Attribution model in Google ads is not a new concept for those who ‘live’ by optimizing ads. But for beginners or in-house teams, how are you understanding and applying? Let’s discuss ‘all’ related questions about attribution model with Digit Matter in the article below!
What is the attribution model? Why is this important to monitor?
For an audience to ‘set foot’ on your website to purchase or leave information, it’s a whole lot of effort. They may visit your website because:
- Read emails
- View 1 post on social media
- View ads
- Search online
- Read reviews
- And through many other ways
Very few people “go straight” to your website right away, except you. And to explain where your leads come from, through what channels, in what order, the Attribution model is the tool to help you explain this.
In other words, the Attribution model is a tool to help you aggregate and track the different journeys of each customer on the journey from ‘stranger’ to ‘lead’ or sales. From there, it helps advertisers find common patterns/templates to optimize the role of each channel and ‘trap’ at the right time, in the right place, in the right way to pull the target audience towards them.
Therefore, calling the Attribute Model a radar that tracks the ‘customer journey’ is not wrong.
If the advertising budget is large enough, this will be an extremely useful tool. After all, ad optimization is a never-ending process. To maximize future results, you need to start with the ‘past’: Are the customers ‘on track’ to your expectations? How do they find out and get excited about your brand? The current way of conveying the message on each channel is in sync with the role of each channel?
What attribution models are there? Distinguish Single-touch attribution models & multi-touch attribution models
When running Google Ads ads, the attribution model has 2 main groups:
1. Single-touch attribution models
Single-touch attribution models is the model Only recorded effectiveness in driving conversions for only 1 channel – the first or last channel exposed:
- First click: With this model, the first channel to reach the target audience is the most effective channel, regardless of their back-to-back interactions or how long it takes.
- Last click: The model ignores the contributions of all other channels and only credits the last channel the audience is exposed to before leaving a lead or making a purchase.
Usually, this should only be a reference model, not the basis for making a final decision because every lead depends not only on the first or last channel, but on the ‘small’ contributions of each. channel throughout their learning, interaction, and decision-making journey.
One of the mistakes we often make is looking at the direct channel that brings in leads. This is quite similar to the last click model. If you run 3 channels GDN, SEM and Facebook in parallel, the results show that most of the leads come from GDN, should you turn off all ads in the other 2 channels.
This depends on the ‘customer journey’. Sometimes things change completely even if you increase your budget 100% to GDN. Because GDN can be an effective channel in closing deals, but it is not necessarily the optimal channel to reach, persuade, and interact in the previous stages. If you only look at 1 cover to judge the content of the book, that is impossible. For that reason, you need to keep an eye on the second group of models: multi-touch attribute model
2. Multi-touch attribution models
Multi-touch attribution models are a more holistic view of the entire customer journey, but recognize the contribution of each channel in different ways:
- Linear: Divide the final effort equally among all channels to reach customers
- Time decay: Channels that are closer to the time of conversion are more likely to be recorded – for example, those that reached customers from a week earlier are only recognized by 50% of those exposed 1 day before the time of conversion.
- Position based: 40% contribution is credited to the first and last channels, the remaining 20% is divided equally between the channels in the middle
- Data-driven: Acknowledge each channel’s effort based on how the target audience interacts along the ‘reach journey’ through the data collected from the system.
You can check out the Top Conversion Paths report to discover the customer journey to solve questions: ‘how do they find you’, ‘what is the common pattern’…?
In addition, to compare the performance of each channel based on the selected attribution model, you can go to the Conversion section and see the Assisted Conversions report. If your goal is to optimize the budget for each channel, these are useful models for cost-effectiveness balance.
However, these also seem to be underutilized models. According to the survey, 58% of people running Google ads often only focus on the first click or last click model, only 34% use the multi-touch attribution model. If you have read this far, it seems that it is time for you to change a few habits before in analyzing – optimizing ads.
Analysis of the advantages and disadvantages of each model Multi-Touch Attribution
1. Linear attribution
Advantages: Since all channels of reaching customers are recognized equally, this will be the most suitable form to optimize the ‘whole customer journey’ instead of focusing on a single activity.
Defect: That is, you will not be able to distinguish which channels are not really effective or contribute to the ultimate success.
2. Time decay attribution
Advantages: If your industry has a short ‘sales cycle’, this will be the right model for you to determine which channels should be focused to accelerate their decision
Defect: If businesses operate in B2B segments or large value products that need time to consider and think for weeks, months, even nearly a year, the application of the above model may not be recognized correctly. Identify the role of advertising channels
3. Position-based attribution
Advantages: Every channel is recognized in the process of ‘persuading customers’ while the two most important channels – the first and the last channel still receive enough due respect.
Defect: Sometimes confusion can occur when placing too much weight on the first channel – the last channel. Just think, what if the first channel to reach is mass emails?
4. Data-driven attribution
Advantages: using the above attribute model, you will increase the accuracy of the influence of each channel through the logic in the data.
Defect: However, if the data is not large enough, the returned results will be very difficult to be accurate!
So which Attribute Model should be used? The answer is ‘no answer’, it all depends on your goals, budget, and available data. Each attribute model will best serve a specific purpose. With the above analysis, hopefully you have a bit of a picture about what is the best model and when is the most suitable for your campaign!
To learn more about Google Ads and suggestions for implementing and optimizing ads, see more at:
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