Design thinking combined with data science and analytics, can help organizations unlock new opportunities and reinforce long-term innovation capability.
Data and business go together like two peas. However, design and business? That’s a touch less intuitive. Today, we’re getting to take a better check out design thinking, the way to use data in design, and what data matters.
What is Design Thinking?
Let’s start with a definition. Design thinking, consistent with IDEO’s CEO Tim Brown, is:
“a human-centred approach to innovation that pulls from the designer’s toolkit to integrate the requirements of individuals , the chances of technology, and therefore the requirements for business success.”
Let’s break that down a touch . Design thinking is:
- Human-centered: you’ve got to place people at the guts of your design
- Approach to innovation: it’s a strategy and set of guiding rules
- Designer’s toolkit: all the tools, tips, and tricks that designers use to bring ideas and ideas to plug.
- Integrate people, technology, and business: it’s to compile the top user (people) using the technology that exists now / within the near future, and style must do that while meeting business requirements.
With all that in mind, we define design thinking as:
A specific methodology/approach for designing new products, services, and experiences that put the user at the guts of the method , using every trick within the book to tie together the user and technology while achieving business requirements.
Design thinking is about taking the approach a designer would — that specialize in the user, incorporating technology, considering the intersection of feasibility, desirability, and viability — outside of a design context. This suggests tinkering and twiddling with a thought , reviewing and failing all the time, and taking note of the people you’re designing for and staying laser-focused on their needs.
Design Thinking Process
So that’s the ethos behind design thinking. Next, we’d like to know how it’s actually done. The method could vary counting on what model you consult, but design thinking generally fits into this framework.
- Empathize. Work to know your audience – who your audience is, what are their pains, problems, attitudes, and what they need to accomplish at an emotional level beyond your product.
- Define. Define the matter that you’re getting to solve within the context of the pains and challenges you uncovered in your empathy discovery. This results in a problem/challenge statement.
- Ideate. Come up with a bunch of various ways to unravel the matter .
- Prototype. Turn those ideas into rock bottom possible fidelity tests that you simply can execute and still get clean data. This stage usually cuts the ideas down as problems are discovered.
- Test. Get your prototypes ahead of users and see what they assert .
Why Business are Embracing Design Thinking
Over the last 20 years, companies became far, much more customer-centric. As an example , it’s hard to imagine a sales team being run today like in Glengarry Glen Ross. Sales are a consultative process now. Products are built with countless revisions of UX testing baked directly into the method .
For sure, every now and again, a Steve Jobs visionary comes and shifts the paradigm of innovation. However, overwhelmingly, organizations are currently within the business of intimately knowing their customers and building and selling things their customers want.
Also, let’s be honest — knowing your customer isn’t a replacement idea. Organizations have always tried their best to know who’s buying them and make products that their customers would also like.
Design thinking, with its customer centricity, may be a natural slot in the new business paradigm.
Why Use Data within the Design Process?
To recap, design thinking is thinking sort of a designer, putting your customer/user first, and solving non-design problems with a design toolkit and methodology.
Now, to data.
The emergence of the web and subsequent massive data collection and storage mean that now, businesses can know their customers better than they ever thought possible. This drives up product quality, successively driving up customer expectation during a vicious feedback circuit .
Now, organizations are expected to understand and anticipate user needs at a private level.
Moreover, you can’t deliver that quality with design thinking alone.
Data, especially big data about your users’ actual behaviour, can assist you understand where you would like to focus, how users are using your product/service “in the wild”, and exactly what pieces are driving people to like your organization.
The acute example of this type of data-ization is product-led growth (PLG), where the merchandise is so focused and attuned to solving users’ problems that it literally sells itself.
However, albeit you’re not a VC-backed PLG machine like Slack or Dropbox, you’ll still use data to know your customers’ pains better, and fuel design-thinking-led development .
What Data Should I Use?
One of the risks of getting access to data on literally everything is that separating the signal from the noise is incredibly difficult. Your data evaluation is going to be idiosyncratic to your organization. Fortunately, there are a couple of must-haves which will likely apply to everyone.
- The most accessible source of insights for nearly any organization is its website. It’s a treasure-trove of knowledge , but it does need to be parsed correctly. For a design thinking approach, we recommend looking at:
- Your user flows. What are people watching , and where are they going?
- See where / what people check out with heat mappings and automatic screen recordings. Content analytics and SERP position. Are you talking about the proper stuff? Are you answering the questions people are asking, and does your product solve the issues that they’re trying to find solutions to?
In-app analytics do serve an identical function to website analytics but differ slightly thanks to their more practical nature. That is, people attend your website for all kinds of reasons. An e-commerce site, for instance , may need traffic both from users looking to shop for and other people trying to find employment .
App analytics are cleaner and speak more to what users are trying to find. App analytics are often used especially effectively to both empathize together with your audience, define your problem (if you’re performing on the app itself), and test via A/B testing (more on this during a second).
A/B and multi-variate testing
A/B and multi-variant testing, it’s a more adult cousin, are probably the simplest thanks to test ideas during a design thinking setting. due to that, they will be used, of course, in testing, but also throughout the process:
- Empathy and problem definition are often tested with A/B testing messaging.
- Ideas are often rapidly prototyped with multi-variant testing on an app or an internet site .
Behaviour flows and other UX testing
UX features a lot of other mechanisms to supply beyond A/B testing. There are a couple of those especially that are helpful for design thinkers in business.
First, behaviour flows on your site or app. Where are users going and the way they’re getting there can tell you an enormous amount about what they’re thinking, what they like/don’t like, and what they struggle with.
Second, paper prototyping. Paper prototyping within the context of an app or a bit of software is essentially a paper version of whatever you’re getting to design. It’s incredibly fast and straightforward to form , meaning that you simply can test an enormous amount, very very quickly without wasting development hours.
Third, in-person UX testing. Sitting down with someone to speak to them through a thought , interview them about the matter , or simply talk through an answer is tremendously valuable because it gives you first-hand insight, straight from the horse’s mouth.
Finally, online user testing. Usertesting.com is the hottest , but there are many sites out there which will offer you the power to rapidly test your idea within the hands of the precise people you’re trying to assist .
Design thinking doesn’t need to be something that only creative agencies use. Anyone can use the framework to drive business objectives.
Understanding your customer, their pains, and iterating to unravel them is usually getting to be a sound business strategy. And by overlaying the tactic with hard data, you’ll drive more meaningful insights, faster and more effectively than ever before.
So what’s your next step? Are you able to embrace design thinking and achieve your growth goals?