How skiing has inspired the evaluation of the digital customer journey
One of the reasons marketers like digital is its accountability – the ease of reporting impressions, clicks and sales events makes the channel a seductive one. The only problem is most brands are measuring the wrong thing. More specifically, they are measuring the right things, the wrong way. In doing so, they are effectively hobbling the performance of what could be their most effective channel.
Most online campaigns are measured against “last click” events, where the last event before a sale gets all the credit for that transaction. But as 95% of online transactions are preceded by multiple digital marketing touch points this approach is fundamentally flawed, since all the other events within a sales journey receive no credit.
Offline marketers have intuitively known this, but often struggled to measure the influence of - and synergies between - TV, Print and POS activity. Digital offers an inherent accountability that allows measurement of the true role each touch-point plays in driving sales.
There is lots of talk within the digital community of the concept of ‘assists’ – by which there is a tacit, but unquantified acceptance that whole swathes of digital investment (‘display’, ‘generic search’, etc) perform some form of priming role. However, there are few attempts to quantify the impact of these assists, and even fewer attempts to attach a monetary value to them.
To resolve this, we have spend the last 3 years looking at millions of online customer journeys, developing a framework that quantifies the role that each touchpoint plays, and attaches a value to it. This allows us to make granular investment decisions based on the true contribution each event makes. We call this approach Pistemap, since the diversity of speeds and routes that consumers taken along their online journey reminds us of the way skiers descend mountains.
For example, when we look at the journeys made en route to taking out a mobile phone contract, we see that some customers make short, direct journeys; others take more convoluted routes. Many get part of the way through the process before going back to the beginning again.
Using Pistemap, we are able to signpost this journey much more effectively than we would if we optimized the campaign using the last-click, purely by understanding where the busy “pistes” are, and prioritising investment along them. Planning convention says a mobile network shouldn’t spend vast sums on handset search terms, since they are too costly on a last-click basis.
Our Pistemap analysis for Orange identified the specific handset terms that featured further back in the customer’s journey when searching for a mobile phone contract. By assigning credit to these terms, were then able to see which ones were cost efficient (based on the journey). Moving away from last-click optimization, we based keyword investment on this insight, and boosted sales for Orange up 122% with a 42% increase in spend.
In display, we knew that there were a host of sites and networks that rarely created the last click before a sale, even if they felt ‘right’ for the brand. Consequently they weren’t featured on DR media plans. By using Pistemap to understand the role of display advertising on these sites in prompting a future purchase, we were able to boost the conversion rate for Orange by 13%.
Affiliate voucher codes for Ecommerce often appeared to drive sales, but Pistemap quantified the extent that this activity ‘stole’ sales from other channels, just because it was the ‘last-click’. By introducing measures to limit this effect, we were able to reduce cannibalisation of other channels by 25%.
The approach has allowed us to record changes in consumer behaviour as they move through the purchase funnel. This insight then forms the basis of a robust planning framework, which underpins planning for our clients, across a range of sectors. Pistemap analysis can effectively chart the routes consumers take on the way to converting – be that across digital channels or within channels such as paid search.
It allows marketers to effectively quantify the true value of every online campaign element.
Author: Martin Lawson, Head of Data, i-level