The post The 101 Guide to Data-Driven Design appeared first on HostGator Web Hosting Blog | Gator Crossing . The web is constantly changing. It isn’t magic; there are thousands, if not millions, of individuals out there who continue to work on their website until it’s reached “optimization”. It either has something to do with the culture of innovation, motivating even good solutions to always push forward, or it’s related to the accessibility of websites and the fact that changing one line of code takes less time than a drink of a cup of coffee. But intrinsic to tech culture is the desire to move forward the right way. There’s improvement for improvement’s sake and then there’s clear, defined, intelligent design decisions that make a product, and a business, better. This, again, is not magic. It’s a matter of understanding your data and applying it, intelligently, for the betterment of product and consumer understanding. The Concept This is what the industry likes to call “data-driven design”. The idea is that numerical and non-numerical information can be used to change the configuration of a product or website in order to improve sales conversion and revenue. Does it work? The short answer is yes. According to Extractable, 71% of businesses surveyed experienced site improvements from the use of data and data-driven design. This is, obviously, fairly compelling evidence. The problem is that people are utilizing the wrong data. 66% tracked impressions, which indicate traffic, but not intent. 46% track time on site, which suggests engagement, but in a very loose way. Are customers sticking around because they’re interested, or because they can’t find what they want? So what are businesses doing wrong? According to web authority Smashing Magazine , marketers and web designers need to understand the core of data-driven design in order to reap its very real potential. Be Specific There are two types of data at work. Quantitative, which includes numerical data, demonstrating the “who, what, when, and where”, and qualitative, which includes all non-numerical data that demonstrates the “why or how”. Data is collected in multiple ways, quantitative from platforms like Google Analytics and qualitative from user testing and surveys, but understanding what data delivers value requires a little focus. As attractive as all metrics are, and as tempting as it may be to draw conclusions from them, if only to give your efforts direction, good data is both empirical and specific. Empirical data refers to any gathered through observation or experimentation. This means that what was gathered came from a purposeful effort. “Specific” data means that it is isolated to a particular page, piece, or idea. This is because each page, subpage, type of content, and call-to-action has a specific goal in mind. A high bounce rate on a page may seem bad, but when you realize that it’s intended to direct people to a vendor or sponsor, suddenly that looks pretty good. The key is to look at each page, understand its intent and purpose, and focus on relevant metrics in order to determine whether or not the goal was achieved. The reason this approach is valuable is because, unlike aggregate data, specific data guides action. If a page fails to achieve a particular goal, then it’s time to do some user testing. This is where qualitative data comes in. Focus groups, surveys, and comments allow you to determine why a page didn’t hit its target and make smart design decisions as a result. An Example Some of this may not be so simple, so let’s take a look at a hypothetical that should help clarify things. In this scenario, we’ll examine the website of a cleaning service business who encourages appointment bookings through an online form. In addition, the site has a blog where it publishes cleaning tips, and a page full of cleaning product recommendations. Each page has a specific goal. For the appointments page, we want form completions, a relatively low “time on page” metric, and, a mid-range bounce rate. This is because new customers will hopefully check out their more informative content, while returning customers will likely just book an appointment and leave. On the blog, we want a low bounce rate, due to the fact that our content is intended to convert viewers into customers, and a decent “time on page” metric to indicate that our content is being read. Finally, the product page should see a high bounce rate as customers stop by and then head out to Amazon to purchase our recommendations. Each of their metrics appears to be okay, except two. The “time on page” metric on their appointments page is high and their form completion rate is low. It’s easy to assume that this means that people are getting frustrated with the form and leaving, but jumping on this assumption would be to ignore the qualitative aspect of the approach. They take the time to do some focus testing, interviewing current customers and brand new customers, and discover that many of the fields on the form are irrelevant or the information is hard to attain. They change accordingly and with this change, the time drops, but not too low, and the form completion rate rises, reinforced by follow-up interviews that indicate that customers are much happier with the new configuration. Diligently applying both human and analytical insights in order to improve products, websites , and services is an intelligent way to advance your business. Understanding that both qualitative and quantitative data play a part and using them in tandem will help make the most out of your approach. Be specific in what you measure and always back up design choices with data of both kinds. The combination will not only solve some headaches from an organizational standpoint, but quickly clear up customers’ pain points as well, meaning more revenue and a better relationship with the people who keep you in business. Register a cheap domain name at HostGator.com
-
Recent Posts
Recent Comments
Archives
- September 2019
- August 2019
- July 2019
- June 2019
- May 2019
- April 2019
- March 2019
- February 2019
- January 2019
- December 2018
- November 2018
- October 2018
- September 2018
- August 2018
- July 2018
- June 2018
- May 2018
- April 2018
- March 2018
- February 2018
- January 2018
- December 2017
- November 2017
- October 2017
- September 2017
- August 2017
- July 2017
- June 2017
- May 2017
- April 2017
- March 2017
- February 2017
- January 2017
- December 2016
- November 2016
- October 2016
- September 2016
- August 2016
- July 2016
- June 2016
- May 2016
- April 2016
- March 2016
- February 2016
- January 2016
- December 2015
- November 2015
- October 2015
- September 2015
- August 2015
- July 2015
- June 2015
- May 2015
- April 2015
- March 2015
- February 2015
- January 2015
- December 2014
- November 2014
- October 2014
- September 2014
- August 2014
- July 2014
- June 2014
- May 2014
- April 2014
- March 2014
- February 2014
- January 2014
- December 2013
- November 2013
- October 2013
- September 2013
- August 2013
- July 2013
- June 2013
- May 2013
- April 2013
- March 2013
- February 2013
- January 2013
- December 2012
- November 2012
- October 2012
- September 2012
- August 2012
- July 2012
- June 2012
- May 2012
- April 2012
- March 2012
- February 2012
- January 2012
- December 2011
- November 2011
- October 2011
- September 2011
- August 2011
- July 2011
- March 2011
- November 2010
Categories
Meta