Are you using the right attribution method for your organisation? | DMA

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Are you using the right attribution method for your organisation?

Using the best attribution method for your brand can enable you to see where to focus marketing spend and more importantly, it can enable you to improve the customer experience. But are you using the right attribution method?

Our recent research found most marketers (69%) agree that accurately attributing value across channels is vitally important to their organisation, yet the majority (82%) say they are using a single-touch point method, such as first-click and last-click attribution, to evaluate the success of marketing. And only 3% strongly disagree with their organisations approach.

Using a basic approach to attribution often results in a distorted view of the impact of campaigns, and where you should focus spend. More importantly, it means you are missing out on vital information that helps to understand your customers so that you can improve their journey.

The three biggest attribution challenges

1. Measuring in isolation

One of the main challenges with attribution is that departments and specialist agencies measure channels in isolation. By measuring the impact of one channel at a time (e.g. PPC), you aren’t looking at the holistic customer journey.

As you know, when a customer engages with your brand, they are likely to do so across multiple touch points. For example, they may see a TV ad, search for it on the internet and see a display ad, before purchasing a product. This combined effort drives the sale, yet marketers still aren’t recognising attribution across all channels.

2. Subjectivity

People decide which attribution model to use, which channels work best, what weightings to apply to engagements and so on. These opinions drive the output, giving a skewed and inaccurate view of the impact of campaigns.

3. Using the wrong method for your organisation

Different attribution methods yield pros and cons and need to be suited to your business structure – rather than what is the simplest approach.

For example, if a business decides to use a last click model, marketing channels that are efficient ‘closers’ in the customer journey will be highly valued, and channels that drive awareness or consideration will be undervalued. This will result in a marketing strategy that is efficient in the short term but does not build for the future.

Weighing up the methods

There is no silver bullet solution for attribution. The approach you should take will depend on your goals.

Here’s a quick overview of the pros and cons of some of the most commonly used attribution methods, starting with the most basic:

Single touch (first/last click)

This method assigns 100% of the revenue credit to a single touch point – the customer’s first or last interaction.

First click

Pro: Helps to decide where marketers should invest top-of-funnel spend – hence why it is suitable to companies with short sales cycles

Pro: Relatively low-level complexity so easy to implement and requires low level investment

Con: Results in high weighting on brand awareness

Con: Ignores the efforts that processed a lead through the marketing funnel

Con: This makes it difficult for marketers to make informed decisions on strategy in the middle and bottom of funnel

Last click

Pro: Gives insight into the touch points that are converting the most leads

Pro: Relatively easy and cost-effective to implement

Con: Tends to result in marketers focussing spend on one piece of activity – the last touch point before a sale (under-numerating what works throughout the rest of the journey)

Con: Ignores the efforts that first engaged and continued to engage a lead through the marketing funnel

Linear multi-touch

This method considers all the touch points that a customer interacts with throughout their purchase journey. This would be best suited to a short buying cycle with minimal research. For example, buying flowers as a gift.

Pro: Provides more information on the full customer journey than single touch-point attribution

Pro: Evenly distributes credit – less likely to focus too little or too much spend on one channel

Con: Still a relatively simple model - assumes all interactions are weighted the same (e.g. email interaction and an event attendance which could result in investment in less effective campaigns)

Con: Taking part’ gains credit so increasing any marketing activity (e.g. serving more display ads) will increase value attributed to that channel, which will result in more investment in that channel

Con: More complex than single-touch so can be more challenging/costly to implement

U-shaped multi-touch

This model gives credit to each touchpoint in the customer journey, but rather than giving equal credits to all, it assumes a different importance for the first and last events and then shares the rest of the credit equally across the remaining touch points. Consider marketing across a customer journey from introducing (first event) to closing (last event) with all middle points as promotors, the U-shaped model can be flexed based on business understanding.

For example, for a long buying cycle with lots of research (e.g. a holiday) during ‘consideration’, promoting touch points will be important. In this case the model may be designed to divide a large proportion of the value between middle touch points. In contrast for a product with a short buying cycle (e.g. a washing machine) then it is likely that the introducer will get most credit followed by the closer with any promotor touchpoints being assigned minimal value.

Pro: More sophisticated model that tracks every single touchpoint

Pro: Gives credit to multiple touch points throughout the customer journey

Con: Relies on subjective opinion

Con: Length of buying cycle and number of touchpoints impacts the value given to promotors regardless of genuine impact

Con: More complex, requires assumed understanding of customer journey to choose weightings

Channel weighted

For this model, channels are given different weightings/rules. These models are more sophisticated because they consider both position in the customer journey (first, last, middle) and the natural (assumed) strength of the channel. They are also more complex, adding an extra layer of subjective rules. This model is still rules based but is sometimes wrongly named data-driven.

Pro: More sophisticated model - tracking every single touch point

Pro: Applies different weighting to touch points

Con: More complex to design and build

Con: Relies on subjective opinion

Con: Doesn’t take in to account interactions across the customer’s lifetime

All the rule based attribution models described above have the same issues. The two most fundamental of these are:

  1. The danger of the self-fulfilling prophecy – the value attributed by these methods will drive future investment, so what you choose to value will receive more investment over time.
  2. They are all subjective – this underpins the inherent flaw in rule based models. It is a human decision to choose the shape and is therefore biased.

The only way to eliminate subjectivity and gain an impartial measure of marketing effectiveness is with a true data-driven model.

Cross-channel data-driven approach

In a true cross-channel data-driven model the individual level data defines and drives the shape of the model – not a human. This means the results aren’t skewed by opinion. Moreover, with this model, all channels are valued accurately, creating a clearer view of where marketing is having its greatest impact.

For a truly data-driven model, it is best to pull in individual level online customer data to create a fuller picture of the customer journey. This new data set helps to better understand which channels work best but it also provides insight that enables you to do further analysis to tailor communications to customer and prospects channel preferences.

This is best for all products but critical for those with a long buying cycle, or where multiple purchases is likely.

Pro: Gives non-subjective, weighted credit to multiple touch points throughout the customer journey

Pro: Quantifies the impact and role of each channel in the path to purchase

Pro: Determines the ROI by channel (and at a more granular level – depending on data capture)

Pro: Effectively merges multiple data sources – including click and impression data

Particularly sophisticated models also:

Pro: Enable you to attribute by customer segments

Pro: Can reflect the lifetime value of a customer – doesn’t treat each purchase as a separate cycle

Con: Is the most complex to implement (although not necessarily to use)

>> For more information on this approach, watch a recording of our recent attribution webinar. Or, download our advanced attribution guide.

Best practice guidance

The more sophisticated the attribution method, the more insight you gain to inform your marketing campaigns and to advise agencies of the impact. This gives you back control and enables you to take the guess work out of marketing.

To help you get the most of your models, we have put together a quick check list:

  • Start with a solid big data platform

Ensure you have one platform with quality and completeness of data

  • Capture individual level data

Make sure you capture online and offline interactions at an individual level to ensure your data platform offers a single customer view (look out for tools like Almanac that can help you with this!)

  • Choose the model that is right for you

Weigh up the pros and cons and select the model that is best for your objectives

  • Focus on customer outcome

Try and aim for the more sophisticated models if you want to improve the customer’s experience. Focusing on a model that combines individual’s purchases, and doesn’t show them as separate journeys is key!

  • Remain impartial

Don’t rely solely on agencies for insight and direction – they can’t see the full picture of the impact of your campaigns and so can only inform on the channel they are tasked with

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