When thinking about ‘data-driven design‘ in terms of ‘user experience design (UI/UX)‘ and ways to build better ‘user experiences’ we are talking about using the information we have carefully gathered and curated during our research phases… for example user interviews, user data, quantitative analytics, surveys, feedback etc. and applying that data to the design process from a user-first perspective.
Upon delivery, the design‘s data drivers in play will require the business goals are being met and that the design brings value for your company or client and relevant stakeholders of the business.
1. Data-Driven Design: Start with user data
Data-driven user experience design is all about utilizing a ‘decision-making’ approach to the user experience design process. This approach relies heavily on data about your users – for example, the way they think and act – their behaviors and attitude.
It is, for this reason, it’s imperative to begin the user experience process focused on user analytics and data. From here you can generate User Personas.
Generating User Personas will help you as a designer to make better more informed data-driven decisions about your design in terms of how your users interact with your product or service.
2. Data-Driven Design: Use the data to make decisions
The facts are simple – Data-driven design will help you as a UX Expert improve your website, application, service, or product performance and help you to increase conversions. That’s really the bottom line here.
In order to make the best decisions, you need to be aware of the best types of data available – it kind of goes without saying. The user experience designer and developer have a multitude of data points available to them in order to make better-informed decision making.
The modern-day UX‘er needs to have a bunch of skills and use them to make informed decisions around things such as user data analytics, rational emotions, cognitive ability, pattern analysis, general psychology, color theory, etc.
3. Data-Driven Design: Develop a methodology
Establish your user-centric design methodology. Realistically User Experience UI/UX has been around for a long time, however, we have been quite limited in terms of the actual methods we have been using.
The reality is (in part because there is no one set formal pathway to becoming a UI/UX – User Experience Designer or Developer) our processes and procedures have not evolved in line with the transition to the modern ‘data-driven‘ world.
4. Data-Driven Design: Be productive with data
As a User Experience (UI/UX) Expert, you are tasked with finding solutions to problems to meet Users and Stakeholder needs.
We’ve found as part of this journey the better you can work with data and more specifically produce visually compelling information out of the data research you’ve found is a key differentiator to being ok, good and a great UX‘er.
A really great read to help you along your data storytelling journey to become more productive using the data you have found is: Data Visualisation: A Handbook for Data Driven Design
This read has a stack of images throughout including extensive how-to and how-not-to examples. The Financial Times even voted it one of the ‘six best books for data geeks.
5. Data-Driven Design: Get started
The time to get started with data-driven designs is now. Data-driven designing is an ongoing process. In talking about this we mean that after your initial research is completed you will need to continuously need to monitor your metrics and performance indicators and tweak and re-configure as appropriate.
When considering the performance, analytics and metrics monitoring for User Experience Design (UI/UX) we recommend looking at some key things:
1. The Users and their actual ‘need’ for the solution you are designing – your website, application, product, or service.
2. A User-First Experience. Always try and create the best User Experience you can putting the ‘User First’.
3. Listen More! Always listen to what your actual Users actually want.
6. Data-Driven Design: Focus on benefits, not features
While the statement ‘benefits NOT features‘ sounds pretty obvious it’s a really common side effect – especially in the startup world to get caught up building out features or stuck in the feature creep zone.
For User Experience best practice – It’s always a good idea to take a pause and re-evaluate. We recommend going back to the beginning if you need to.
Remember to put the ‘User First‘ to understand what is actually required.
7. Data-Driven Design: Always track and measure your results.
Part of being a User Experience (UI/UX) Expert is being able to understand, evaluate, track and measure your results.
Any number of relevant online searches will reveal a plethora of tools to aid in this quest. What we find useful is using a standardized library of UX templates alongside your developed “Methodology (See point 3.).
Templates are useful when tracking and measuring your results to ensure the user data, survey question responses, statistics and analysis, etc. that you gather is treated fairly and consistently across the board without bias.
Standardized UX templates will also help you identify any gaps in your collected data. As the User Experience (UI/UX) process is an iterative one – using Templates will allow you to make tweaks as you go and re-gather or re-calibrate on the fly as required – saving time and resources.
When considering ‘Data-Driven‘ UI/UX design and development we are looking at ensuring first and foremost our User’s needs are being accounted for.
We do this by taking a data-based approach – by Using (consistently with templates based on a methodology), Analysing, Tracking, and Measuring the performance of the data we have collected.
As User Experience (UI/UX) experts, we are able to gain a huge intelligence advantage when using this data. By gauging how our users are likely to react or behave based on certain influencers, situations, or events around various widgets, products, or tools we place in front of them is an amazing insight from a company research standpoint.
Resultant information from these datasets can be used in critical decision-making for multiple business units such as Development, Product, Sales, Marketing, Operations and Executive Management.