Paving a Consumer’s Journey: From Research to Retrieval, and Data’s Role
Data is vital to understanding the customer journey, but how a brand uses it can be the difference between a winning customer experience and a lackluster one.
by Eric Matisoff
posted on 07-11-2018
Stop for a minute and think about all the different ways customers interact with your brand. They might hear about a new hotel or product from a friend’s Facebook post, check out a flashy ad about that same hotel through digital signage at an airport, or receive an email offer for a discounted stay.
Aside from promoting your offerings, these various touchpoints also can help gain insight into consumer behavior, which in turn allows you to market smarter and sell better.
Data is vital to understanding the customer journey, but how you use it can make the difference between a winning customer experience and a lackluster one.
Creating a framework for your customer journey analysis
Data helps marketers orchestrate the customer journey, but you must first have a framework for how you map it to the customer journey, how you measure what’s working and understand how to use it to course correct, or optimize, your promotions.
Start with a measurement plan that focuses on identifying objectives, goals, metrics, and targets for those metrics. An example of a plan could encompass a goal to increase awareness of a new campaign or a new hotel brand. Your goal will revolve around the tactics, which could include leveraging display media and paid search along with optimized campaign landing pages. Then the metrics associated with this goal would align with click-through and conversion rates associated with those campaigns, as well as conversion rates associated with each of the landing pages. Be sure to apply segments to these metrics that differentiate loyal versus new customers, device types, and geography.
Marketers then need to define what success looks like by putting measurable targets on your predefined metrics. If you’re trying to increase the number of hotel confirmations, for example, you want to quantify that into upper and lower targets: a 3 percent to 6 percent increase in first-time bookings over the next three months, for example. This is often where the customer journey planning process breaks down, but don’t let it. Instead, use a bracketing exercise to identify what would be truly awful for this campaign (a 0 percent increase) and what would be good enough to warrant a promotion (a 10 percent increase). Then, begin to slide those unlikely estimates to numbers that are a bit more realistic.
Starting with this framework is the basis for everything you should be doing when it comes to analytics and applying it to customer journey analysis.
There are two approaches you can take to customer journey analysis and how to leverage data for it: prescriptive or exploratory. They’re both important to helping you understand how to move customers further down the funnel. But any company that wants to deliver better customer experiences today needs to slowly move away from just dictating step by step how they want consumers to interact with their brand, and move toward identifying trends and uncovering insights about how various customer segments actually navigate their own path to purchase.
This is when you’ll find opportunities to optimize, to improve, and to learn.
The prescriptive approach to customer journey analysis
Data from a variety of touchpoints is critical to understanding your customers, but businesses often use this data in prescriptive ways — they prescribe marketing solutions by thinking, “What do I want my customer journey to be?”
Marketing personas are an offshoot of such a prescriptive approach. The soccer mom. The grill dad. The yoga enthusiast. As a marketer, you have carefully constructed personas as stand-ins for your customers. Armed with data, you then prescribe targeted messaging to be delivered by push notifications, advertising, as well as personalized emails and experiences.
These tactics need to be deeply analyzed — identifying where users are falling through your prescription and where they are falling out. Don’t forget to leverage those personas from earlier to see how and where they differ. Similarly, it’s important to create this fallout analysis at different levels of granularity in the journey. For example: a four-step funnel focused on key moments compared to a 15-step one that analyzes specifics like impressions, clicks, and page views.
Such a prescriptive approach shouldn’t be discounted — it’s served many marketers well for many years. But relying on it solely for all marketing prevents you from accurately mapping the journeys your customers actually follow.
How many times have you lost customers along the way because they were fed one offer too many or just saturated with the wrong message at the wrong time? This points to a problem with using only a prescriptive approach to consumer data. How else, then, can you view your data?
Exploratory analysis is another approach that can be very effective.
The exploratory approach
The exploratory method of data analysis also is powered by data from several different sources — online purchasing behavior, social media likes, shopping history, cross-channel promotion history, and more.
It goes without saying that people don’t always fit into only one box — a customer might not just be a soccer mom; she also might be a grill enthusiast and a working woman. So, instead of using data to know which experiences to prescribe to different customer profiles, an exploratory analysis would help you understand what actions customers took to get where they are now.
Working backwards is at the heart of the exploratory approach. Follow the trail of breadcrumbs from the touchpoints to see what path a customer took to conversion. Ask yourself, “How did users actually get here? Did they follow our path of display ads or click through from an informational article to a booking, or did they just go straight from a display ad to a booking or purchase?”
The exploratory approach focuses on the hows of the interaction as opposed to a more rigid, top-down, swallow-the-pill prescription method. When used in concert, both techniques of data analysis can lead to more conversions — and yes, more revenue.
Moving from tactics to a true understanding of the customer journey
Analysis of all of the data that supports the customer journey is the direction every brand should head in.
No matter how good your marketing department is, no two people are going to have the same exact journey. Some may follow the prescribed path and others may come to your brand and convert based on a path that has very little to do with what you’ve orchestrated. That’s why an exploratory approach is important as well. Attacking your customer journey analysis from both angles will give you more insights that will optimize the funnel of awareness, conversion, and loyalty, and ultimately help you move from simply marketing to customers to truly engaging them.
This article was originally published on InfoWorld.
Topics: Digital Transformation, Analytics, Sustainability