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Multi-channel marketing has been a popular digital marketing strategy for years, allowing marketers to reach their target audience through a variety of different platforms. That’s because this strategy has proven to be effective. HubSpot research shows that 92% of marketers use more than one channel and 81% use more than three. 

With a multi-channel marketing strategy, your school can spread a unified message across different platforms—including social media, website blogs, emails, and paid advertisements, to name a few. By using different marketing touchpoints in this way, you can reach a broader audience with a more impactful message. 

But how can you determine which touchpoints play the biggest role in your prospect’s conversion journey—or how to allocate the right resources and budget to drive positive results?

This is where attribution modelling comes in. 

By setting up Google Analytics correctly and applying the right attribution model for your school, you can gain better insights that help you enhance your multi-channel digital marketing strategy. Read on to learn more about attribution modelling and how your school can apply it to improve overall student recruitment efforts!

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Applying Attribution Modeling in Your School’s Multi-Channel Marketing Strategy 

An attribution model, according to Google Analytics, is understood as the rule (or set of rules) used to determine “how credit for sales and conversions is assigned to touchpoints in conversion paths.” Essentially, it allows marketers to give credit to specific touchpoints for completing a sale or driving a conversion—giving value to touchpoints that play the biggest role in a prospect’s conversion journey.

For instance, a student may discover your school through a social media post or hear about your latest program via email marketing. They may then click the link to your landing page and fill out a form, completing their conversion journey. In this scenario, your school can attribute the conversion to different touchpoints and credit the first interaction or the last interaction—or even choose from Google’s wide range of available models for one that best suits your individual campaign goals.

By using Google Analytics, schools can access Multi-Channel Funnels (MCF) reports, which show how different traffic sources contribute to a prospect’s conversion. The MCF Channel Groupings, as seen below, depict conversion paths that consist of different channel combinations. Monitoring these conversion paths and analyzing the results can help schools determine which traffic sources or channel groupings yield more conversions. 

Google Analytics attribution model

Requirements Your School Needs to Address before Using Attribution Models

It should be noted that before starting with attribution, you’ll need to have goals or transactions properly set up and configured in Google Analytics. Doing so provides you with the data you’ll need to use attribution modelling. You’ll also need to link any Google marketing tools that your school may be using, such as Google AdWords. This is especially relevant if your school is running any pay-per-click (PPC) advertising campaigns.

Ensuring that Google Tag Manager is properly set up for your school’s inbound marketing efforts is also an important step. Google Tag Manager makes it easier for your school to update or deploy Google tags and other relevant code used to provide you with access to Google’s range of advertising and measurement services. With that step completed, you can feel more confident knowing that your conversion data is going to the right source and is correctly attributed.

The image above shows a basic setup in Google Tag Manager. Tags are in blue and serve different functions. For instance, the “PPC Lead” tag tracks paid ad conversions on a specific page while the “Callto Click” and “Mailto Click” tags track users who click on a phone number or an email on the website. This is where you’ll want to paste your conversion code and configure the actions that will generate the conversion.

Google Analytics for schools

Why Correct Attribution Matters in Your School’s Overall Marketing Strategy 

Google Analytics offers users a wide range of attribution models, and the data gathered by them can be used to further optimize your efforts—helping you understand traffic and conversions as well as identify the greatest return on investment (ROI) from your multi-channel marketing efforts. This can affect how your school prioritizes its efforts, managing its budget and resources in a way that ensures maximum impact.

Attribution models give you more control over the conversion value you can assign to each interaction. When done right, this can help you adopt models that better align with how prospects discover your school and search for your offerings. It can even help you find more opportunities for reaching prospective students earlier in the sales funnel. By diving into the data, you can also better understand how your ads perform and optimize your efforts to promote better results.

This all goes to show that data is integral to the success of your multi-channel digital marketing strategy. Unfortunately, a 2020 web analytics survey shows that despite its valuable contribution, data is too often “mistrusted”—left with untapped potential. Around 88% of respondents said that they did not trust their data to be at least 90% accurate and only 6% of marketers in the survey reported the opposite.

Clearly, there’s a gulf to overcome in order for businesses across all sectors to become more data-driven and confident with their marketing strategy. Starting with a thorough exploration of the Google Analytics platform and its lists of reports, while also choosing the right goals to track, can go a long way in ensuring that your data is accurate and actionable. 

Being proactive in this way can help your team bridge the data divide and develop effective ways to measure your school’s marketing and advertising ROI, as was the case in HEM’s collaboration with McGill SCS.

Key Attribution Models Your School Needs to Know for More Effective Marketing 

Different attribution models have different functions, giving schools a range of options to choose from. It all depends on your digital marketing strategy and the touchpoints you value most. In this way, you can customize your analytics to reflect your priorities—giving you the insights you need to make better marketing and advertising decisions. 

Here’s a breakdown of the different attribution models in Google Analytics for schools:

Google Analytics in higher education

Based on information from Google Analytics

1. First Interaction Attribution Model

True to its name, the First Interaction (or First-Click) attribution model assigns the full credit for a conversion to the first touchpoint. Essentially, this ignores all other marketing campaigns and channels and focuses solely on that First Interaction. 

This makes the First Interaction model quite limiting in general, but particularly effective for schools wanting to determine which channel brings in the highest number of new visitors. New schools or schools with new programs may be interested to try this model to track how they reach new prospects in order to increase brand awareness. 

2. Last Interaction Attribution Model

On the opposite end, the Last Interaction (or Last Click) attribution model gives the full credit for a conversion to the last touchpoint, regardless of what it may be. This model overlooks all previous touchpoints and, interestingly, is used as the default by Google Analytics activity columns. 

Because of how it attributes data, the Last Interaction model is ideal for schools looking to track conversions beyond the consideration stage. Schools running ad campaigns can use it to track prospects right at the very end of their conversion journey, determining the efficacy of their campaign efforts.

3. Last Non-Direct Click Attribution Model

Set as the default for non-Multi-Channel Funnels reports by Google Analytics, the Last Non-Direct Click model assigns the value of a conversion to the last touchpoint so long as it is a non-direct traffic source. Here, the data skips direct traffic (visitors who go straight to your website) and only targets the channel prospects used before converting, such as email or social media. 

This model can be useful for schools wanting to track conversions coming from different channels, narrowing their data pool by excluding prospects who have already seen their marketing campaigns and know the website domain name. 

4. Last Google Ads Click Attribution Model

Schools running different AdWords campaigns may benefit most from the Last Google Ads Click attribution model. Here, the full credit is given to the last paid ad that prospects clicked on before converting. All other traffic sources and touchpoints are ignored in this model, making it solely focused on existing Google AdWords campaigns. 

This model may sound very restrictive—and in some ways, it is—but it allows schools to easily figure out which paid ads and keywords are driving the most success. 

5. Linear Attribution Model

If each touchpoint in your prospect’s conversion journey is equally important for your school, then the Linear attribution model may provide you with the best solution. Here, credit for each conversion is equally distributed to all of your touchpoints and channels. For instance, paid search, social media, email, and direct channels would each be assigned 25% credit for the conversion. 

The Linear model can help schools that want to see the big picture in their marketing strategy, giving insights on how each channel and touchpoint perform in the overall conversion journey. Over time, schools using this model can determine which channels are generating better results and put more resources into them. 

6. Time Decay Attribution Model

Considered to be one of the more popular attribution models, the Time Decay model assigns most of the credit to the channels and touchpoints that are closer towards the end of the conversion path—giving less value to those in the beginning. 

This model is time-sensitive and can be great for schools running temporary promotional campaigns, assigning most of the value to those ads as they motivate prospects to make a buying decision. Since the Time Decay model prioritizes the last channels in the conversion path, it can help schools discover which channels push prospects closer towards converting. 

Alternatively, it can also be used to help schools identify channels that attract prospects at the top of the marketing funnel. By knowing this information, schools can make better decisions concerning the purpose and function of different channels in their overall marketing strategy.

7. Position-Based Attribution Model

The Position-Based attribution model can be viewed as a hybrid of sorts, combining both the first and last click models. Here, the first and last touchpoints equally receive the majority of the credit while those in the middle equally share the remaining credit. For example, the full value of 100% would be divided into 80%, equally split between the first and last interaction, and 20% for everything in between.

This model can work for schools that want to prioritize both the first and last interaction equally, gaining insight on which channels acquire prospects and which ones convert them—attributing the most value to those same channels and touchpoints. 

8. Cross-Channel Data-Driven Attribution Model

Earlier this year, Google announced that it would fully roll out the Cross-Channel Data-Driven attribution model in Google Analytics 4. This Data-Driven model makes it so that schools can receive data insights that reflect how prospects engage with their overall marketing efforts. Through Google’s machine learning algorithm, the Data-Driven model determines which touchpoints have the strongest impact on your strategy and attributes credit for conversions accordingly. 

The image below shows how the Cross-Channel Data-Driven model attributes conversions to different channel groupings:

attributions modeling

Source: Google Blog

Because of its design, the Data-Driven model can be used to analyze insights from multiple sources in order to confirm whether or not the data gathered is statistically significant. In this way, schools can develop a broader understanding of how different marketing activities influence conversions—leading to better marketing decisions about where and how to allocate resources in order to increase the ROI. 

How to Choose the Right Google Analytics Attribution Model for Your School 

Choosing the right Google Analytics attribution model may not always be a straightforward task, but it can provide you with valuable insights on the performance of your school’s marketing efforts while introducing you to new opportunities and areas of improvement.

If you’re unsure which model to go with, then consider using Google’s Multi-Channel Funnels (MCF) Comparison Tool, which allows your school to compare up to three different attribution models at once. You can start by developing a clear vision of your advertising and marketing goals as well as a solid framework for your school’s business objectives. With that in hand, you can begin experimenting with different models and analyzing the results to determine the one that works best for your individual needs and purposes.

The image below shows how schools can use the MCF Model Comparison Tool to view and analyze different attribution models side by side:

Google Analytics in education

Source: LogicSpot 

According to Alexander Nachaj, HEM’s Manager of Search and Analytics, “Different attribution works well for different situations. Last Click gives an immediate and clear indication of lead generation campaign performance. A Data-Driven model could be very useful for broader awareness campaigns, where it is necessary to understand the efficacy of various channels in contributing to the final conversion action.”

The Last Click model is one that HEM heavily relies on to track conversions for a broad range of schools. That is because many schools are focused on lead generation campaigns. “Since our main efforts are lead generation, we only count the last click that led the user to the form where they converted. This inevitably overlooks some of the more complex paths a user might take (paid ads -> organic -> direct, for example), but it allows us to make more direct connections between our campaign performance and conversion data,” says Alexander. 

In some cases, schools adopt a Data-Driven attribution model before working with HEM. However, this can also yield messy data as the conversion value gets divided into fractions that are then attributed to different channels. With the right infrastructure, that isn’t a concern—though the right infrastructure is not always a given. 

“Last Click is arguably the most strict and conservative way to measure results, which is why we use it,” Alexander adds. “As it focuses on clicks rather than views, it helps ensure that our data is grounded in measurable and high-intent actions taken by the users.” This is particularly notable since other models, like First Click, can distort the overall analytics for lead generation efforts by focusing on the first interaction instead of counting the conversion action. 

Ultimately, it’s all about context, but having a solid understanding of different attribution models and available options can help you determine the right move for your school. 

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