Customer journeys have become increasingly complex. The demand for a seamless experience for all customers, regardless of their step in the funnel, or their chosen platform for information has revised the traditional customer journey. Understanding its complexity is key before conducting research into your brand’s customer journey.
The customer journey is the series of engagements and interactions a customer goes through with a brand, product, or business, starting from the moment they identify a problem or need to the point of making a purchasing choice.
It begins with the awareness stage, which is where customers have realised that they have a need to fill, or a problem to solve. Brand awareness may start with advertisement in traditional media (e.g. print, radio, TV) or an online campaign, but most likely these channels will have to play together.
Consumers may then move over to the stage of consideration, where they look for more information by browsing online product reviews, asking friends or consulting a local retailer. While comparing product features and prices, they may discover new brands or alternative products and start their journey all over again.
And at some point, they will make a purchase decision, deliberately or with the help of a little nudge. This is the decision stage.
After buying a product or service for the first time, your goal as a brand would be to keep them as loyal customers, posing as advocates for your brand.
Due to technological developments, and customers’ increasing demands for seamless experiences, the customer journey is more complex than ever.
This complexity is not just about the vast amount of different touchpoints, it is primarily about the many ways in which they can be combined and connected, to lead consumers down the customer journey. And to make it even more complex, different customer segments may prefer different journeys. Among all the possibilities, there could well be a relatively well-paved path to success for each of them. Therefore, it is no wonder that particularly researchers are expected to give orientation.
This challenge has many facets and data analysis is definitely one of them. Calculating the impact of single experiences on the overall brand perception or purchase likability in a Key Driver Analysis, can become quite complex. Attributing the success of a conversion to a single effort with Multi-Touch Attribution models, may begin to feel like an art rather than a scientific method. While these questions certainly deserve more attention, this article will primarily concentrate on the challenges faced by data collectors, such as Norstat, when conducting customer journey research.
The first challenge consists in getting an overview over all relevant touchpoints. These may be completely under the control of the brand (e.g. website, outlet stores), managed by the brand even though the medium is not owned (e.g. advertisement), but also completely out of a brand’s control (e.g. word of mouth). Even for medium-sized brands, the amount of different touchpoints can be somewhere in the hundreds and this makes it really hard to get a comprehensive overview.
The second challenge involves how to collect data about each of these touchpoints. Two primary approaches are available: actively asking people (active data collection) or passively measuring and observing (passive data collection). Determining which option is superior is not straightforward. It is necessary to ask actively when you can’t measure the interaction or engagement with a certain touchpoint. However, active data collection has its drawbacks, particularly when it comes to capturing perceptions that operate below the threshold of conscious attention but still influence consumers subconsciously. On the other hand, measuring through passive data collection also has limitations. Often, passive data provides only superficial insights and fails to reveal the emotional engagement associated with a touchpoint. For instance, knowing from geo-data that someone was near a billboard does not guarantee that the billboard was actually perceived.
And that brings us to the next challenge: How can we get access to as many data points as possible for a single customer journey? In a time where cookie tracking is becoming less prominent, it is essential to rely on other data points as well. You may track the comments of consumers on Social Media and perform a sentiment analysis on whether they are talking positively or negatively about your brand. You may trigger a short online survey after each purchase has been made on your website and ask about the customer’s experience. Whatever you do, there is probably no “one-size-fits-all”-approach and you have to become a bit creative to get all data collected.
Even if you manage to get everything together, you’re running into the next challenge: How can you connect all these dots to get to see the bigger picture? This is where our Integrated Data Services come into play. In the simplest case, you are able to collect data about every touchpoint for each individual in your study, enabling a straightforward analysis. However, having such a comprehensive dataset is rarely the reality. More commonly, you’ll have some data for each touchpoint with overlapping samples across different touchpoints. Unfortunately, in addition to that, there are often numerous missing values and data gaps. Modern statistical procedures will now allow you to estimate these blind spots from the known connections (e.g. Lookalike Audiences), but will also set requirements for data collections: You’ll have to have enough cases in these sample overlaps to draw the inference on the general customer.
Last but not least, we’re always collecting data for those who analyse and work it. This means all data has to meet some additional requirements in data analysis, especially finding a common KPI for all touchpoints to make them comparable. Given all the challenges above, this can become really tough. Other projects expected us to deal with different streams of live data and make all information available in an online dashboard. So depending on what the data should be used for, the last challenge consists in preparing all data for its users.
Taken all the points above into consideration, it should have become clear that research into customer journeys may turn out to be very different for different brands, different customer segments and different media environments. It’s probably not possible to map a path that works for everyone. This is why our project managers will be happy to discuss an individual solutions with you that exactly meets your requirements. Get in touch with us and learn, what we can do for you.
Please let us know, what challenges you’re up to. We’re keen on becoming part of your success story.