With the big data buzz pervading the marketing world with relentless force, the last few years have been fruitful for marketing tool providers. Yet the boom has also fuelled wrong expectations about the understanding of digital customer journeys on the part of both consumers and businesses.

Consumers fear that companies can combine all their data into a holistic picture of their personalized journey throughout the internet, and the NSA and Facebook data scandals have supported that notion. Companies on the other hand believe that they have the data to derive any kind of customer journey based real-time segmentation, allowing perfectly customized offers and messages just with a turn of your finger.

To some degree, these beliefs are the unfortunate by-products of misleading advertising efforts with over-promising value propositions on the part of many tracking technology and service providers.

It’s high time to clear up the biggest misconceptions about customer journeys!

1. Everyone knows what a customer journey is

A customer journey is not a customer journey is not a customer journey. Technically speaking, a customer journey can be subdivided into the following parts:

• The Inter-Site Customer Journey refers to all the websites users visit before they visit the final website. Tracking these sites with time stamps and a unique identifier generates lots of data. Challenges are to match the data to a content ontology and to transfer it to the analytics platform.
• The Referrer Analysis is actually a subset of the first point and describes the last link before entering the analyzed website. This analysis is well sophisticated due to the need for attribution modeling – a main component of online media performance management.
• The On-Site Customer Journey commonly referred to as “customer journey” by e-commerce companies depicts all of the user’s interaction on a specific site.
• Finally, if available, the Login Customer Journey comprises of all parts behind an individual user login gate.

2. I can identify each customer on every step of his journey

Most service providers do not even follow a data-driven approach to derive an analytical understanding of customer journey; they rather draw up a qualitative and exemplary customer journey based on their target group insights. But even when the customer journey analyses are based on data, they often lack unique identifiers mainly due to complex multi-user situations and insufficient cross-device tracking solutions. Further, many ad blocking tools disable not only cookies, but also tracking infrastructures. Hence, customer journey insights can only be derived on an extrapolated perspective filling data gaps with projected information.

3. You can analyze your entire customer journey with one tool

Holistic customer journey tracking is an intelligent combination of inter-site digital customer journey tracking architecture, well tagged web-analytics for on-site and login customer journeys combined with the reach of third party cookie data and complemented with search and buzz analysis. From our experience, the only service portfolio provider coming close to a holistic customer journey tracking is Google.

4. Data-driven analysis is only limited to online touch-points

The concept of digital customer journey tracking techniques, even though not on a 1-on-1-perspective, can be extended to non-digital touch-points such as out-of-home, TV or radio. Search or buzz data can work as a way more effective resonator than traditional unique links and QR codes.

5. Existing segments can be instantly deducted from the customer journey

A common misconception is that existing customer segments are directly mirrored in the customer journey. Unfortunately, this is not the case. Segments, as used for personalization or marketing planning, have to be built in an iterative learning process. Setting up such a process and building the required database takes time and constant efforts.

6. I know everything about customer journey tracking

This is probably the most definite lie. The landscape of tracking providers is highly fragmented. Concepts and technologies are rapidly evolving side by side to almost infinite numbers of potential relevant touch-points. Asking the right questions as well as the smart selection and integration of data service providers and the corresponding analysis will remain an ongoing challenge.