By Jess Sherratt, head of user experience at Code Computerlove
In times of great change – experimenting within an ever-altering consumer landscape is more important than ever.
Assumptions won’t cut it anymore. We can’t use the things we’ve known in the past; rely on stereotypes or even user behaviour findings from 12 months ago to shape strategies. Continual learning has always meant continual research, but today’s world is shifting at such a pace that it’s time to go beyond Conversion Optimisation and look at addressing some big business questions through experimentation.
Experimenting can also help businesses spend wisely – as a way to de-risk product development and without having to go into big build cycles in a world that we don’t have a clue about.
Any research helps us reduce risk around our decisions, whether that be for marketing, product placement or a digital service. So even if you’ve got great insight from a survey or focus group – experimenting is a fail-safe way to validate assumptions, with real users in real time, and as a way to get real value out of insight by actually making change.
And sometimes it’s the big bets – the unexpected results – that count the most. Challenging the most deep rooted assumptions about a business.
Similarly, experimentation organisations have the potential to tap into the power of high-velocity incrementalism as well as find the big disruptive idea, and there are some key types of experiments that can help to achieve this.
There’s a definite shift towards business experiments to drive innovation around business growth in 2021 and to validate fundamental business questions, challenge even big assumptions and long-standing processes through even the simplest of experiments.
To approach this kind of experiment, we map out the entire business model before we identify where to focus and to set our hypotheses.
In general, hypotheses – and types of experiments – then fall into three key categories: desirability, viability and feasibility, and running experiments across the entire customer journey – across business silos, with acquisition, conversation and retention all working together. In short Product Thinking applied to a business.
Within product thinking we consider desirability to be a product or service that meets a user’s needs, considering the factors for acquisition and retention. Experimenting with these can be carried out via many methods to test whether users are interested in what you are creating.
A great example is a fake door test. A fake door test is where an advertisement or button on a website enables the user to interact with something ‘new’. This could be used for various pricing structures, value propositions or new features.
The fake door bit is that it’s actually coming soon, but we can track an interested click through rate and even gather user information to update them when the product, feature or service is launched.
Desirability experiments help businesses to identify key USPs for their product as well as prioritise the different features and their level of importance to users. It can also help businesses to really understand what messaging works with which audience, which can help with targeted marketing.
A feasibility experiment is carried out to address what is possible to do, whether this be a technical investigation into API’s or a data assessment to make sure we can actually pool information in the correct way, it is all about assessing can we do what we want to.
Something we often do around the product lifecycle is conduct ‘Technical Spikes’. What these enable us to do is understand a piece of technology in detail and investigate how this might work within the ecosystem. The output of this could be a prototype demonstrating that the outcome we want to achieve is possible.
Feasibility experiments help businesses to understand what effort is required to achieve a specific outcome as well as identifying whether it is actually possible. This type of activity can help to identify a tech north star and define an MVP.
Viability experiments enable us to experiment with how the solution fits within our business model and ultimately tests whether there will be a return on the investment in the solution. Viability may be the hardest to test but it is the one that holds the biggest risk to the business.
An example of this would be to run a pilot that doesn’t have to cost the full extent of the business operations but is a key indicator of how much it would actually cost. For example if a business was intending to run a manned live chat they could dedicate a person to answering the sessions and see how this performs from an operational perspective.
Viability experiments help businesses to understand what would be required to invest in the solution in order to operationally deliver it. This also helps measure the ROI of this solution to explore whether it is something that a business could invest in.
A final point on experimentation is to create a balanced portfolio of experiments. Treat your experiments like you would a venture capital portfolio – the idea being that if you run 10 experiments there will likely be one or two that will deliver a big return, two or three that give a reasonable yield and some that won’t work.
And be brave. Because if you’re only testing ideas that you know will work, you will probably miss out on finding that gem of a result. Or if you’re not feeling so brave – place small bets and focus on speed.
So place your bets – make 2021 the year to make and change things, by placing bets big and small, seeing what works and doesn’t – both front end and with technology.