I recently attended the Customer 360 Forum, which combined presentations from prominent CX leaders with roundtables, where attendees took part in facilitated discussions.
As a co-founder of CX Collective, I moderated the roundtable discussions on ‘Customer Data, Insight and Analytics’, which gave me the opportunity to discuss and discover current challenges facing attendees and how they were overcoming them.
What was striking is that no matter the size of the organisation, the challenges they face are similar, and in many cases, the solution is too.
Tech: everyone has a problem with their plumbing
In CX, the nirvana that many people are striving for is a ‘single view of customer’. The ability to deliver an experience that tracks all interactions, across multiple products, through every channel, from prospect to advocate.
Obviously, achieving a single view of customer vision isn’t easy. And it became apparent from our discussions that it’s a challenge some of the largest and most sophisticated businesses in Australia are still grappling with.
The main cause of this seems to be the ‘plumbing’, as one of the delegates explained it.
Pots of data sit in disparate locations, some in legacy systems, others in new platforms not quite living up to the bright dream sold to them by their vendors – all of which need to be integrated together.
It’s this ‘plumbing’ that’s causing the biggest headache in being able to deliver a single view and the consensus now is that, for the time being, that our efforts should be focused elsewhere.
From the roundtable discussion, the general agreement was that while the single view of the customer is great in theory, getting there may not be possible for most organisations. Instead of trying to create a holistic, single view, most attendees felt it better to focus on ‘moments that matter’ and fixing the problems they can with the technology they have, rather than trying to reach an unattainable tech nirvana.
Creating solutions, without having a problem
That brings us to the next issue concerning technology: it’s often and solution looking for a problem.
What was clear from the Forum is that everyone has a lot of data, but not enough insights. And we’re not just talking about data-driven insights generated in an analytics dashboard, but rather human insights based on conversations with real customers.
A common observation is that data teams were often finding a solution, through rigorous analysis of data, without a clear understanding of if and what the human need is. Without human oversight, data can give us a misleading impression of customer behaviour and preferences, which can distort the solutions that we develop.
Take your Netflix viewing. If you’ve ever tried to find something to watch that sits slightly outside your usual watching habits, you may have noticed that Netflix actually makes it very difficult for you. The algorithm ‘people who watched this will like this’ is so ingrained, that if you dip a toe outside your usual genre, the tech keeps on trying to pull you back to what it thinks you want. What this has meant is that the tech has caused me to behave in a certain way, rather than solved my human issue of wanting to find something different to watch.
Start with a human problem
A great example of meeting a human problem came from Jay Sellick’s presentation. Jay is Chief Customer Officer or Sportsbet, a business operating in a highly competitive market with a commoditised product and mountains of data available on their users.
While Jay did talk through some incredibly smart ways they were using insights from data to deliver better experiences to their customers, the topic that resonated most was how making a human decision based on empathy delivered an exceptional experience to a subset of users who may otherwise have been disgruntled. They call these human decisions ‘justice bets’.
14th July 2019 was a day of celebration in the Roberts household as England clinched the Cricket World Cup in a nail-biting finish at Lords. For those of you who don’t follow the game, or have forgotten the finer points of that particular match, England won in the final over partly due to an exceedingly lucky deflection as one of the batsmen was running which went over the boundary for a 4:
For this to happen in any match would be unusual, but in the final of a World Cup it was incredibly unlikely. Some would say that there was some injustice in New Zealand losing in this way and SportBet knew that its customers who had bet on New Zealand to win may have felt disgruntled.
So they enacted what they called a ‘justice bet’, and paid out the bets to those who had backed New Zealand as if they had won the game, at a cost of over a million dollars.
Could they have used data to segment out those who had lost, identified how they this unlikely result not going their way had affected their betting behaviour and then analysed whether paying out the bets would have made commercial sense? Possibly.
Did making an empathetic decision not based on data and demonstrating to their customers that they understood them as humans deliver an exceptional experience immediately? Definitely.
Real prototyping, with real humans…
Another great example of the importance of understanding that ‘customers’ are in fact real humans came from another of our presenters, TransportNSW.
TransportNSW are currently in the process of investing in new rolling stock for the Sydney train network. It’s a large project with significant expenditure, with 512 new trains being ordered from a South Korean manufacturer.
As part of the process, TransportNSW built a full-sized prototype at a cost of several million dollars, which they then tested with real customers.
The prototype was easily reconfigurable, with 3D-printed parts to allow for fast testing and modification.
This real-world testing ensured that the new trains will meet the real needs of TransportNSW’s customers. While data on existing usage indicated that customers preferred the ‘flip’ style seats that many current trains have, testing with real customers showed that they preferred the new style of fixed seat, which included a tray table and a powerpoint.
While this has been an expensive and laborious process, the benefits of it are obvious, customers will be able to benefit from using a train that meets their human needs, not just one that the data indicated that they should have a preference for.
While this example may seem extreme, its principle can be applied to the smallest project. Hand drawn UX concepts or sample copylines to be tested with real people in order to get a better understanding of if they really work, or not.
My key takeaways from the event
The opportunity to hear how a mix of organisations were meeting their diverse customer-focused data and insights challenges was interesting and inspiring.
My main takeaway was that the commonalities in the problems faced far outweighed the differences in our diverse delegates. Everyone is struggling with technology. If you’re battling to connect the dots around data, then you are not alone and many of the biggest organisations are in the same boat.
The most inspiring and rewarding development coming from that realisation, is that instead of thinking tech was going to solve all problems – the ‘if you build it, solutions will come’ approach – firms are going back to basics and identifying problems that they use their data to solve.
While their challenges may be very different, the solution was the same: start with the human problems and work from there. By doing that and solving for those problems, you will be delivering far greater value to your organisation than working fixing a problem that your data suggests customer might be facing.
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