosystem.

Google’s system knows it got you a certain number of form fills, chats, or calls. It needs to know how many of those were good quality leads. How many of those went on to become actual sales?

That would lead you to create a “next step” in the process, such as qualified leads, and feed this back into Google. You can also then bid against those or use them as observations, but they will be in the system as a positive funnel event.

Read more: Building A Lead Generation Plan

Ecommerce

• Online conversion actions: purchase, add to cart.
• Offline conversion stages: subscriber, repeat buyer.
• Support tools: Shopify to track returns, exchanges, etc.

For ecommerce, it’s typically a lot simpler to track the right events, but it’s trickier to rate their value to the business.

Google can record purchase transactions as an event, but it lacks your backend data on which locations have the fewest returns or exchanges, which products lead to higher rates of subscription and repeat purchases, and what each product’s margin is.

If you’re using Shopify, they have a Google and YouTube app that does pretty much all the heavy lifting you need to do to link the two platforms and track ecommerce sales.

How To Use Performance Data To Fuel Better Marketing Investments

“I know which channels and campaigns are providing the best ROI” is verbal gold for a CMO.

Being able to quantify the impact of where they spend their marketing budget positions them to make smarter decisions and increase their value to the business that employs them.

Unfortunately, this is easier said than done. Here are some ways to think through the more common hurdles that get in your way as a marketing leader.

Thinking Through In-Platform Attribution

Once you set up tracking and make sure you’re getting good performance data in, you can use it to inform attribution and omnichannel strategy.

My methodology is different from how many marketers approach this. I’m of the mind that attribution is not something that can be fully solved, and over-relying on third-party tools will set you in the wrong direction because they all have different biases.

Certain tools can’t see the actual power of YouTube, for example.

One study by Haus showed that YouTube in-platform reporting is three times less than what they see. So many third-party attribution tools can’t see view-through or engagement data for YouTube, so they end up with a higher-than-ideal margin of error on the reporting.

Some other tools can see the click and view attribution for Meta, but only click attribution for Google. What I like to do is optimize each campaign in-platform based on that platform’s data.

Handling Conflicting Attribution Data

When we come across situations where different platforms show us conflicting attribution data, we use overall sales reports and tools like TripleWhale or Northbeam to help validate that data.

This helps us understand directionally, if we put another 20% of our budget into a specific campaign type, how does that impact the overall revenue?

It’s really about looking at blended numbers – some people call it media efficiency rate (MER) or blended return on ad spend (ROAS) – to see how that data changes over time with different campaign and marketing changes.

We use this to allocate budget according to what really moves the needle as far as revenue and profit are concerned. This is much better than just relying on what a platform tells you.

With lead generation, this is less of a problem because most lead form fills happen pretty quickly after the initial click.

If the user submits the form on the same page they landed on, you will very likely capture UTM and GCLID parameters.

For lead gen, we typically look to verify that the number of leads in the customer relationship management (CRM) is within 10% of what Google attributes to itself.

Point Of Diminishing Returns: Why All Growth Stalls

One thing many people forget is that with visibility and success in digital advertising, you pay a price in terms of incremental headroom.

In other words, you have much more untapped opportunity at 30% impression share than you do at 85%. Getting from 30% to 85% is going to probably be much less expensive than going from 85% to 90%.

If you look at Google Ads’ own attribution, there’s a finite amount of headroom with Search and Shopping.

Once you hit the top of that, it usually tapers off somewhere between 70-80%, and you’ve got to start finding other campaigns/platforms to start feeding the funnel. That could be other Google properties (like YouTube) or channels like Facebook, Instagram, or TikTok.

Fortunately, Google is now starting the rollout to show you this data for Performance Max in addition to Search and Shopping. This means you can take advantage of benefits like finding new advertising opportunities while still applying optimization tactics that you’re used to.

The other thing that’s really important, especially for newer advertisers, is not to expect the same performance from every campaign type.

People who have been around the block in PPC know, for example, that a 5x ROAS on branded search is realistic, but for YouTube, it might be 1x or even less.

You need to be okay with that, as long as you can get all the numbers to line up in terms of your total costs versus total revenue and margin.

Good Strategy Is Always Built On Clear Business Goals

Conversion tracking and attribution are essential parts of the CMO toolkit, but they mean little without the skill and literacy to interpret performance data in the context of a business.

If we were to sum up the most important part of this thought process, it would be:

• Native platform tracking is crucial, but it’s only one part of the puzzle. Feed meaningful business outcomes back to the ad platforms to improve performance over time.
• No attribution model is perfect. Treat attribution as directional rather than as an absolute, and be cautious about over-relying on third-party insights as they have their own blind spots.
• Use blended metrics and cross-platform validation to make strategic choices based on actual business needs and financial goals, not just the metrics that one channel reports.
• Recognize diminishing returns as you scale inside one platform and diversify intelligently across multiple channels to maintain growth.

Ultimately, your ability to optimize campaigns hinges on a central, unbiased source of truth that isn’t influenced by the incentives of any single ad platform.

Google or Meta are businesses built to serve their own business objectives and those of their shareholders, which don’t always align with those of your business.

By owning your data and attribution strategy, you set your brand up to make smarter, more confident marketing investments instead of pinning all your hopes on a long shot that’s rarely (if ever) accurate.

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