What Is Multi-Channel Attribution?

For most companies in 2019, the typical customer journey involves many different online and offline touchpoints that ultimately influence prospects to purchase or convert. It is vital to understand which touchpoints were responsible for a given conversion and how much credit to assign to each of them – multi-channel attribution is the process of figuring out this information. This type of marketing attribution generates insight into the channels involved in conversions, making clear the extent to which organic search, paid advertising, or phone calls helped in driving a company’s customers to convert.

Why is it important for businesses?

It can be difficult to establish which of your marketing channels are contributing the most towards conversions, particularly when your company uses a wide range of different channels. Without understanding this, it’s impossible to decide which channels to prioritise and where to spend your marketing budget.

The Online Marketing Institute estimates that, on average, customers encounter between 7 and 13 different touchpoints prior to converting. A typical customer journey may not be linear – it could involve multiple breaks and returns to the journey before the customer finally converts.

Consider the following example: a prospect searches for a product on Google. Your brand bids for the keywords that the prospect has used, so your pay-per-click ad features in the results page and the prospect clicks on it. They then decide to research your competitors and compare prices. A few days later, they see an ad for your brand on another website and return to sign up for your newsletter. The prospect is reminded to look into your company when they receive your newsletter email, prompting them to search for your brand and click-through on your organic listing before converting.

Even in this simple customer journey, several different touchpoints are involved before the prospect converts. Multi-channel attribution can help firms to track the impact of each of these touchpoints on the overall sales funnel and determine which channels to focus on in order to drive growth in the future.

As a result, multi-channel marketing attribution models can increase the efficiency with which resources are spent on different channels. They can also help to provide evidence that spending on marketing channels is justified. Multi-channel attribution can even assist companies with working out which customer journey pathways are preferred by different target segments, enabling firms to optimise the content of each touchpoint to suit the demographics that frequently convert after encountering them.

To summarise, it is important that businesses utilise multi-channel attribution because:

  • It helps to determine which touchpoints to focus on and invest in
  • It justifies marketing spend on different types of channel
  • It establishes which channels help to drive conversions with different segments.

What are the advantages of different multi-channel attribution models?

But how should the credit be split across the various touchpoints in the customer journey? A range of multi-channel attribution models exist. Each type of marketing attribution model has different rules for assigning credit to the channels involved in the sales funnel.

Broadly speaking, these marketing attribution models can be split into two categories: those which credit one of the touchpoints and those which credit multiple channels.

Single touchpoint models include:

  • Last interaction
  • Last non-direct click
  • Last ads clicks
  • First interaction

Multiple touchpoint models include:

  • Linear
  • Time decay
  • Position-based

Last Interaction

Discounting all of the prior touchpoints in the sales funnel, this marketing attribution model assigns all of the credit to the last interaction the user had before converting. Whilst this model is easy to implement, the main disadvantage is that the influence of various other channels in the customer journey is not accounted for.

Last Non-Direct Click

The same rules, advantages, and disadvantages apply as in the last interaction model, but all direct traffic to the site is ignored. This model is less useful in cases where a large number of conversions stem from users visiting the site directly.

Last Ads Click

This attribution model assumes that the last ad a user clicked prior to converting is the most significant, assigning all of the credit to this ad. As with the last interaction model, the influence of all other marketing channels are ignored when implementing a last ads click model. you can download ms office from microsoft and get ms office 2007 product key from here to see the analytics report.

First Interaction

This form of marketing attribution only credits the first marketing channel involved in the customer journey. For example, a user could find a company organically on a Google results page then click on an email and a pay-per-click ad from that company before converting on its website. If the rules of the first interaction attribution model were followed in this case, then only the organic search result would be credited.


A linear attribution model is the simplest of those which take into account multiple channels that influenced the conversion. Utilising this model, each and every channel in the customer journey is credited equally. Whilst this type of attribution model is easy to set up, it is not the most accurate – for most firms, it is unlikely that each touchpoint is equally involved in encouraging a user to convert.

Time Decay

Working on the assumption that touchpoints closer to the conversion are more significant – yet still crediting multiple touchpoints – the time decay attribution model assigns an increasing amount of credit to channels that featured later in the customer journey. This model operates using a fixed “half-life” value that is designated at the start: if a half-life of 5 days was set, then a channel that was interacted with 5 days prior to the conversion would receive half of the credit that was assigned to an interaction immediately before the conversion. This marketing attribution model may be advantageous for companies with longer sales funnels that require a lot of input to encourage users to convert.


A position-based attribution model allows for more customisation than the other types we have discussed so far. A designated percentage of the credit for the conversion is assigned to the first and last interactions with channels in the sales funnel, then the remaining percentage of the credit is split evenly across all of the other channels involved. This form of marketing attribution model results in a U-shaped curve of credit applied across all of the channels and is advantageous because of its customisability, allowing the user to decide which touchpoints are most important.

Tips for setting up multi-channel attribution

Multi-channel attribution can be set up using standard analytics platforms such as Google Analytics.  Before this can be achieved, e-commerce settings must be activated or goals must be set in Google Analytics. This helps to identify which types of interactions should be considered conversions, allowing Google Analytics to recognise when multi-channel attribution should be implemented.

The standard reports in Google Analytics operate using the last interaction model (assigning all of the credit to the last touchpoint in the customer journey). By contrast, the multi-channel funnel (MCF) reports allow credit to be assigned to all of the channels involved in each conversion. The MCF reports also provide insight into the number of times a channel was the last click before a conversion compared to those times where it assisted in influencing conversion.

In the Overview MCF report, users can visualise which touchpoints commonly work together to drive conversions using the conversion overlap analysis visualisation. The Assisted Conversion MCF report provides the ratio of the last click to conversion assists for each touchpoint, as well as enabling the user to view trends in this data over time.

Top Conversion Paths, the next MCF report, enables the user to visualise the ten most common paths that their customers have taken prior to conversion – this provides insight into the order in which touchpoints are commonly interacted with and the number of times users usually interact with each touchpoint. The length of each conversion path can also be viewed in the Top Conversion Paths report.

The Time Lag MCF report is useful for revealing how long it takes visitors to convert from the point of their first session. The Path Length MCF report is similar to the Time Lag report, but considers the length of time taken to convert in terms of the number of interactions.

A final useful tip on implementing multi-channel attribution through Google Analytics is the use of the platforms in-built segmentation capability. As with other types of report, the MCF reports can be viewed in the context of which user-defined segments were involved.

Having set up a means of analysing online touchpoints using an analytics platform, a vital further step is to establish call tracking. This is particularly important for companies that generate business via phone calls, considering them to be a form of conversion within the sales funnel.

Without call tracking, it’s impossible to determine the previous steps in the customer’s journey prior to phoning up. Utilising a call tracking service provider, such as Calltracks, gives companies insight into the touchpoints which influenced a given prospect to call up. This enables firms to establish which combinations of marketing channels are most effective at driving calls and generating leads despite the fact that phone call conversions take place offline. Armed with this information, companies can optimise their online marketing campaigns to generate leads in the most efficient way.