This article is part of our Retail Reloaded series. The series offers a new vision for retail businesses through an evolved use of technology, cutting-edge innovation and digitalization practices.
Position your organization for success by developing new capabilities, new skills, and, importantly, a new vision for this new normal. There are three core actions where technology can help retailers not only survive this crisis but emerge as winners. SAVE, ACCELERATE, and SHARE.
In this article, as part of the SAVE strategy, we explore how the most innovative companies identify winning ideas, projects and products to work on, whilst conserving cash and time. We will guide you through the process of testing and validation of ideas, what a desired output of an experiment should be, how to create value for your stakeholders, how to determine the price for your products and services, as well as how to we make decisions about where to invest next.
The disruptive forces that have been released by the recent global health crisis will create rapid and possibly permanent shifts in social norms and customer behaviors. We are witnessing a swift shift to the digital. As conventional retail businesses tumble one by one, the space for bold new initiatives has been created.
Caught between the pressure to rapidly reinvent themselves and rising revenue and workforce losses, retail businesses face the unparalleled crisis in their history.
But the opportunities for retail are as significant as the risks.
Clearly, the solution for significant savings of resources and long term sustainability can only be found in technology — automation, digitalization, and the platformization of retail. Something we call Retail Reloaded. Being exposed to the cutting edge of retail technology development, we often ask ourselves a question: How can we help retail businesses effectively adopt new technologies? How do we help our customers innovate? And, how do we help them to create these new opportunities with the minimum risk and waste involved?
It’s called Discovery-Driven Business Planning and it is the backbone of every sane yet daring agile new initiative or venture.
The purpose of the Discovery in innovation and any risky new project for that matter, as explained in this introduction to design thinking, is not to provide elaborate product or business strategies. Its goal is to uncover underlying issues and offer solutions for initiatives early on, in the planning phase, to prevent expensive mistakes. Furthermore, it is utilized during the initial setup and throughout the development phase to minimize bottlenecks in delivery.
Discovery is a fairly loose system of trials and errors through which we reality-proof the initiative’s initial assumptions, gradually increasing the degree of accuracy and the probability of a successful outcome. It is a creative process that knows how to deal with a lot of uncertainty and surprises. Hence the name Discovery.
To avoid falling prey to the common trap of never reaching the desired conclusion when dealing with fluidity which tends to escape our ability to measure, it is crucial that we define the boundaries of discovery through milestones and validation mechanisms.
We must make sure that each hypothesis can be measured, at first somewhat clumsily, and then with increasing precision. Setting up measurable milestones will inform our decisions at crucial checkpoints going forward: to stick with an evolving hypothesis, to pivot to a new one, or to stop the initiative altogether.
Validation sources and metrics
The validation of initial assumptions may come from our experience with similar situations, the advice of industry experts, customers, internal stakeholders, engineers, product usage reports, published information, support tickets, win/loss statements, or other listening mechanisms.
How much data is enough for an experiment to be valid? Which data is relevant?
A successful experiment will have both qualitative and quantitative validation defined.
Quantitative (measurable in numbers):
- 100 new users will click on the new Account section tab in the app to access their membership preferences.
Think of qualitative as soft data, something which can’t have a number put on it. Something helping you to build a psychological profile of your customer or their situation. In this case, qualitative data can be attributes used by our early adopters:
- I feel the features are easy to access. For me the screen is clear and I can see the actions to take.
Qualitative data brings some context to the numbers. If we have 100 new users clicking on a new Account section, qualitative data tells us why and what goes on in their mind while doing so.
When this data is grouped, we learn the perceived value of the feature, product, initiative or venture that we want to create. Does it make sense to invest in it? If the value proves to be low and in a risky zone, usually, there are three options to choose from:
- Iterate a prototype until you hit the mark. This is where savings are to be made as you are iterating a prototype to get what you want. At this stage you do not want a large scale system.
- Change the hypotheses. This is also fine but you will need stronger and deeper data to support such a decision.
- Adjust the desired outcome. As the experiment unfolds, with an influx of data, we may come to realize that we’ve missed the mark on expectations and desired outcomes. No worries, it’s not just you. This happens all the time. Discovery is not a linear process. It has many moving parts, which sometimes may suggest that we simply need to adjust the desired outcome. In other words, we need to keep discovering.
Remember: data is informative, not directional.
No metric should be examined in separation from the greater picture. Connections between data need to be understood and evaluated. Good experiments will take many metrics into account and observe how they move each other. These correlations are the mechanics of metrics, they uncover the dynamics behind the data and user flows.
The most informative metrics are composite and dynamic. They care about progress over time, taking into account multiple indicators, e.g. daily signups growing, churn rate dropping, more users going through a certain flow, less support tickets being submitted, more engagement on social media, etc.
As a retailer, you know that there’s nothing more valuable (and harder) than gaining and maintaining loyal customers. Customer lifetime value is the holy grail of retail metrics. In today’s world of abundance, however, delighting customers and meeting their needs, although important and necessary, is not enough for a lifetime. Innovation must be seen as an investment in the quality of life, time savings and personal capabilities of your customers. It is a worthwhile endeavour, is it not? We use Discovery to uncover how the innovations we consider investing in may increase the value of our customers.
Finally, let us not forget the North Star metric which keeps different teams within a company on track about the company position reflected in these three metrics: revenue, customer retention, and progress. These three metrics often govern any product and retail business planning decision in the end.
Sometimes, we win by failing
Failure is an option here. If things are not failing, you are not innovating.
In classic terms, failure means: not enough data, users, or the data doesn’t speak.
In design thinking, however, the process could prove its own goal. Process for the sake of learning the process, if you like. The question here is not whether the KPIs were reached. Every product is different, every problem requires a unique solution. Often, it may seem that the team had wasted time building a prototype feature they dumped in the end, but the real question is—how much value did they derive from building and testing it? Did it lead to more valuable insights about a customer that a team can now use to pivot their focus in a new direction? Perhaps, they uncovered a better solution? Understood their mistakes? Perfected their design thinking capacities?
Through discovery, teams gain skills to build better products faster with confidence in the predicted outcome.
The project reaches an experimental cul-de-sac when the learning curve starts dropping. This is when we stop the experiment, step back and start analyzing the reasons and get ready to start anew with clearer idea of what the desired outcome should be and how to test it more efficiently.
You’ve got to start with the customer experience and work backwards toward the technology, not the other way around.
—Steve Jobs quote—
When done right, we can expect all or some of the following outcomes from the Discovery phase:
- Technical, sales and process PoCs
- Product prototype or MVP
- Solution with achievable project market fit
- Agreed North-Star metrics
- Mapped-out decision-making process
- A document with Key Learnings
- Mapped-out user journey
- Value proposition
Roadmap is one of the discovery phase’s dynamic outputs which in the given moment offers the best possible plan. It lines up the set of currently absent product attributes, which are deemed to be the quickest way to capture monetizable value, if delivered according to the proposed order. The roadmap remains flexible as the experiment unfolds and more data and learnings are gathered.
At HTEC, our timeline usually looks like this:
Week 1 – set the problem hypothesis based on data and conversations with a client.
Week 2 – define the validation process, goals, metrics, and target audience.
Week 3 – start user interviewing/testing (validating the hypothesis) and create a prototype
Week 4 – test the prototype, write specifications with engineering.
We seek to incorporate our knowledge back into the prototype or MVP. We will then A/B test to see if it made the difference.
Finally, an experiment will record a set of insights and conclusions on how the process could be improved and the lessons learned. Gitlab, a 1000+ ppl forever remote company, has created a methodology widely used in agile product development.
You should look to build your own once you have the experience and know what works best for your product/team/business.
The discovery process is endlessly repeatable. The source of growth is not so much the efficiency but a long term value the product creates for its customers.
A product team will typically lead the process, ensuring that the value is distributed between other teams which through their work then create more value for the organization. Discovery benefits multiple teams in many ways, such as:
- Sales – engage with beta users, nurturing them to become the first buyers.
- Marketing – hands-on learning about which value proposition sits best with potential customers.
- Developers – strong bonding with users and understanding their problems first hand.
Remember: The purpose of MVP is testing. Not to provide a market-grade level of value.
The most common mistakes happen when companies go straight into the production of a first version which they name an MVP, but there was never really any MVP to start with. When this V1 hits the market, it serves the purpose of an MVP, as the testing which wasn’t properly done in the discovery phase now happens with real users. This is expensive. It puts pressure on developers who now have to put out the fires instead of focusing on product improvements, while support struggles on the front line and the whole thing becomes painful. The sense of achievement is lost while teams and customers get frustrated. Ultimately this type of approach only serves to make everyone more inclined to drop out.
If there’s anything we’ve learned being a retail technology group and engineering company working with award-winning innovative products and ventures, it is that no matter how well established and market savvy you are—never underestimate the value of preparation and testing.
Being deeply immersed in the business, we think we know what customers want. But the times are changing as we speak and so are the trends. Retail is among the most volatile and fastest-changing industries. It is now heavily dependent on new technologies for progress and, for many businesses, even for survival.
According to Statista, online sales, led by Amazon, reached $3.5 trillion in 2019, which was 14% of the global retail sales. This year, due to COVID-19, the situation looks even grimmer for non-digital retail. The numbers are crumbling. We are looking for solutions, working closely with retailers to help them stay on top of the situation by automating operations, accelerating their digital transformation and adapting customer experiences.
Last year, we were invited to work on a project with the world’s leading haute couture department store, on gamifying their shopping experience. Since the retailer’s main focus is luxury shopping in-store, our task was to envisage the physical store experience as a virtual one that lives within a customer’s mobile app, allowing them a far greater degree of interaction with products as they browsed. Of course a significant additional aspect was that the overall experience would be self-serve. Unfortunately, the project stalled due to typical issues around lack of budget and other focus. But probably it ultimately died due to a lack of ambition. What a pity, as such a capability right now would be exceptionally useful.
In a socially distanced era, having already evolved and weaponised such a self-serve experience would be a huge advantage for a department store. It showed how even the most established retail businesses have been sleepwalking when it comes to digital transformation for a long time. Covid has laid bare those weaknesses.
To hypothesize and prioritize what to build, buy or partner with when it comes to technology, teams inevitably spend time mapping out potential and experimenting around value streams. We ask: what brings the most value to the largest number of customers and how best can you build those new functionalities and features?
Netflix’s visual evolution is a time-lapse of the company’s quest for a clear value proposition as their product evolved. Market conditions and user demands changed, and so did the Netflix visual identity and value proposition. They constantly searched for the answer to a single question: “What is Netflix experience?”. In the beginning, the focus was on how it brings families together, but lately, it has shifted back to its earlier assumptions which focus more on the content offer and the ease of use “WATCH ANYWHERE. CANCEL ANYTIME.”.
What value does your product create for your customers?
Discovery will tell.
An important determining factor of the product’s success is: how much are customers willing to pay for the value it creates?
When interviewing early adopters, talk about what they would do if your product didn’t exist. What is an alternative? How much of the value does it cover? Does it take more than one other product to provide the same value? How much do they cost? Do customers consider your product a must-have or a nice-to-have? How well does it fit into their life or their business flow?
The monetization model is an important part of any MVP, even though it doesn’t always feel natural to think about pricing at such an early stage. An MVP may not cost anything, but a proxy for money/value can be the time users spend with the product, for example. Capturing monetization value from the market is a process with a set of leavers, some of which get developed over time such as usability or loyalty and they all affect the price.
Let’s continue with the Netflix example. They think about monetizing the feeling of safety and coziness when, for the duration of my favorite show, I’ve escaped everyday reality and I feel that it improves the quality of my life. By this logic, the ideal pricing model would be a price for each minute of feeling good. Of course, this doesn’t work, so what Netflix ends up doing is a subscription model that’s affordable and helps to popularize the product. Ultimately it puts Netflix in control of the free time of millions of people around the world. Priceless! To choose this model, they pondered on two things:
What is measurable?
- Feelings per minute is a vague and cruel measure that surely wouldn’t sit well with customers.
What is comparable?
- How much does the rest of the industry charge? Price consideration comes before the actual product experience in most cases.
Discover the right initiatives.
Discovery-driven planning essentially asks the question: how do we make good decisions about where to invest next?
By experimentation, we identify and iteratively test, at a granular level, what our customers want or will want in the near future.
On another level, when a project is in motion, discovery helps forward-thinking teams mitigate business risk, whilst considering the feasibility and usability risks that come with any new initiative. In our next article read about the things you can do today to future-proof you next retail investment.
Discovery-driven design thinking is a powerful tool for strategic new business planning. But it is laden with uncertainty such as product development, changing markets, technology development, mergers and acquisitions, strategic alliances, even major changes within a company’s structure and culture. Basically any innovative endeavor with a great number of unknowns. But in the beginning, all you need is an open mind and an inquisitive spirit.
If the whole thing sounds overwhelming, start with the smallest thing you can do right now to validate your idea. Write a hypothesis on a piece of paper, draw a straw man of your solution or talk about it with the first person you meet. It only takes a tiny flame to start a forest fire.
If you need professional technology advice on any new business ideas that you have, use the form below to get in touch with us. We can help you discover and build products that will accelerate your digital presence with your customers and prevent you from spending resources on the ventures that don’t stand a chance.