The customer journey can be a long and arduous one, calling at many ports before the decision to buy is finally made. As marketers, it’s important that we map the entire journey so we can understand which marketing touchpoints are vital navigation aids and which are merely signposts on an already clearly defined route. Marketing attribution helps us make sense of those customer journeys and optimize future voyages.   

Marketing attribution used to be a simple job. Full credit for a conversion was typically given to the first or last touchpoint, and everything else was essentially ignored. This rather unscientific approach often championed a dominant marketing channel like paid search and undervalued everything else. This could result in skewed budgets and underinvestment in equally important channels like email, social media, and content marketing. 

Every Marketing Engagement Has Value

Savvy marketers soon realized that they couldn’t ignore the various marketing touchpoints on the customer journey because every engagement has to have value. The problem was how to assign that value for every “marketing assist” along the journey. To solve this problem, marketers created a number of attribution models. While these attribution models certainly improved the marketers’ insight into their marketing success, they are far from perfect. Therefore, before deploying a specific attribution model, understanding each system’s pros and cons is essential. 

Last-Click Attribution

The original and still most commonly used attribution model. Last-click attribution grants all the credit for a conversion to the last-clicked ad and corresponding keyword. 

  • Pros of Last-Click Attribution: If you are looking for a simple attribution model, last-click attribution is as simple as it comes. But simplicity doesn’t come without its problems. 
  • Cons of Last-Click Attribution: Last-click attribution essentially ignores every marketing engagement before the last click prior to conversion. That may mean a cheap brand-related keyword gets all the credit after more expensive search keywords won the initial engagement, and carefully executed marketing automation campaigns nurtured the prospect until they searched for the brand by name with the full intention of buying. 

First-Click Attribution

First-click attribution essentially turns last-click attribution on its head and attributes all the credit for a conversion to the initial click. 

  • Pros of First-Click Attribution: Again, a very simple attribution model. First-click attribution may be advantageous compared to the last-click model because it highlights how your clients originally discovered your organization. 
  • Cons of First-Click Attribution: Like last-click attribution, the first-click model ignores the rest of the customer journey and may result in underinvestment in critical marketing strategies. 

Linear Attribution

The linear attribution model believes that all clicks on the customer journey are equal and shares the credit for conversion across all ad engagements. 

  • Pros of Linear Attribution: Linear attribution is an egalitarian attribution model which rewards every marketing engagement on your customer’s journey. This highlights the importance of marketing channels that may have previously lost out to more prominent channels. 
  • Cons of Linear Attribution: Unfortunately, not all steps on the customer journey are equal. In any competitive industry, where a prospective client may visit multiple brands before buying, you could argue that the marketing campaigns delivered between the first and final click are more important than the linear attribution model suggests. 

Time Decay Attribution

The time decay attribution favors ad engagements that occur closer in time to the conversion. The model typically uses a seven-day half-life rule. A click occurring eight days before a sale will only get half the credit of an engagement the day before conversion. 

  • Pros of Time Decay Attribution: Time decay attribution is ideal for marketers keen to promote a quick turnaround from discovery to conversion. This may suit marketers of Fast Moving Consumer Goods (FMCG) or consumable items for business customers. 
  • Cons of Time Decay Attribution: For more considered purchases, time decay attribution may give a false impression of the value of engagements that happen later in the customer journey. 

Position-Based Attribution

Position-based attribution is very similar to linear attribution, but instead of the egalitarian model, it weighs the credit in favor of the first and last click. While the first and final click each receive 40% credit for the conversion, the clicks in the middle of the journey take a share of the remaining 20% credit. 

  • Pros of Position-Based Attribution: Position-based attribution recognizes the first and final click are significant steps in the customer journey while also recognizing every other step in your marketing strategy has value. It also helps marketers judge the impact of their campaign strategy and potentially optimize the journey helping to shorten the time between first and final clicks. 
  • Cons of Position-Based Attribution: Again, for more considered purchases, the engagement between the first and final click may be more important than position-based attribution suggests. 

Data-Driven Attribution

Data-driven attribution assigns credit for engagements based on data that determines which campaigns have had the most significant impact on your conversions. 

  • Pros of Data-Driven Attribution: Data-driven attribution uses Google Analytics to examine website visits from Search, Shopping, YouTube, and display ads to give a more accurate understanding of how the customer journey led to conversion. By crunching so much data, data-driven attribution is considered the most precise attribution model available to marketers today. 
  • Cons of Data-Driven Attribution: You’ve probably guessed that this isn’t easy to set up and will require a significant investment in the implementation process and training. It also doesn’t consider marketing activities that happen outside of the digital realm. 

How Attribution Models Can Help Inform Your Marketing Automation and CRM Strategies

The more information you have about your customer engagements with your marketing campaigns, the more you can do to optimize the experience. 

Attribution data will help you fine-tune your marketing automation strategies by helping you understand how you win and (equally importantly) lose customers. Not only will this be beneficial when building workflows and creating content, but it can also be used to inform strategies like lead scoring. Lead scoring will not only help you deliver more appropriate messages based on your prospects’ position in the sales funnel, but it will also highlight the very hottest leads to your sales team. 

When attribution data is readily available in your CRM system, the process of reporting to the various stakeholders in your organization becomes much more manageable. This will improve cross-departmental communication and demonstrate to your leadership team where further investments need to be made in the marketing department. 

Start Mapping Your Customer Journeys

To learn more about how the marketing experts at emfluence can help you identify and deploy the most suitable attribution model for your organization and start mapping your customer journeys, contact us today at

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