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Amol Ghemud Published: August 17, 2020
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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.
What are Google Ads attribution models?
Attribution-Models
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.
Why does it matter?
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.
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.
What happens if you change the attribution model in between?
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.
Which attribution model is best based on industry?
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.
Which attribution model should you choose?
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:
First Click
Last Click
Position-Based
Linear
Time Decay
Data-Driven
Google Ads Attribution Model
Let’s find out which attribution model you should choose based on your business objective.
Objective: Brand awareness
Attribution Model: First Click
What does it measure?
This attribution model attributes all credit for leads/sales generated to the original source.
First Click Attribution
When to use it?
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.
Most effective
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.
Objective: Email Marketing
Attribution Model: Last Click
What does it measure?
This attribution model attributes all credit for leads/sales generated to the last marketing touch point.
Last Click Attribution
When to use it?
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.
Most effective
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.
Objective: Sales & ROI
Attribution Model: Position-Based
What does it measure?
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.
Position Based Attribution
When to use it?
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.
Most Effective
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.
Objective: Subscription
Attribution Model: Linear attribution
What does it measure?
Linear attribution model attributes equal credit for leads/sales generated to all the marketing touch points irrespective of their role in the sales cycle.
Linear Attribution
When to use it?
Use the Linear attribution model if you’re running a subscription service business that depends on periodic revenue and ongoing engagement with your product.
Most effective
The Linear attribution model is effective to measure overall brand reach & revenue, and to see which channels are consistently influential during a customer journey.
Objective: Maximize Repeat Customers
Attribution Model: Time Decay
What does it measure?
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 Attribution
When to use it?
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.
Most effective
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.
Objective: Lead Generation
Attribution Model: Data Driven
What does it measure?
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.
Data Driven Attribution
When to use it?
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.
Most effective
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.
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.
Conclusion
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.
Last click: This is the default setting for Google Ads and Google Analytics. It gives credit for conversions/sales/ whatever your goal is to the last-clicked keyword or ad, etc.
Free click: First Click gives credit to the channel or keyword that first drove traffic to your site.
Linear model: The linear model of attribution works by equally distributing the credit to every interaction a user takes before converting.
Time decay model: This gives maximum credit to actions that happened closer to a final conversion.
Position-based model: Position-based modeling gives 40% of conversion credit to both the first and last touches and 20% to the remaining clicks on the journey.
Data-driven model: It uses Google machine learning technology to give credit to the most influencer keywords in the conversion process.
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:
First Interaction
Last Interaction
Last Non-Direct Click
Linear
Time-Decay
Position-Based
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.
In your Google Analytics dashboard, click Conversions > Multi-Channel Funnels > Attribution > Model Comparison. This allows you to view the various default models offered in the platform.
Visit your first Campaign page, and then click in the Keywords tab to view the reporting table.
Click on Columnsà Custom Conversions à Google Analytics
Next click on Create to create a new column. This is where you select an attribution model, where campaign performance data will be filtered.
From a list of options, choose your metric; this will be the attribution model used to understand your data.
Click Save to use this model going forward.
Watch: Google Ads Attribution Models Compared
For Curious Minds
An attribution model provides the rules for assigning credit to each ad interaction along a customer's conversion journey. This is vital for accurate ROI measurement because it prevents you from overvaluing the final click and ignoring the crucial touchpoints that initiated and nurtured a prospect's interest. Without it, you risk misallocating your budget to only closing channels. A customer journey is rarely linear; the content indicates it takes 7-13 touches for a lead to convert. A last-click model would ignore the first six to twelve interactions, making your awareness and consideration campaigns appear worthless. By selecting an appropriate model, you can:
Identify your most effective prospecting channels that introduce new customers.
Understand the supporting role of mid-funnel content and remarketing ads.
Make informed budget decisions based on a complete view of the conversion path.
This holistic perspective, powered by a well-chosen Google Ads attribution model, is the key to building a sustainable and scalable advertising strategy. You can start uncovering which channels are the unsung heroes of your campaigns by exploring the models further.
An attribution model provides a necessary framework for navigating the complexity of a modern customer journey. It establishes a set of rules to distribute credit for a conversion among all the different ads a user interacts with, from initial awareness to the final purchase. This prevents the common mistake of assigning 100% of the value to the last ad they clicked. The 7-13 touches metric proves that multiple interactions, including those with RLSA and display remarketing ads, collectively influence a conversion. Choosing the right model helps you quantify the impact of each touchpoint. For example, a time-decay model gives more credit to interactions closer to the conversion, while a linear model distributes credit equally, acknowledging every step's contribution. This structured approach allows you to see which channels excel at initiating contact, which are best for nurturing leads, and which are most effective at closing sales. Evaluating how different models assign value is the first step toward optimizing your full-funnel strategy.
You should use these two models to answer two entirely different strategic questions about your campaigns. A first-click model is designed to identify top-of-funnel success, while a last-click model measures bottom-of-funnel performance. Comparing them reveals the distinct roles your ads play in the customer journey. A first-click attribution model assigns 100% of the conversion credit to the very first ad a customer interacted with. This is ideal for answering, “Which of my campaigns are most effective at introducing new prospects to my brand?” It highlights your best demand-generation efforts. In contrast, a last-click attribution model gives all credit to the final ad clicked before conversion. This model answers, “Which campaigns are most effective at closing deals and driving immediate sales?” It helps you identify your strongest call-to-action ads. Using both models provides a balanced view: one shows you what starts the conversation, and the other shows you what finishes it. Understanding this distinction is key to creating a truly effective full-funnel strategy.
This metric directly exposes the core flaw of last-click attribution: it completely ignores the majority of the customer's journey. By assigning 100% of the credit to the final touchpoint, it creates a distorted view of performance where only the closing ads receive recognition, while the crucial introductory and nurturing interactions are deemed worthless. When a conversion requires an average of 7-13 touches, a last-click model effectively disregards up to 90% of your marketing efforts for that sale. This disproportionately penalizes top-of-funnel and mid-funnel campaigns. The types of campaigns that lose credit include:
Awareness Campaigns: Broad display or video ads that introduce your brand to new audiences.
Content Marketing Promotions: Ads driving traffic to blog posts or guides that educate prospects early on.
RLSA Campaigns: Search ads that re-engage users who have visited your site but are not yet ready to buy.
Shifting to a multi-touch model is the only way to accurately value these essential, early-stage interactions within Google Ads. To see the true impact of all your campaigns, you must look beyond the final click.
Marketers can justify budgets for assisting channels by shifting the conversation from direct conversions to assisted conversions and total pipeline contribution. The 7-13 touches metric is powerful evidence that sales are a team effort among your channels, not the work of a single hero ad. A last-click model hides this teamwork, but a different model can reveal it. To build your case for channels that play a supporting role, you should focus on data that highlights their influence across the funnel. Use these approaches within Google Ads:
Analyze Assisted Conversions Report: This report shows how many conversions a specific campaign, ad group, or keyword participated in, even if it wasn't the final click. A high assist-to-last-click ratio proves its value as a setup player.
Switch to a Multi-Touch Model: Implement a linear, time-decay, or position-based model. These models assign partial credit to every interaction, providing a direct monetary value for the assists.
Examine Top Conversion Paths: This report visualizes the most common sequences of channel interactions leading to a sale, making the collaborative nature of your marketing tangible.
By presenting this data, you can prove that cutting budget from an “assisting” channel could cripple the performance of your “closing” channels. Discover the hidden value in your campaigns by adopting a broader measurement perspective.
A practical approach is to start simple and evolve your model as your understanding of the customer journey deepens. For a new business, immediate sales are often the priority, but a more nuanced view should be the goal. This phased strategy ensures your measurement aligns with your business maturity. Here is a recommended stepwise plan:
Step 1: Start with Last-Click (Temporarily). For the first 1-2 months, use the default last-click model. This provides a basic, albeit flawed, baseline for what drives direct sales and helps you get campaigns off the ground quickly.
Step 2: Move to a Rules-Based Multi-Touch Model. Once you have consistent conversion data, switch to a Time-Decay or Position-Based model. These offer a more balanced view by crediting touchpoints throughout the journey without being overly complex. This is the ideal stage for most growing businesses.
Step 3: Evaluate Data-Driven Attribution. After collecting sufficient conversion data (as defined by Google Ads), consider switching to the data-driven model. This uses machine learning to assign credit based on your account's specific performance patterns.
The key is to transition when your strategic questions change—from “What sells now?” to “How do customers discover and decide on us?” This evolution ensures your attribution model always reflects your business objectives. To find out if you have enough data for the next step, consult the model comparison tool in your account.
A smart marketing team uses multiple attribution models not to find a single “best” one, but as different lenses to answer distinct business questions. The Model Comparison Tool in Google Ads is designed for this exact purpose, allowing you to see how conversion credit would shift if you changed models, without actually making a permanent switch. This allows you to gain multifaceted insights from the same dataset. To identify your best channels for different funnel stages, follow this process:
To find prospecting channels: Use the First-Click model. Look at which campaigns or keywords receive the most credit under this model. These are your best initiators and are responsible for filling the top of your funnel.
To find closing channels: Use the Last-Click model. The campaigns that excel here are your most effective closers, prompting the final action from ready-to-buy customers.
To understand the entire journey: Use a Linear or Position-Based model to see which channels consistently appear in the middle of the conversion path, acting as crucial nurturing touchpoints.
By switching between these views in your analysis, you can build a complete map of your customer journey and allocate budget more effectively. This technique transforms attribution from a simple setting into a powerful analytical tool.
As privacy changes make third-party tracking less reliable, your choice of attribution model will become a cornerstone of strategic decision-making. With less granular data available, the model you use determines how you interpret the signals you can still collect, directly impacting your perceived campaign performance and budget allocation. Relying on last-click becomes even riskier in a privacy-centric world. Early-funnel interactions, often happening across different devices or sessions, will be the first to become unmeasurable with certain tracking methods. A last-click model will completely ignore these already-fading signals. In this future, you should:
Prioritize models that capture complexity, like Google's Data-Driven Attribution, which uses machine learning to fill in gaps where direct observation is lost.
Focus on directional insights rather than perfect, user-level credit assignment.
Supplement attribution data with broader analyses like media mix modeling (MMM) to understand performance holistically.
The strategic importance shifts from perfect measurement to intelligent estimation. Your attribution model is your primary tool for making sense of an increasingly fragmented and anonymized digital landscape. Learning to use it wisely is no longer optional.
The most significant error is creating a feedback loop that starves the top of the marketing funnel. By exclusively rewarding the final click, businesses systematically devalue and defund the very campaigns that introduce new customers, eventually leading to a shrinking audience and stagnant growth. This happens because last-click attribution makes awareness and consideration campaigns appear to have zero ROI. A switch to a more balanced model immediately corrects this distortion. A Position-Based model, for instance, assigns significant credit to both the first and last interactions, recognizing the value of both customer acquisition and closing. A Time-Decay model gives more credit to touchpoints closer to the conversion but still assigns value to earlier interactions. Both models acknowledge that the customer journey is a process, not a single event. By making this change, you give yourself permission to invest in brand-building and mid-funnel nurturing, confident that their contribution to the final sale will be measured and recognized. This shift is fundamental to achieving long-term, sustainable growth with Google Ads.
This problem stems directly from an over-reliance on last-click or other bottom-of-funnel attribution models. These models are designed to measure who gets credit for the final sale, not who initiated the customer journey, making your awareness campaigns look like a sunk cost even when they are critical for filling your pipeline. The solution is to use a model designed specifically to answer the question of customer origination. The First-Click Attribution Model is the best tool for this specific purpose. It gives 100% of the conversion credit to the very first ad a user interacted with on their path to becoming a customer. By applying this model, you can:
Identify which campaigns are most effective at generating new leads.
Justify spend on upper-funnel keywords or display placements that may not convert immediately.
Understand the true origin of your most valuable customers.
While you might not use first-click to manage your entire Google Ads account, it is an essential analytical lens for evaluating and optimizing your demand generation strategy. Adopting it for analysis helps you avoid the critical mistake of cutting off your most important sources of future growth.
The primary risk of inaction is making critical budget decisions based on flawed data, leading to wasted spend and missed growth opportunities. Sticking with the wrong model creates a distorted reality where you continuously invest in a few channels that appear to work while neglecting others that are secretly driving significant value. This can lead to a performance plateau or even decline. Choosing a more suitable attribution model helps resolve these inaccuracies by painting a more complete picture of the conversion path. For example, if your data shows strong performance only from branded search, a last-click model is likely hiding the generic search or display campaigns that introduced those users to your brand initially. Switching to a Position-Based or Linear model would redistribute credit, revealing the true contribution of those earlier touchpoints. This adjustment allows you to see how your channels work together as a system, correcting the data and enabling smarter, more effective optimization of your entire Google Ads portfolio. To begin fixing your data, you must first fix your measurement framework.
Multi-touch models provide more accurate insights for long sales cycles because they acknowledge that no single ad is solely responsible for a conversion that takes weeks or months. They distribute credit across multiple interactions, reflecting the reality of a prolonged consideration phase. This prevents you from mistakenly optimizing for only the final click when numerous earlier touchpoints were essential for nurturing the lead. The choice between different multi-touch models depends on your business philosophy:
Linear Model: Choose this if you believe every touchpoint is equally important in the customer journey. It's simple and values consistent engagement.
Time-Decay Model: Select this if you believe touchpoints closer to the conversion are more influential. It is ideal for shorter consideration cycles within a longer sales process.
Position-Based Model: Use this if you value the first touch (discovery) and the last touch (close) most highly. It's great for businesses that want to credit both prospecting and closing efforts.
Your decision should be guided by which narrative best fits your customer's typical path to purchase. Analyzing your conversion paths in Google Analytics can provide the context needed to select the most appropriate model for your unique business.
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.
Growth Strategy and Planning
