The Customer Journey to Online Purchase

With the growth of online commerce, the path or journey undertaken by a customer to lead to a purchase decision has become increasingly complex. To use an analogy used by Nielsen in their 2013 Australian Connected Consumer Report, when you think of the landscape as a Rubik's cube, consumers rarely fit on one side; they fit across multiple blocks and their path isn't finite.

The result of this is that marketers need to start to rethink the way they view the customer journey in order to get a more accurate picture of their marketing efforts.

So while we understand that marketing channels such as email, display, paid search and social influence customers at different points, they in fact can also influence each other, meaning we shouldn't judge them in isolation.

Marketing activity has the ability to act as both an Assist channel, as well as a Last Interaction channel. Assist channels build awareness, consideration, and intent earlier in the journey. Conversely Last Interaction channels act as the final point of contact prior to a purchase conversion.

Assist vs Last Interaction.

Here lies the crux - even though a Last Interaction represents the point at which a  purchase was ultimately made, it does not necessarily understand or credit the work of previous channels in the lead up to the conversion.

Google has done a great job of providing new tools and research to help highlight this fact. There are some great visualisations based on analytic deep dives that break down the channel influence in a number of industries. Unfortunately it does not have Australia specific data, but it does helps visualise the differences.

US CPG Industry.

US Retail Industry.

US Finance Industry.

This leads us to Multi-Channel Funnels. A fairly new feature in Analytics, this repot is generated from the sequence of interactions (i.e clicks and referrals from channels) that lead up to each conversion and transaction. Virtually all digital channels can be added, and with a loopback window of 1-90 days, the data is a powerful addition to channel planning analysis.

Once you set up and get familiar with this data, you can also expand out into Attribution Modeling, a tool that allows you to easily experiment with your channel mix to drive the best results with minimal impact.

Probably the biggest challenge to a switch to this mindset will be agency alignment. If you have a range of different agencies responsible for social, search, digital media and platforms, they may tend to want fall back on only reporting on the channel they are responsible for (again in isolation). With a Multi-Channel view delivering a much more complete picture of your marketing efforts, forcing alignment ensures a much greater chance of revenue and conversion.


This post continues my series on Mental Models.