CX Strategy: Value Ratios in Journey Management

Uncharacteristically, for the past 2 weeks all I have been thinking about is the practice of journey design, how we use journeys to guide the practice of service strategy and, more holistically (services making up the totality of experience), of CX Strategy. This has been in part triggered by being immersed in all things journey design and CX strategy at the Forrester CX Summit in London a few weeks ago, but also because I have been working on something which has required me to pull together thoughts about the future of digital strategies and journey orchestration/management was a big part of that.

As a CX practitioner, I believe in customer journeys as the simplest and yet most effective way to manage CX. As much as we all agree that customers do not take linear pathways towards meaningful actions, we also need to agree that we require organizing principles and tools to be able to visualise how to take action to drive improvements. In simpler words, yes, people make decisions in varied ways but at a macro-level certain categories still apply and it is these categories which enable CX practitioners to make decisions that make sense for customers and the business alike.

Take the macro journey of car buying and its multiple potential micro journeys. While there may be a billion ways in which individual consumers have gone from “wanting a car” to “buying a car”, the reality is that when zooming out and reviewing said decisions at a macro level, one can still see the same categories: most people do not buy cars on a whim, most people research cars, most people research them in largely the same ways, most people make decisions in line with their income and family situation, most people expect financing to be a big part of their journey and most people expect a certain level of service after they have purchased a car. Equally within all of these “stages” (and, yes, based on sheer number of people that do the same things, you can definitely taxonomise a number of stages per the “car buying journey), people also tend to use similar channels, ask the same type of people, and expect the same interactions when landing in specific digital channels. Google’s “messy medium” was poorly understood to mean that people are incredibly random in the middle of the journey to buy a car. The reality is the messiness is really just adding the dimensions of time and direction to what is, eventually, a linear progression: you either buy or do not buy a car. The only thing that changes is how many times you’re willing to cycle through parts of the journey and when you do that.

Let me make it even simpler: let’s say I wanted to buy a car right now. We already own a car so some of the things I would need to think about is buy-back or any government schemes to pay me back for “recycling” my old car. I know have seen some cars on the road I like so I will start with researching options, I’ll check price and feel disappointed that they’re waaay more expensive than I thought if bought new. So then I’ll look into financing and maybe a “lookalike” brand or second hand, I will make a shortlist and realise it’s maybe all a bit onerous. And stop. Pause for a month or two while I rethink. But then one day, I will be driving my old car past the showroom of one of the brands I liked, and I will decide to stop and look at the car I liked and fall in love with the feel of it and really want to have one. So I will go back home and restart the search, see about financing options and decide I want to go for it. And then start the process of getting a leasing deal and move ahead with buying the car…

Do you see what I mean? At a macro level, the journey is the same. The thing that changes is time and direction. That’s all.

So, while there may be experts out there doubting the relevance of journeys, I would argue that the only thing they are doing is refusing to apply categorisation to data. Yes, you can treat every individual like they were on their distinct pathway to a purchase (and they probably are) BUT we have already seen that approach applied to micro personalisation in marketing and we know that, while we may invest massively in hypertargeting and micro personalisation of ads, ultimately the outcomes are not better in terms of value to the customer or the company. We tend to overinvest in trying to get thing “just so” for everyone when, in actuality, people are only bothered by specific things and we probably should spend more time understanding and addressing those things.

Which takes me, 2 pages later, to the core of this article. At the CX Summit, during one of the talks on Measuring Journeys, the concept of balancing the Journey Value Ratio was briefly mentioned. The idea behind it was that when measuring journeys one should aim to look at end-to-end value delivered so that at the end of the journey, when the person clicks to complete a meaningful action, the overall value provided is positive (you can get a teaser of this as described by Forrester here). This means that for any critical journey, you should have a simple viw of key interactions and ensure that you have a balanced ratio of positives/ highs and negatives/ lows, focusing on a net neutral or net positive (ideally) at the end.

Again, in simple terms this looks like this (and I’ll mark interaction friction or seamlessness with “low” and “high”): I was trying to buy a summer tote the other day and had gone to the website of a major fashion retailer where the search brought up a bunch of options (high, because in some websites search does not pick up specific models). I picked a specific design and then tried to figure out if the tote was big enough but the images were not taken in context, basically the tote was on a white background (low), so I had to resort to product specifics drop-down (low) to understand the size; the size was given in inches (low for me, because I understand only metrics) so I had to convert to cms to figure it out. I added it to my basket and tried to check out (high because it was easy) but I was asked to log in/ make an account (low) and was not given a Guest checkout (very low), I logged in with my Google account (high) and was taken to a basket review page (high) and then asked to insert address, which I did by adding my Post Code and expecting the website to auto-populate but it did not (massive low) and then clicked to payment where I was asked to type my card details with no autofill options (low + drop off).

So add all of that up and you get 2 highs and a bunch of lows. The trouble here is that not all of the highs and lows are of equal value, so there are some parts of the journeys that may have highs and lows that are of less importance to the overall outcome. Search is a great example of where it can be a “drop-off level” low, like for instance in Net-a-Porter where the search function and subsequent filtering used to not include price, material and sometimes even size separated by types of products (e.g. you could not pick size 7 for shoes and 42 for dresses at the same time). When trying to select among thousands of options, one could easily get overwhelmed and drop off. So, on balance, a higher-category “low”.

Autofills are also “drop-off level” lows, especially when we talk about quick purchases, non-involved purchases or impulse purchases: I am already thinking I don’t really need that dress, if I have to stand up and get my wallet to type in the card number than I will most likely not proceed with the purchase. This you can easily categorise as the highest-category “low”.

Now let’s take that series of micro-journey observations to a macro level. Let’s go back to buying a car: you can easily see how the same principle can be applied to buying a car. Which stage of the journey is the one where massive friction can cause drop offs and how can you balance with a seamless experience elsewhere? What are the non-negotiables in a journey and how are you set up to manage them? Is my discovery stage a bit messy but do I make up for it with an amazing configurator? Is the configurator a bit less visual than customers would like it, but is the leasing calculator simple and providing clear options? And most importantly, which sub-par experience will create a drop-off risk and which is likely to be tolerable? These are the types of questions I would be asking if I was thinking about how to manage a set of critical journeys.

I think we can spend a lot of time thinking about how to provide individually tailored journeys to people, but I wonder if the smarter thing to do would be to actually put all of our efforts in ensuring that those non-negotiables that drive most journeys are resolved before we go trying to micro-tailoring everything. I think people are willing to let the small things slide, if the key interactions are seamless, and that, my friends, is thinking about how to balance journey value ratios.