Day: February 19, 2018

In 2018, it almost sounds repetitive to say that user experience trumps features, and designing a better product depends on understanding what it feels like to use it, and best to design a product that can be used intuitively. Intuitive user experience and a great product depend on a number of things including great design. However, there is something far more important and basic than design, which is data. Data in the form of customer feedback, customer expectation and motivations, system performance and errors, and the ability to make sense of data is collected over weeks, months, and years in the right context is what helps develop great products and superior UX. Yet, data is often ignored or given just lip service simply because product designers and developers do not have the resources or interest to process complex datasets concerning customer feedback and expectations. Let us admit it. Customer feedback, surveys, and reviews build up over a period of time, and most companies simply toss the accumulated data to the side, quite literally. Yet, it is this very data that is needed to create better experiences and better products. Why the reluctance to use data when it is so freely available? Every business gathers data, even if they do not realize that they are. However, most companies are reluctant to use the data that is already available on their systems. This data may stem from customer feedback forms, web traffic figures, purchase trends, social media conversations, and just about anything that results due to the intersection of business, customer, and the product. The reluctance stems from distrusting data and feeling overloaded by data that is continuously collected by systems. With many products being “intelligent”, data overload has led to data daze, as a Forbes article puts it. The same article describes data daze resulting in analysis paralysis. The answer is simple. Most companies hesitate using data or downrightly avoid anything remotely related to data because they feel paralyzed by it. How can a business avoid this state of data paralysis, and confront it to make it something useful? 84% of CEOs do not trust the quality of data they have on hand It is psychologically proven that too much information reduces cognitive ability process it. This means, too much data leads to data daze. Overanalyzing data can lead to analysis paralysis, similar to what happens to an individual with psychological difficulties. While distrusting the quality of data and feeling overwhelmed by data that is available is natural, so is feeling paralyzed by over-analysis of data. The truth is, no company can process all the data that it collects. It needs to know what it wants to know with data that is already available, and how it is going to process it. This brings us to the question of processing and placing data in meaningful contexts. How to place data in meaningful contexts When it comes to understanding and using data, context matters more than anything else. Cognitive overload of information results in inefficient use of that information. For example, a boy that is given a dozen books on his birthday may not value them, or even feel intimidated by them, even if those books are classics. However, if he learns to categories those books in a shelf, or is helped to do so by someone who understands those books, he will not only pick up those books, by also put to use what he learns from them. Similarly, every business must put the data that they collect into context. Without placing data in context and simply processing it using analytical tools will result in an analysis that may not be relevant at all, resulting in analysis paralysis. With the Internet of Things, location-based applications, wearable tech, and sensors contributing to the data deluge, one must really know how to place all that data in context. While this may seem difficult, it is not impossible. Ask yourself these questions: What am I trying to improve? What might my customers want? How can make it easier for customers to use my product? Which variables could help me understand what customers want? How can reduce the amount of data that is analyzed? As you can see, asking yourself or other C-level executives in your company will help you to develop a frame of reference with which you can handle data. Once you know what you are looking for, it is easier to find it. Usually, you can find all these answers with the assistance of your customers plus with a little help from your friends (IT department and technology). 3 important sources of data to develop better products and UX As you might have learned to question yourself in the previous section, the answer to your data quandary lies with your customers and your IT department. Collect customer feedback: To make sure that you understand your customers better so that you can design a product that is inherently more intuitive to use, you should start collecting customer feedback. Customer feedback can be collected in umpteen numbers of ways, both online and offline. Customer feedback, opinions, and reviews can be processed using linguistic and data crunching tools so that you understand the prevailing opinion about your product, and how it can be improved. This axiom holds true whether you have designed an application as a product, or an actual physical table as your product of choice. The fewer customers you have, the more opportunities you have to seek detailed and intimate feedback from them. If you have a large number of customers, feedback forms can be statistically analyzed. While this may sound time-consuming, which it inherently is, improving user experience and creating better products are ongoing processes too. Customer expectations, and what motivates them: Next, make sure that the features that you offer alongside your product meet customer expectations and motivations. This is the part that answers “why does my customer want to use my product” question. Knock the door of your IT department: