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Attribution modelling techniques are usually carried out with an aim to distribute the value of a sale to the contributing online media in order to optimise the online marketing mix towards an appropriate target.
But the value of click path analysis is far greater than attributing value to the small proportion of customers that actually purchase online. For most organisations transacting online, the majority of interactions with online marketing campaigns result in non-purchase.
These visitors can be segmented depending on the trends that are identified. Common methods of defining these segments are by the position within the purchase cycle, method of purchase or by the trends in media consumption.
Here are four potential uses of this information:
Evaluating the click path of a non-purchasing customer allows marketers to understand the actions taken by browsers in the consideration stage of purchase and to target this user with appropriate advertising in the future.
Taking a basic example, if a customer enters a travel website via paid search keywords relating to Egypt Holidays, this information can be used to serve relevant display advertising. There are of course, far more complex opportunities to retarget customers based on sequential non-purchase activity.
In my last post, I discussed the requirement for a better understanding of the benefits of investing in search marketing over and above direct acquisition based activity. Understanding trends in the media generating visitors to a site and not purchasing, helps with the apportioning of online media budgets.
For example, if a TV advert generates increased PPC activity on a particular asset, the information relating to non-purchase can be used as a performance indicator for the campaign. The marketing budget associated with these clicks can therefore also be attributed to the TV campaign.
The reasons for non-purchase are a great source of intelligence for any organisation. Click path analysis provides a quantitative insight into criteria such as pricing and product selection.
For example, if a customer has clicked multiple times from a price comparison site and not purchased, there is a strong possibility that this decision is price orientated. This information can be supplemented by qualitative data in the form of site departure surveys to gain a better understanding between person, price and product.
Just because a consumer clicks on a keyword and does not purchase, it does not mean that the click has not served any value. The customer has been exposed to the brand potentially facilitating access to their consideration set for future purchases. There comes a point however, when the true value of advertising must be take into consideration in the context of these non-explicit benefits and finite online marketing budgets.
Online marketers benefit from the ability to be able to easily identify cost within the intricate elements of a campaign. If a particular campaign is deemed expensive at inception, then click path analysis can provide tangible supporting evidence with which to renegotiate or reduce investment.
Click path analysis provides far more information about engagement with online advertising than merely insight into the path to purchase. Attribution data provides only a fraction of the information that is contained within recorded online marketing metrics as the majority of data is associated with non-purchase patterns.
Understanding and gaining meaningful insight from this vast quantity of data is a massive challenge for any organisation. But if this challenge can be met, the benefits in terms of increased performance efficiencies are long lasting.