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At present, there are 6 different attribution models available in Google Ads conversion tracking. For those who do not have much knowledge about attribution modelling, choosing one among 6 could be a headache. In a broader perspective, attribution modelling can help you understand when, how and why people converted on your website through Google Ads.
On the other hand, choosing a wrong attribution model can furnish inaccurate, incomplete data that can impact your success with Google Ads campaigns.
Here come the questions: What are the different attribution models to choose from? Which one is best for your business or business objective?
That’s what we are here to answer…..
Let’s dive deep into the ocean of Google Ads attribution modelling.
According to Google, “On the path to conversion, customers may do multiple searches and interact with multiple ads from the same advertiser. Attribution models let you choose how much credit each ad interaction gets for your conversions.”
Attribution is important, irrespective of your industry or your buying cycle. As more attribution models are created, it becomes more confusing to understand which one is the right one. Nowadays, without any data backing it, people start claiming a specific attribution model is right and best. The reality, however, is that no single attribution model can be the standalone source of accurate data — because no single attribution model can paint the full picture for decision making.
An attribution model is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths.” – Google Analytics Help
Sounds simple right?
Well, not really. It is not that simple in the era of digital marketing where a user gets exposed to multiple channels during its conversion path.
For a lead to convert, it takes around 7-13 touches or engagement with your business. This means that they could have visited your landing page or website with RLSA, display remarketing ads or other channels like Instagram, Twitter, Facebook etc.
Now you see the problem. With so many touches, you simply can’t give credit to a single channel for a conversion. All channels need not necessarily play an important role in lead nurturing. But you just can’t ignore a channel that pushes the lead down the funnel by an inch.
Here comes the importance of an attribution model. Attribution modeling seeks to offer visible data on what channels played the most important roles in converting a given prospect.
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You must be wondering which attribution model is the right one. The truth is, it depends on what question you are trying to answer. That’s right — we are suggesting that you should use different attribution models to answer different questions.
Let’s take an example. You want to know which channels have first-click attribution. You need to answer the question, “Which channels generated new prospects?” Look at the first-click attribution model to answer this question. You also want to know which channels are closer to your conversion. Look at the last-touch attribution model to get the answer.
At some point, it is likely that you’ll want to consider multi-channel performance. Looking at the multi-touch attribution model will definitely give you the answer. The multi-click attribution model you choose totally depends on your sales cycle and the questions you are looking to answer.
Hence, you must change the attribution model when you want to achieve a desired result.
An attribution model works on Google’s machine learning to analyze the touch points lying on a conversion path. It attributes credits to all/some touch points based on the attribution model included in a given conversion. Moreover, it ensures that you are able to extract the accurate data from your campaigns given that you have selected an attribution model with respect to your business objective.
With change in business/campaign objective, you may find a need to switch to a different attribution suitable to that objective. In this case if you switch the existing conversion attribution to the other model, chances are you may not get the desired results in early phases of the campaigns.
It is advisable that you should not switch an attribution model but create a new conversion with the required model. However, move to a data-driven attribution model (within the same conversion action) if it is available as this works effectively.
Well, you should not attach any specific attribution model to an industry.
So it depends.
Selecting an attribution model must be based on your business objective.
You might be having a new product in the pipeline and existing brands, too. Campaign objectives for both these would be completely different – hence the attribution model, too. Ensuring the right model will not only provide you accurate & clear data, but also help in taking strategic decisions for future success.
The objective of every marketing campaign is to generate the desired results, the success of which can be measured by analysing the contribution of different channels during a conversion path.
There is no hard and fast rule that describes a ‘best’ attribution model. It totally depends on your marketing objectives. The right attribution model defines the success of your marketing campaigns.
In Google Ads, the following 6 types of attribution model are available:
Let’s find out which attribution model you should choose based on your business objective.
This attribution model attributes all credit for leads/sales generated to the original source.
Use the First-Click attribution model to understand which of your sources are generating new prospects. You can run promotional campaigns to generate buzz about a new product.
First Click works effectively if your advertising is limited to one or two channels. In this case a customer has limited options for finding your store.
If you are in a position to expand your reach with new prospects or you are launching a new product, you could use this model to measure brand awareness & determine which channels are most likely to produce new leads/sales.
This attribution model attributes all credit for leads/sales generated to the last marketing touch point.
To measure the success of an email marketing campaign, use Last-Click attribution model.
For example, you run a campaign to your current customers with a promo code for 30% off and generate $20k revenue. All of that revenue would accurately be attributed to the email campaign with Last-Click attribution.
Last-Click puts weight on the final actions before a conversion. With this model, analyze the “decision factor” that resulted in conversion. Last-Click works best for businesses with shorter sales cycles.
Position-Based attribution is also called U-shaped attribution. This attribution model attributes a higher value to the first and last touch (typically 40 percent each) and distributes the remaining value among all touch points in between.
If you want to simply look at all of the channels that are contributing (for increasing ROI), linear attribution could be a good model for you.
Let’s take an example.
A customer visits your store through Google organic search, then subscribes to your email list and clicks to your store from an email. Two months later they are re-marketed by a Google Ad and go to your store directly. A week later they see a Display Ad and make a purchase. The linear model would attribute maximum credit to organic search & Display Ad.
Position-Based attribution heavily gives credit to the channel that first brought in a customer as well as the channel that caused a conversion. But it also considers channels in between that helped nurture and keep your customers in the conversion path.
This helps you focus on channels that bring new customers in and channels at the bottom of the funnel.
Linear attribution model attributes equal credit for leads/sales generated to all the marketing touch points irrespective of their role in the sales cycle.
Use the Linear attribution model if you’re running a subscription service business that depends on periodic revenue and ongoing engagement with your product.
The Linear attribution model is effective to measure overall brand reach & revenue, and to see which channels are consistently influential during a customer journey.
The Time Decay attribution model put more emphasis on channels closer to the conversion point and less to channels earlier in the funnel.
Time Decay is meant to assign credit to the channels that helped your prospect reach the conclusion to buy. If you have a long sales cycle and you’re trying to understand which channels push prospects from the nurture phase to the bottom of the funnel, this could be a good model for you.
Since the Time Decay model gives credit to every marketing touch point, it works well for stores with a large amount of repeat customers. These customers come across different advertising and marketing methods, so using the Time Decay model can help you find what is driving repeat conversions.
The Data-Driven attribution model, also known as Algorithm-Based attribution model uses Google machine learning technology to give credit to the most influential channels in the conversion process.
If you are running marketing campaigns across multiple platforms or running multiple campaigns in Google Ads itself, you should go for the Data-Driven attribution model.
Since Data-Driven attribution works by crediting all the elements in a conversion funnel, businesses with huge spends should opt for it.
Lead generation campaigns are where the customer does not immediately perform an action. Customers come across remarketing campaigns and other channels before conversion. Hence, you will be able to identify which channel/campaign is most effective by using the Data-Driven attribution model.
Check how effectively we used Data-Driven attribution to help our client Lendingkart achieve 20% business growth.
Note: Data-Driven attribution has pre-requisites & is not available to all accounts. Know about Data-Driven attribution model requirements here. In case Data-Driven attribution is not available to you, select ‘Position-Based attribution’ for your lead generation campaigns.
Attribution modeling offers you a clearer picture of what channels work for you for a lead to convert. It gives credit to different channels & campaigns/keywords based on the model you use. Attribution models are simply meant to help you better understand how and why a person converted.
Wrong attribution models will lead you to make poor decisions, while right models will unlock some powerful data.
Do not just rely on any specific attribution model but select one based on your business objectives. If a specific model does serve your purpose, then pick a new model or even compare a few models. Include them in your campaigns to make a marketing decision and see if they drive any incremental revenue for your business.
What is the best adwords attribution model?
If you are looking for the best attribution model ad words, we’ll break it down for you. Attribution modelling is the method used to measure the financial effectiveness of a communication channel, along with the impact it has created on your business goals. The purpose of attribution modelling is to help you achieve your business goals, by highlighting what’s working and leveraging performance to increase profitability and reduce unnecessary expenditure. There are many models to choose from.
There is not one perfect or best attribution model. You can test what works best for you.
What are the different attribution models?
There are several different attribution models out there. Attribution modeling is a framework to analyse which touchpoints or marketing channels should receive credit for a conversion. Each attribution has a unique approach to distributing the value of a conversion across each touchpoint.. There are six common attribution models:
By analyzing these attribution models, you can get a better idea of the ROI for each marketing channel. There isn’t necessarily a “best” attribution model – you can simply choose one as your standard for reporting and analysis. Different factors, like business goals or buying cycles, can make one model better than another.
What is attribution model in google analytics? (KW: google analytics attribution models)
According to Google, Google attribution analytics models refer to the rules, or set of rules, that determine how credit for sales and conversions are assigned to touchpoints in conversion paths. For example, the Last Interaction model in Analytics assigns 100% credit to the final touchpoints (i.e., clicks) that immediately precede sales or conversions. First Interaction attribution assigns 100% credit to touchpoints that initiate conversion paths. There is no “best” or “perfect” attribution model.
You can choose one as your standard model for reporting and analytics purposes and determine what is giving you the best ROI. You can use the Multi-Channel Funnels and Model Comparison Tool to compare how different attribution models impact the valuation of your marketing channels.
How do I find the attribution model in Google Analytics?
If you have a Google Analytics account, you must have come across the by-now very common term, “attribution models.”
According to Google support, “You can use the Multi-Channel Funnels Model Comparison Tool to compare how different attribution models impact the valuation of your marketing channels.
In the tool, the calculated Conversion Value (and the number of conversions) for each of your marketing channels will vary according to the attribution model used. A channel that predominantly initiates conversion paths will have a higher Conversion Value according to the First Interaction attribution model than it would according to the Last Interaction attribution model.”
How do I set attribution model in Google Analytics?
Whether you’re setting an attribution model for the first time or switching from one model to another, here is a basic breakdown of how to do it in your Google Analytics account.
Amol has helped catalyse business growth with his strategic & data-driven methodologies. With a decade of experience in the field of marketing, he has donned multiple hats, from channel optimization, data analytics and creative brand positioning to growth engineering and sales.
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