6 types of Google Ads attribution models and when to use them
Like any analysis tool, Attribution Modeling is most effective when you have a clear goal: define your analysis questions, and make a plan for what you learn.
- Start by identifying your marketing goals. Are you focused on branding and awareness, lead generation, developing new business, or repeat business? Are your current campaigns meeting these objectives?
- Develop a basic outline for your customer journey, including path length, time to conversion, and the relevant marketing channels. You can find this information in the Multi-Channel Funnels reports in Google Analytics. Look for key details: does the path differ based on the first touchpoint? Does it differ by order size or product category?
- Think about how you assign credit to these interactions today – even if you’re new to attribution modeling, you surely have some sort of intuitive model. What would happen if you valued interactions in the path differently?
- Define the role and expected impact of each campaign element. When you start modeling, check whether the models match or contradict your expectations.5. Plan your next steps. If you learn that a certain campaign, source, or interaction is performing differently than expected, will you be able to take action to change it? Once you’ve identified your analysis questions, you should explore different attribution models and determine which are best suited to your marketing goals. It’s important to compare multiple models to learn about different aspects of your marketing program.
Gives all credit for the conversion to the last-clicked keyword
The Last Interaction model attributes 100% of the conversion value to the last channel with which the customer interacted before buying or converting. This model is extremely common – most likely you’re already using some version of it – so it’s a great baseline for comparison with other models.
Gives all credit for the conversion to the first-clicked keyword
The First Interaction model attributes 100% of the conversion value to the first channel with which the customer interacted. This model can help you understand which campaigns create initial awareness. For example, if your brand is not well known, you may value keywords or channels that first exposed customers to the brand.
Distributes the credit for the conversion equally across all clicks on the path
The Linear model gives equal credit to each channel interaction on the way to conversion. This model might be used if your campaigns are designed to maintain contact and awareness with the customer throughout the entire sales cycle. In this case, each touchpoint is equally important during the consideration process.
Gives more credit to clicks that happened closer in time to the conversion
The Time Decay model assigns the most credit to touchpoints that occurred nearest to the time of conversion. If the sales cycle involves only a short consideration phase – for example, if you’re running a one or two-day promotion – then interactions that occurred a week earlier would have less value than those during the promotion window.
Gives 40% of the credit to both the first- and last-clicked keyword, with the remaining 20% spread out across the other clicks on the path
The Position Based model allows you to assign credit based on position in the customer journey. The first position highlights campaigns that introduce customers, while the last emphasizes those that close conversions. This model can be used to give more credit to those interactions or to assign customized weights according to the position.
Data-driven attribution gives credit for conversions based on how people engage with your various ads and decide to become your customers.
It uses data from your account to determine which ads, keywords, and campaigns have the greatest impact on your business goals. You can use data-driven attribution for a website, store visit, and Google Analytics conversions from Search Network campaigns.
Data-driven attribution is different from the other attribution models, in that it uses your conversion data to calculate the actual contribution of each ad interaction across the conversion path. Each data-driven model is specific to each advertiser.
This means that when you’re evaluating conversion data, you’ll see which ads have the greatest effect on your business goals. And, if you use an automated bid strategy to drive more conversions, your bidding will use this important information to help you get more conversions.
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