Using Data Attribution Comparison Table in Google Analytics 4

It's commonly used multi-channel strategies to acquire as many customers and sales as possible. However, the contribution of sales is made up by multiple partners and not always with high ROAS as advertising platforms show you.

A correct analysis of sales contributions is important for the allocation of budget on the different channels and planning a proper marketing strategy based on these.

The famous Messy Middle: to understand well what is in between the acquisition or the first touchpoint and the final sale, has become a fundamental reading for all online businesses.

Source Google

It seems a bit weird approach, but some agencies are currently calculating marketing campaigns performance with a unified ROAS dictated by the simple calculation of all the channels taken in place:

ROAS = Total Revenue / Total Ad Spend

Underlying this calculation is an objective assumption that working in a multi-touch and multi-channel scenario, we should consider the ROAS at a higher "view".

Based on Ipsos research, the merchants that in 2021 used 5 channels to communicate with their audience have had x2 more sales than others.

It is a very interesting fact: omnichannel is a must-have. The only difference is how you manage communication on the different channels and what strategy you roll out.

Another point of view is to calculate the contribution using a scientific method.

Working in a multi-touch and multi-channel environment, it's better to understand who is contributing and who is contributing much more than others to be more impactful on the business sales.

What is a marketing attribution model?

A small step behind introducing the concept of marketing attribution

How he attributes himself to a partner and his weight in fulfilling this goal. Attribution models then assign different values to the various touchpoints that drive sales.

The most widespread attribution methods currently and still present in GA3 are:

• Last Interaction Attribution

• First Interaction Attribution

• Last Non-Direct Click

• Linear Attribution

• Time Decay Attribution

• Position-based Attribution

  
  

Once you have switched to GA4, you can use an attribution method based on the data and compare it with the "standard" ones in the list above.

The configuration of Google Analytics 4 is not a walk for those unfamiliar with analytical tools or data setup, but it offers excellent satisfaction if configured well.

Why is marketing attribution important?

To better evaluate the allocation of budgets and costs for each sale, customer acquisition or, more generally, objectives.

For instance, if a consumer sees a display ad and an email campaign but only converts after viewing a special promotion within the email, marketers might realize that the email played a more significant role in driving sales than the display ads. Consequently, they can allocate more resources to developing targeted email campaigns.

Google Ads has a different attribution method than Facebook Ads as well as Pinterest, TikTok and programmatic partners.

To achieve the data granularity required for effective attribution, marketing teams need advanced analytics platforms that can accurately and efficiently distil big data into person-level insights that can be used for optimizations within the campaign.

How is marketing attribution measured?

Marketing attribution can be measured through models that evaluate different aspects of the campaign to determine which ads were most effective for sale. The most effective attribution models will provide information on:

• Which messages a consumer was exposed to and on which channel
• Which point of contact had the most significant impact on their purchase decision
• The role of brand perception in the conversion decision
• Which advertisement has better results
• Which format is more performing
• The effect of external factors (e.g. how gas prices affect auto sales)

Many businesses still rely on the last-click attribution model, even though it can no longer reflect the buying behaviour of real consumers.

How to normalize the attribution of conversion campaigns

When you configure Google Analytics 4 properly, it's possible to use data-based attribution (machine learning) to show which campaigns had a better impact on which touchpoint - see exactly what campaigns have influenced the conversion in the user's journey.

Since 2014, the template has been accessible in Google Ads and is now integrated into the new Google Analytics 4 platform. It functions across devices such as smartphones and tablets and channels including Search, social media, apps, Display, and YouTube.

The dedicated section of the tool allows us to evaluate campaigns with different attribution methods by comparing the one based on data (data-driven) and with other more recognized and standard models such as last click, first click, etc.

The comparison allows you to view, using the last column, the differences between the different models. In this first view, selecting a suitable time range makes it possible to evaluate the purchase conversions by a single medium.

In the image above, the section dedicated to the conversion path is shown, divided into three macro touchpoints of the funnel (early, mid and late). In these columns, it is possible to highlight the actual contribution to the customer sales decision-making path.

Changing the breakdown from Source to Campaign is interesting because it shows what happens at the different steps of the purchase funnel.

E-commerce companies that consistently conduct marketing experiments instead of taking a “one and done” approach produce 30% higher ad performance in the same year and a 45% increase in performance the year after that.”– Think With Google

Also published here.