Why are we here?
Why, indeed. At the risk of halting us all in our tracks with such a frighteningly existential question, this is in fact a perfectly fair question to pose at the outset of design and build efforts for new digital platforms. Prior to talented designers and software engineers creating new digital products, it is vital that all involved have a shared understanding of;
- what are we designing and building?
- why are we doing it (and who for)?
Simple, right? Simple perhaps, but often such questions can be given scant consideration in the race towards product delivery. At Umain, we ensure that all design & build production is prefaced with a thorough ‘Explore & Define’ phase, so that we really know our users, and that we know their needs, and how best to serve them. Let’s deconstruct what this entails in more detail.
(1) Understanding the ‘what’
The Explore & Define phase at project initiation is a combination of;
- quantitative data analytics; broadly speaking, understanding the ‘what’ (e.g. what jobs need to be done & how are we currently performing)
- qualitative user research; in short, understanding the ‘why’ (e.g. what user motivations & needs should we address).
There’s that word analytics, which can send even the most seasoned digital professional running for cover. Yes, analysis of lots of quantitative data can bring us a bewildering array of product metrics such as conversion rate %, bounce rate %, average order value, task completion %, frequency, profit per user/customer (to name a few). However, simply put, at Umain we ‘do’ Analytics, because it gets us to focus on the things that matter the most. For example;
- We define how success will be measured (by focusing on business objectives & KPIs);
- We link business objectives (what clients want to achieve) with user objectives (what users want to achieve), and ensure as much mutual benefit as possible;
- We help all involved to ask better questions. Analytics is of course about answering questions, but the secret value is in encouraging everyone to ask better questions, and to seek to explore and to understand.
Objectives and KPIs
When the team at Umain created a new brand & lead generation website for a major global company in 2020, we started out, in conjunction with the client, by clearly defining business objectives, user objectives and KPIs. We also specified site users into three distinct segments, namely;
To illustrate, here’s an example of the output of that definition for Retailers;
Objective / KPI #1
- Business Objectives: Be known (Awareness)
- User Objectives: Understand the brand & its purpose
- Website Objectives: Navigate to brand purpose / About content
- KPIs: % of sessions where target content viewed, Landing page to target content click-through rate %
Objective / KPI #2
- Business Objectives: Be recognised (Consideration / Brand image)
- User Objectives: Understand how the brand differs from competitors, plus its USPs
- Website Objectives: Navigate to ‘How it works’ content / Product Detail Pages
- KPIs: % of sessions where target content viewed
Objective / KPI #3
- Business Objectives: Be chosen (Action / Conversion)
- User Objectives: Contact a local distributor
- Website Objectives: Navigate to Contact page
- KPIs: Contact Form Submit %
These objectives and KPIs helped us to focus our user-centred thinking on the key user journeys, and to develop hypotheses, and initial prototypes, as to how to maximise conversion in line with goals.
“We ‘do’ analytics, because it gets us to focus on the things that matter the most.”
(2) Understanding the ‘why’
Focus on problems
This brings us to the importance of understanding user motivations and needs. In this respect, we can employ persona-building techniques to ‘profile’ who we are creating for. Alternatively, we apply a Jobs-to-be-done framework to clearly understand and define the real jobs customers use a product for. Great products are built around the core concept that they help users solve problems. Focusing on jobs to be done helps us to focus on doing the right thing.
Qualitative & quantitative
As we navigate this process of truly understanding users’ needs, a range of specialists including UX designers and web analysts, plus senior business design, design and technology subject matter experts, bring their collective know-how to the table. We employ a selection of qualitative research methods to complement our quantitative baseline, including (but not limited to);
- Usability testing (remote and/or in person)
- User video recordings (on-site or in-app)
- Competitive intelligence / competitor benchmarking
- Secondary research / UX heuristics
- User interviews (in-depth 1:1 interviews, triads or focus groups)
- Observation / ethnographic research
Following the qualitative research, we deep-dive the quantitative analysis further to explore initial hypotheses developed through this mixed skills, mixed methodologies approach. For example, field level analytics will help pinpoint the degree to which specific points of user delay, confusion or abandonment are prevalent, having identified such usability issues initially though user testing. Essentially, we take a quant-qual-quant approach, although these steps are interchangeable.
(3) The importance of storytelling and why context is key
The human brain is programmed to think in terms of stories and narrative. Data and facts about user needs are important but they won’t necessarily be enough to engage the minds of project sponsors, commercial owners and all those involved in the delivery of new products. The key here is to synthesise all the insights and hypotheses from the exploration phase in a compelling way, and by describing it in terms of the impact for real users.
We may highlight with data that only 20% of those starting a payment details page complete a transaction, but when we marry that with face-to-face usability testing and watch as Jennifer or Victor struggle with the lack of trust or reassurance messaging that they expected, then it is an entirely more compelling basis on which to seek to resolve the user experience.
A narrative is a powerful way to break down resistance and to mobilise new product design or product optimisation. In ‘Talk Like Ted’, Carmine Gallo rightfully summarises that ‘stories are just data with a soul’. Stories inspire us to care about Jennifer, Victor, and others like them, and to want to solve their problems. At Umain, we have many storytellers, across many disciplines, helping to illuminate the needs of real users.
In tandem with great stories, understanding the context in which your app or site is used, is essential. In gaming, for example, the ‘typical’ user has on average 3–4 gaming apps on their mobile. Your app does not exist in isolation, and we therefore need to conduct interviews with users or to conduct competitor analysis, to determine if competing apps have great features that users love, that may lead them to churn from using your product in future.
We also need to understand at what point of the research-to-action cycle users are in when engaging with your product. Some cycles have typically much longer research phases than others (e.g. travel, hospitality etc.), whereas others (e.g. ordering a refill or parts) are much shorter. At Umain, we use various frameworks, to place user behaviour in context e.g. AIDA framework. We recently built an end-to-end evaluation framework for a cybercrime prevention client, presented in Google Data Studio dashboards, to understand user behaviour from awareness through to action, with specific KPIs to optimise for each stage. Earlier stages were focused on increasing brand awareness among users, whereas latter stages were measured in terms of task completion %, customer satisfaction and Net Promoter Score.
In an increasingly fragmented digital world (e.g. ‘too much’ choice for users), plus mixed ‘clicks n’ bricks’ distribution models, the need to have a single view of the customer and to offer a highly personalised user experience, has never been greater. Much of this customer-level analytics, with a unique customerID across all channels, can be captured through loyalty programme mechanics. Companies who are able to navigate this complexity and to simplify this into an easy, rewarding user experience, will have satisfied customers and a profitable business. At Umain, we’re here to help you understand, and to better serve your customers.
(4) Outputs from exploration become inputs to design
Outputs are really inputs
Distilling all this analysis and user research into high-level user requirements is one thing, but handing over clear ideas, initial prototypes and plans on project scope, to commence product design is quite another. To synthesise outputs from the Explore & Define phase, the following is typically delivered as inputs to inform the design phase;
- Overall problem definition (targets vs.baseline performance)
- Objectives & KPIs definition
- Evaluation framework
- Project scope & plan
- Key challenges & opportunities
- High-level concepts
- Idea prototypes
- Jobs-to-be-done definition
- User profiles / personas
- Product roadmap
- Prioritisation frameworks e.g. LIFT, PIE, ICE to inform features planning
We will explore these deliverables in more detail in future articles.
Why this matters
A solid foundation at project initiation avoids unnecessary rework later, plus mitigates risk against costly investments in poorly converting user interfaces. This is achieved by the inputs of analysts and designers in this early exploration and definition phase, operating within the collective expertise of the wider departments in Umain. Understanding UX and having clear evaluation criteria also ensures that all decisions are based on objective data rather than merely opinion.
- Enlist the brightest analytics, UX and design critical thinkers from an early project stage
- Create a shared clarity of purpose — define what we are doing, and why we are doing it
- Know how we will evaluate success later when our new product is launched
- Do not stifle creativity in design and technology; inform it
- High quality inputs maximise the probability of high quality outputs
And remember, this is how the team at Umain gets ‘warmed up’ to deliver great customer experiences; the real magic comes when products launch! To find out more feel free to reach out to myself or any of the team at Umain.
Damien Smyth is VP of Analytics at Umain, leading a team of analytics & optimisation rockstars, driving a user-centric, data-informed approach in all our decisions, to deliver genuine impact for clients. He brings 15 years of leadership experience in analytics, research and business intelligence, across a range of sectors, markets and brands. The creative and analytical sides of his brain have been competing for over 40 years and we’re not sure who's winning, but the analytical side is keeping score.