Thursday, August 4, 2022

The Practical Guide to Advertising Attribution

Written by
Lisa Travis

Do you know exactly and accurately how much money your advertising is generating? If your answer isn’t yes, this guide is for you.

While advertising attribution has always been a challenge, privacy law and regulations are now making it one of the most critical - and difficult - obstacles for marketers around the world.

Depending on your company’s acquisition channels and sales funnel, it can be one of the simplest or most complex areas of the intersection of data and marketing.

We’re going to walk you through how to get your attribution set up. At each stage, you’ll want to assess if the next phase of attribution is necessary for you. We’ll also give concrete examples of types of companies and where/when/why it would make sense.

But first, what is marketing attribution?

Marketing attribution is the evaluation process of the marketing efforts that led your customer to conversion. The primary goal is to establish which channels and messages had the greatest impact on conversion.

The Fundamental Problem with Advertising Attribution

It’s a two fold problem: (1) not only are you not able to track accurate return on investment, (2) you also can’t supply the ad algorithms the data they need to reach more of your customers - thus harming your actual return on investment even more.

The ad platforms work by installing a cookie on YOUR customer’s computer.

This is called a “third” party cookie since it’s a party outside of your business organization. This is exactly what has already been limited, and will continue to be limited by both private companies (i.e. Apple) and public (i.e. GDPR).

As third party cookies are getting deprecated (even Google will phase them out by 2024), this means you’re going to see even less over the next few years, until you’re running blind.


Even right now, 66% of people opt out of tracking according to the attribution analytics company Branch.

And each year the number of people using ad blockers continues to rise.

User-uploaded image: attribution+ad+blocking.png


By relying on third parties (Facebook/Meta, Google, etc. 🤯) to track and provide your customer’s data, you will have:

  • Unattributed sales - the sales came from ads, but due to privacy law, the ad platform was not able to attribute it
  • Ad platforms “double counting” - i.e. a customer clicks on an ad on Google, then Facebook, and both ad platforms say the sale came from them
  • Shrinking remarketing lists
  • An inability to engage in cross-platform remarketing (e.g. uploading CRM lists)

The future is a customer supplying you the data directly. This is what is meant by “first party.” If you don’t do this, you will lose to your competitors that do.

Stage 1: Ad Spend to Revenue Ratio

Who It's Recommended For: Anyone running ads.

How much are you spending on advertising? And what is the revenue you are receiving? This is the ad spend to revenue ratio.

The above is a real chart from an eCommerce company. While this chart was created with Supermetrics and Google Data Studio, you can calculate this number manually without it as a short term solution.

The client in this photo is aiming for a 25% ad spend to revenue ratio (see bullet points in the section below for how to determine the right ratio for your business). What you don’t see in this chart is that during that same time frame their “reported” ROAS on Facebook went from 2 to 0.2 - a huge difference!

Why? 95% of their customers buy the ads through Facebook on iPhone. When iOS 15 went into full effect, their reported revenue from Facebook/Meta ads dropped significantly.

Had they just relied on the ad platform data, they would have mistakenly believed Facebook ads “stopped” working. They didn’t - only it’s tracking did. While this doesn’t help the ad platforms optimize (we’ll get to that), this simple metric and understanding allowed them to continue to spend, stop relying on ad platform data alone, and profit.

As to what the “right” ad spend to revenue ratio is, this depends on a host of factors:

  • Your north star metric
  • Your margins
  • Your repeat buyer rate (which affects customer lifetime value and allows
  • Your business type (SaaS, DTC, B2B, etc.)
  • Your other marketing channels

We also suggest charting “Direct Traffic” attributed sales from Google Analytics, as sales attributed to that channel often increase in direct proportion to decreases in paid channels, due to cookie deprecation and privacy features in iOS as mentioned above.

Stage 2:  Server-Side Tracking To Feed the Ad Platforms Better Data

Who It's Recommended For: If you're spending under $1,000,000 per year on ads, use the attribution available in the ad platforms and Google analytics.

While that eCommerce company did make strides, they still had a critical problem: their Facebook/Meta ads still weren’t getting effective data. Even though the ads were getting purchases, Facebook/Meta didn’t recognize them and couldn’t attribute them to the ad or audience.

So how do you fix this?

You will have to GIVE Facebook/Meta your customer’s data since they can no longer collect it.

This is where server-side tracking comes in.

Server-side tracking acts the same way as pixel tracking — it sends information from the advertising platform to the server indicating when someone converts on an ad. The main difference between pixel based tracking and server-side tracking is that server-side tracking bypasses the browser. This circumvents ad blockers which allows for improved conversion tracking and data accuracy.

You will need to hire a developer unless you use a paid solution to set this up.

If you don’t have a developer to set up server-side tracking, the paid solutions are quite cost effective.

Some tools that do this:

  • EdgeTag
  • Cometly (Shopify Only)
  • Zaras

If you have a developer and want to save on ongoing software costs, you can also set it up yourself.

Here are the steps to set up server side tracking yourself:

  1. Set up Google Cloud Platform
  2. Set up Google Tag Manager (server side). Note: Do not use the Google provided default URL; update DNS to use a custom client subdomain (e.g. tagging.clientwebsite.com). When on client’s subdomain, this IS the client’s data as it is collected in a 1st party context. If you use the default Google URL, the data will not be collected in a 1st party context.
  3. Link Google Tag Manager & Google Analytics
  4. Set up GA4 Property. Note: GA4 will automatically create events; conversion tracking needs to be toggled on
  5. Connect GA4 to Google Tag Manager
  6. Create GA4 conversion events in Google Tag Manager
  7. Create Google Ads conversion events in Google Tag Manager
  8. Create Facebook conversion events in Google Tag Manager (Set up Facebook CAPI via connection to Google Tag Manager)

You need to be doing server-side tracking. If you aren’t already doing this, then you need to implement this regardless of your company size.

Stage 3: Attribution Software (Ongoing Cost)

Who It's Recommended For: If you’re spending $1,000,000 - $10,000,000 per year on ads, then consider marketing mix modeling and multi-touch attribution vendors.

Once you’ve done Stage 1 and Stage 2, it’s potentially time for you to explore Stage 3: an advertising attribution software solution. While you can jump to Stage 4 if you want to develop your own solution, for the vast majority of businesses, an advertising attribution software will be the path forward.

To make this easier, we created a database of all the advertising attribution software companies we have trialed, demoed, or worked with, so to make things easier for yourself, you check out our Ad Tech Airtable.

That said, each of these has their own method of attribution modeling. So it’s really about finding the solution that fits your niche, your level of ad spend, your current team, and your structure.

So what are the attribution models we'd recommend?

1) Marketing Mix Modeling: A privacy-friendly, statistical analysis of internal and external factors with the goal of understanding how each one of those factors individually and collectively impacts your conversions. Factors considered in marketing mix modeling include seasonality, media activities, external effects (salary weeks, weather, consumer confidence index, and competitor activities), and internal effects (channel distribution activities, product changes, price changes, sales process changes, and organic content). The goal of marketing mix modeling is to identify possible scenarios that maximize the accuracy of the scenario and the impact it will have on the business.

2) Multi-Touch Attribution: A fractional attribution method that assigns a value to every touchpoint a customer experiences before a conversion.

When reviewing each attribution solution, first identify which attribution model you'd like to use, then set up demos with vendors that offer that attribution model.

During the attribution product demo, here are questions that may be important for you to review:

How is pricing configured (example: monthly, annually, etc.)?

Note: We highly advise against annual when buying an attribution solution given the constant changes in our privacy landscape.

Is there a time/ duration of use commitment?

Time commitments can vary by attribution solution. A short commitment is beneficial to get you through onboarding and training, but anything longer than 2-3 month could be a risky investment.

How many users are allowed?

In some cases, attribution systems may have upcharges for additional users. Check on this if you’re planning to have multiple team members use the attribution tool.

How is customer service handled?

Setup of an attribution system may require troubleshooting at times. Understanding how customer service is handled will help you set expectations moving forward. Once the system is set up, training may also be required. You want to make sure you’re working with a provider who will support you through the whole process.

Is the attribution first touch, last touch, multitouch, etc? Can multiple attribution models be used or interchanged?

Part of the data analysis process should be looking at different attribution models. Ask about default modeling and if you’re able to change or compare different models.

Is the attribution solution web or server based?

Web-based solutions may still be subject to ad blockers. If you’re considering a web-based solution, find out how ad blockers are circumvented before moving forward.

How is the attribution different from competing solutions?

Many attribution tools look the same on the surface, so asking about points of differentiation can help you identify which solution may be best for you.

How is the attribution solution implemented (client vs provider)?

If you are required to implement the solution, do you have someone on your team who can oversee the implementation process?

What is required for implementation?

Whether the you or the provider is the one implementing, a list of requirements for implementation will help identify if the solution will work for your business.

Is there a standard data retention window, and can this be customized?

This should be aligned with your sales funnel so you’re not only getting all the information you need, when you need it, but also so you are not storing data that is no longer useful.

Is there PII (personal identifiable information) within the CDP?

It’s important to consider the trust you’ve built with your audience. If PII is within the system, you’ll want to accurately reflect this in your privacy policy.

Stage 4: Building Your Own “In-House” Attribution Solution (Upfront Cost)

Who It's Recommended For: If you’re spending over $10,000,000 per year on ads, then consider marketing mix modeling, multi-touch attribution, and custom/in-house revenue attribution modeling based on building out your own data warehouse.

This can be as simple as creating your own cookie and an SQL report, or as complex as hiring an engineering team.

For example, one of our B2B clients created their own “first party” cookie that tracks first touch and last touch in an SQL database.

You can do the same by following this tutorial:

However, for larger amounts of advertising spend, sales cycles, and complexity of your tech stack, you may very well need to hire a data scientist or data analyst to help in the process.

Matt Boulous, COO of Blotout (an attribution analytics company we advise), estimates an effective in-house attribution tool could range anywhere from $100,000 to 7 figures or more — primarily due to salaries required for the members of your team required to build and maintain them.

Conclusion

Although it is possible to see general long-term trends in digital marketing (e.g. depreciation of 3rd party cookies, increased privacy opt-ins from apps and Apple, increased need for 1st-party data so website that didn't have logins might need to create that feature), it is still really hard to predict the future.

You might be asking: How am I going to keep up with all these rules and changes if there’s a looming update every 6 months?!

Well, the answer is that businesses don't have to, because there are service and software providers that do this for you. When you go the service/software provider route, you gain a ton of efficiency, time savings, and short term cost savings. That said, for larger organizations, going in-house could offer cost savings over time depending on the level events and tracking required to make everything cohesive.

Ultimately, as a VP of Marketing, CMO, or founder, it will be your job to create an advertising attribution solution. If you still feel that you need some advisory on your next steps, feel free to get in contact with me here.

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