UX and Data architecture - what's the difference?

Throughout most of our lives, whether it's personal or professional, we'll probably be familiar with the seeming obsession companies have with providing us the perfect 'User Experience', or UX. Whether it's something we look forward to, such as going on holiday or getting married, or the more mundane things such as a trip to the supermarket or browsing Netflix, UX is everywhere!

For me, even if I think back to my early jobs there is evidence that this way of thinking existed, albeit with a very different slant to it.

As a newspaper delivery boy, we were expected to deliver the papers at the crack of dawn so our customers could see what was going on in the world as early as possible.

Then again, as I recall working in one of the many Supermarkets we have in this country, we'd navigate 'mystery shoppers', offer to pack customers' bags for them and minimising the amount of queues they had to wait in at checkouts, all with the aim of keeping our customers coming back to our shop.

Since my early twenties, I have had an annoying habit of experiencing things myself and then imagining how they could be improved, more often than not with the aim of me, the customer, "getting things done as quickly and easily as possible".

It was during my first 'proper' job, in a call centre incidentally, and a point in my life where my interest in technology had also come to the fore, that I was able to combine the desire to improve things, and interest in technology, into a passion that gave me a platform to progress in my career in a way that really motivated me.

I still remember the first process I was able to improve using this combination. Fed up of hearing customers complain about receiving incorrect letters related to their direct debits, I worked with the IT team, reviewed the process, and helped them code a more logical way to correctly send out these important letters to our customers. This was about fifteen years ago and seems so basic compared to the world we live in nowadays.

For whilst the early examples I provided were all manual steps we took to improve our UX, it's difficult to argue with the fact it is advancements in technology that have had the biggest impact on UX over the last couple of decades.

However, this is what I think leads a lot of people to make their first incorrect assumption. Better technology does not automatically lead to better UX.

Over the years, as I've taken on different roles throughout my career and as technology has come on leaps and bounds, I have often heard people say "having a nice looking website will provide a better UX", or "people would get a better UX from a mobile App". This might be a fair sentiment, but it probably won't surprise some of you to hear that a large percentage of these initiatives fell short of their full potential.

So why did most of them fail? Or if not 'fail', then end up delivering something that could have been better?

This is where we get to the crux of my blog; more often than not, the reason this happens is because the data architecture has simply not been thought through properly.

Now before you all run off and question the skills of architect friends or colleagues, this isn't really their fault. Data, by its very nature, is factual and logical. UX is the exact opposite.

Just looking at two images below, simple Googled word-clouds of the terms "User experience" and "Data architecture", illustrates the juxtaposed concepts synonymous with each.

Look at this image. Words like info, data, web and diagram take prominence.

Now look at this one. You see words like perceptions, behaviours, emotions and user take centre stage.

The point I'm making here is that UX is a very emotive subject. It tends to evoke feelings, is something that everyone has experience with in some shape or form, and therefore it's an area that everyone is pretty comfortable talking about.

As we move towards data architecture however, people are generally less familiar with the associated terms, and therefore the language evokes a sense of unfamiliarity or even fear, leading people to ignore or avoid the topic.

The problem with this is that you really can't have a truly great UX without a very well thought out data architecture, and ultimately the purpose of great data architecture must be to provide the 'User' with the best possible experience.

And I should clarify when talking about data architecture in this way, I'm talking about it at all levels. Whether it's a simple page structure, the way an entire site is built or a technology landscape is connected up, all have examples of where the data architecture and UX is intrinsically linked.

So let's bring that to life a little bit.

In my current world, Salesforce plays a big part of it. For those unfamiliar with Salesforce, it's a globally renown CRM platform that is highly configurable. Each page is designed to provide the Users with the best possible experience, surfacing the most useful information at the right time.

On the face of it, that might seem really straightforward, as it's just a bunch of data fields on a page really. However, from a technical perspective, there is a combination of 'objects' that need to be connected using unique identifiers and relationships, and if even a single one of these is incorrect, the information on the page will be completely wrong and the experience would be ruined.

In the next example let's look at a more familiar name; Amazon.

When you first land on Amazon the experience isn't that special to be honest. It's a fairly clean interface and allows you to navigate an online shop window. You get some trending items and some sales, then when you get to an item it starts to get more interesting; you get suggested additional purchases and comparisons, something that is only possible with incredibly complex data architecture.

But it's when you register or login that things become truly mind blowing. You immediately see recommended items for you, based on what you've looked at, bought or probably even thought about (joking!) - again, something fundamentally underpinned by that same data architecture.

For my final example, I'll use something so commonplace nowadays that people might not even realise the data architecture that enables it.

Registering or logging in to most sites is now something all connected through social media profiles. Whether it's Facebook, Twitter, LinkedIn or Google, at the click of a button you have information entered, site profiles created and preferences shared. Some are understandably cautious about the amount of information shared across these sites, but whether you trust the companies themselves or not, you can't help but appreciate the hugely increased UX created when things are connected in this way.

So, is there a point to this, or has it just been the ramblings of an overactive mind whilst looking after a wonderful new baby?

I've recently been challenged to think differently about 'problem solving' and what it means. As someone who prides themselves on being a problem solver, this was something that was difficult to hear - I'm always solving problems, it's kind of my thing.

But what this latest challenge helped me understand, and why it led to me wanting to write something like this, is that when it comes to solving data problems, you need to try to consider the lense that your audience is likely to give the problem - and more often than not, this is likely going to be at the more emotive end of the spectrum.

So I leave these two warnings for anyone who has made it all the way through this, my first blog.

Firstly, when looking to achieve an awe-inspiring UX, get your data architecture right. Understanding what your customers or users want is key, but coming up with a way of connecting up the necessary data, and making sure it's governed in the best possible way, is as important to achieving the UX you're after.

Secondly, for any data gurus reading this, don't forget that whilst it might seem obvious to some of us that fixing the data, or data architecture, will ultimately improve the UX and probably lead to an increase in revenue or decrease in operational costs, this isn't true of everyone. Consider your audience, their motivations, or 'lenses', and try to explain the problem, solution and reasoning in a way that will resonate with them.

Thank you for taking the time to read all this, please do let me know what you think about the content or blog itself. Also, if there are any other data or UX related topics you're keen to discuss I'd love to hear about it.