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There are more ways than ever for companies to engage with their customers. According to Upland BlueVenn, retail customers interact with brands on up to 20 different marketing channels! As the customer journey becomes more complicated with each new potential touchpoint, assigning value to each of these channels is becoming increasingly difficult. That’s where attribution modeling comes into play.
Marketing attribution helps marketers assess the performance and success of the various marketing channels based on key objectives and goals. There are countless models that can help you and your marketing team determine channel success, so it’s important that you understand the differences and their impact on performance.
With so many options, how do you choose which attribution model to use for your campaigns? Let’s walk through the most common marketing attribution types, including various single-source and multi-touch models. Below, you’ll find easy-to-follow examples and the pros and cons of each.
Last-touch (also known as last-click) attributes 100% of the conversion to the last action in the customer journey. This touchpoint could be a visit from a PPC ad, a download of a gated resource, or even a click from your email marketing program.
Because you are only looking for the most recent action, this is one of the easier models to apply to your marketing activities. It’s even the default attribution model in Google Ads.
Simple, straightforward insight into lower-funnel attribution
Highlights key customer actions immediately before purchase/conversion
Does not show user’s full path to conversion, only the last interaction
Lack of insight into higher and mid-funnel marketing tactics
While this model is one of the simpler attribution structures, last-touch can still be very useful for products or campaigns that target low-funnel customers who are closer to a purchase decision. These users are much more likely to convert on “buy now” or “purchase today” calls to action.
Many ecommerce brands benefit from last-touch attribution, especially those that are focused on marketing tactics in the lower third of the marketing funnel. Some high-impact, low-funnel tactics include paid search, paid social, shopping advertising, or even remarketing digital advertising efforts.
The first-touch attribution model assigns 100% of the credit to the first interaction in the customer journey. Think of it as the opposite of last-touch. Ignoring all engagements beyond that first interaction, first-touch offers a good look into top-of-funnel and brand awareness marketing tactics.
Both first- and last-touch attribution models are considered “single-source” attribution, meaning they only consider a single interaction when assigning channels or tactic success. For that reason, they are not always the most effective at factoring in advanced, multi-channel marketing strategies.
Does not show user’s full path to conversion, only the first interaction
Lack of insight into mid- and lower-funnel marketing tactics
Not an accurate look into the full, multi-channel conversion process
With its similarities to last-touch, first-touch attribution works best on simple, straightforward campaigns with a limited number of customer touchpoints. This model works well if your brand is just getting started with marketing implementation, or you are hyper-focused on “awareness” or high-funnel tactics.
If your organization is also struggling to gain traction with inbound leads, first-touch allows your team to really dig into those early-funnel activities that drive brand awareness and increase the number of incoming marketing qualified leads.
Linear attribution is the most straightforward of the multi-touch attribution models. This model assigns equal weight to every interaction in the customer journey. For example, if your customer engages with four touchpoints — they click a paid search ad, read a blog, download an ebook, and then convert from an email newsletter — then each of these interactions would receive 25% of the credit for that conversion.
While this multi-touch model offers a better look at the full journey, it’s very rare that each interaction is equally important to the final conversion or purchase. While the weight of channel importance may be lost with Linear Attribution, it still provides more context for understanding user flow through the journey.
More insight into the full customer journey and relevant marketing tactics
Allows you to optimize throughout the customer journey as opposed to just the first and last interactions
Data could be skewed as each interaction gets equal weight
Linear does not take into account which specific engagement was the most important to the customer journey
Linear attribution models are best used when your organization is working on a limited budget, but your campaigns require multiple touchpoints before a purchase. This model works well for B2B sales cycles that require multiple touches and more time spent in the consideration phase of the funnel.
Like the example above, if you develop three campaigns — each with social ads, a blog, an ebook, and an email newsletter — linear attribution will help determine which campaigns are driving the most return, but offer little context as to which tactic is driving conversions, or that final meaningful action.
Taking a step beyond linear attribution’s equal weight for interactions, time decay gives credit to different channels using an "exponential decay" formula. This means that interactions near the end of the journey are weighted with more credit than activities closer to the top of the funnel. This attribution model hinges on the hypothesis that interactions closer to the conversion have greater impact than earlier journey interactions.
While this model may provide a more advanced look at your marketing tactics than others, its effectiveness depends on how impactful top-of-funnel activities are for your customers. Sending surveys or holding focus groups may help you better understand if time decay attribution is right for your organization.
Better insight into long sales cycle products or services
Takes customer journey length, time, and the importance of interactions into account
Only uses a time-bound formula to provide weighted credit to channels
Does not take into context the actual impact of interactions outside of sales cycle timing
This attribution model is particularly useful for high-consideration products and services when marketing qualified leads may take longer to arrive at a final conversion. It’s very similar to linear attribution, but it takes into consideration the impact of lower-funnel tactics and weighs them accordingly.
Time-decay attribution can be applied to high-value ecommerce purchases, such as high-end furniture. While a high-end furniture brand would certainly be interested in the impact of high-funnel tactics, like display or social advertising, they would also understand that an “abandoned cart” email campaign or product-specific retargeting has more impact on a customer’s final decision.
Data-driven attribution gives credit to interactions based on how your customers have engaged with various touchpoints in the past. This involves using data from past conversations to determine which tactics actually have the greatest impact on future conversions. As this model is entirely based on the existing marketing data you have available, it provides a custom, comprehensive look at your customers and the touchpoints along the sales cycle.
This model is especially valuable because it also compares individuals following the same journey to track where customers fell out of the sales cycle. Identifying these gaps or weak points in the journey provides more insight into your marketing efforts than a simple, single-source approach.
Most comprehensive model when weighting success of channels based on historical conversion data
Removes guesswork from customer journey and offers the best option for channel optimizations
This is the most complex of the attribution models listed and requires the most time and effort to set up
Works best with high-volume conversions to better optimize channel value
By far the most complex of the models listed, data-driven attribution allows brands to benchmark tactical performance against themselves, providing the most comprehensive look at the customer journey. This attribution model tends to work best for complex sales cycles with many individuals involved in the buying journey.
For example, if you work for a B2B software company, you may be creating tactics like display ads to target marketing managers to demonstrate the value of your platform. However, segmenting CEOs or CTOs — who have the power to make purchasing decisions — in an email journey may carry more weight than those initial display ads. This will help you allocate future marketing funds and prioritize high-impact actions.
The greatest benefit of exploring attribution models is the ability to gain more insight into the marketing tactics and plans your team is employing. These insights can help you optimize the customer journey and allow you to spend more time on the interactions that have the greatest impact for your brand — and your customers.
Ultimately, choosing the right attribution for your organization involves aligning your strategic objectives, active channel mix, marketing tactics, and the context of your customer journey. Taking all of those factors into consideration should help you make the best choice as you look to gather more insights into your audience and report marketing success to the rest of your organization.
Ready to start assessing your current attribution model? Reach out to our team of digital marketing experts and start making optimizations that can move the needle for your customers today.