A summary of the Product themes most relevant to early stage startups, and some practical suggestions on how to deliver results in each area
Turning an idea into a billion dollar business is the ultimate goal of many entrepreneurs. At The Venture City, we have the privilege of helping early stage technology entrepreneurs build the solid foundations that they need to achieve unicorn status.
Our experience with companies in our Growth Accelerator suggests that by far the majority of the advice and assistance we provide falls broadly under the “Product Management” umbrella. While each team and business idea is unique, there is an essential list of Product topics that we use as the foundation for more detailed discussions later. I thought it would be helpful to summarise the conversations that we regularly have around these key Product themes, along with some practical suggestions on how to deliver results in each area.
The Product themes covered in this article are:
- Market research and analysis
- Customer research: Understand your customers’ needs
- Competitor research
- Product Vision and Product Strategy
- Analytics mindset
- Setting goals: Understand where you want to go
- Developing a roadmap
- Testing and prototyping
Founding teams need to find a way to allocate responsibilities for a range of critical roles. First-time tech founders often do not fully appreciate the importance, scope and skillset of the product manager.
Without a dedicated product manager in place, there is no-one to act as the guardian of the product vision, strategy and design. For example, I have seen CEOs prioritise sales revenue and change roadmaps frequently to accommodate client-specific requests that aren’t applicable to the broader user base, and/or CTOs prioritise backend updates at the expense of an improved user experience.
I strongly advise founders to bring on a dedicated product manager as early as possible, or at the very least, develop a “Product Mindset”. In particular, this means finding the balance between Technology (understanding what is possible and what is feasible), Users (what is useful and desirable), and the Business (what products/services are marketable and distributable). Combined with a bias towards action, this makes the product manager an indispensable member of an early stage startup team.
2. Market research and analysis
Understanding the “size of the prize” is a sensible starting point when developing a new product. This is an initial filter to identify markets with the largest opportunities.
There are three concepts that need to be assessed:
- TAM (Total Available Market): total (global) market demand for a product or service
- SAM (Serviceable Available Market): the segment of the TAM targeted by your products and services which is within your geographical reach
- SOM (Serviceable Obtainable Market): the portion of SAM that you can feasibly capture
The best market sizing estimates are derived using both top-down and bottom-up approaches. These can be validated using industry reports, expert interviews, benchmarking competitors, and sensitivity analysis. It is important to understand which assumptions your estimates are most sensitive to as these represent both your biggest opportunities and biggest risks simultaneously.
In addition, the sooner you can identify your target customer segment, the better. While larger customer segments generally represent a greater revenue opportunity, they aren’t necessarily “better” than smaller segments, since the former they tend to be more heterogeneous and more challenging to service. A clear customer segment definition ensures that your efforts are aligned with your business goals/objectives.
3. Customer research: Understand your customers’ needs
It goes without saying that those businesses which do the best job of meeting their customers’ needs and addressing their pain points are most likely to be successful.
Generating customer insights doesn’t have to be complicated. If you’re starting from scratch, start with industry reports, talk to experts, and ideally potential customers. Focus groups and surveys are also good ways to identify unmet needs and to gather feedback about planned features.
Remember that what people say they will do is often different to how they actually behave, particularly when it comes to purchasing behaviour. So the sooner you have a product in place that you can put in front of users, the better.
Once your website or app is up and running, customer behaviour metrics (e.g. registration completion rate; checkout completion rate; interaction/activity metrics) can reveal areas for improvement, as can drop-off rates at different stages of the customer journey/user funnel.
Critically, you should develop a range of customer-centric metrics to ensure that customer activity, satisfaction and feedback are being measured, tracked and actioned.
4. Competitor research
Understanding who your competitors are is a great learning opportunity: not only can it help you identify customer pain points (which you will go on to solve), but it can give you insights about the critical steps in operating a business in your market, areas for improvement, and avoid making the same mistakes as others.
Don’t be put off just because a market has well-established incumbents. You should respect your competitors, not fear them. The landscape is littered with the corpses of tech giants who failed to innovate and were buried by upstart new entrants: Kodak, Blackberry and Nokia come to mind.
Also, a crowded market does not necessarily mean that your product won’t be successful. Many markets are big enough to accommodate multiple players. Electronic payment platforms are a great example: PayPal, Braintree, Stripe, TransferWise, WePay, Venmo, Square, Google Pay, Amazon Pay… the list goes on. Of course, a crowded market means you’ll need to work harder to differentiate yourself.
Importantly, remember that you don’t choose your competitors; your customers do. Even if you think that existing, competing products are terrible, ignore them at your peril. Do not underestimate the pain that users will go through if they see value at the end of a process. If all you’re doing is developing a prettier website and reducing the number of steps in a purchasing flow (for example), the incumbents will beat you every time if you do not create genuine value for users at the end.
5. Product Vision and Product Strategy
Every new product needs a vision. It is a compact expression of the overarching goal i.e. the ultimate reason for creating the product. It describes the future we are trying to create.
Equally as important is the product strategy i.e. the steps to achieve that vision.
A Product Vision can be expressed succinctly in the following format:
For <who/target market or customer>,who want to <do what/solve what problem/statement of the need>,the <product/business name> is a <product category>that <key value proposition/key benefit/reason to buy>.Unlike <primary competitive alternative>,<our product/business name> <statement of primary differentiation>
For example, Microsoft might express their vision for the Surface tablet as follows:
For the business user who needs to be productive in the office and on the go, the Surface is a convertible tablet that is easy to carry and gives you full computing productivity no matter where you are.
Unlike laptops, Surface serves your on-the-go needs without having to carry an extra device.
Your Product Strategy, on the other hand, is all about how you will go about achieving the Product Vision. Product Strategy is most effectively expressed by a prioritised Product roadmap (prioritisation and building a roadmap are discussed later in this article).
While a product vision stays relatively constant, product strategies will likely change as customer feedback is received and the market itself evolves. Successful entrepreneurs are those who understand that they need to be ready to adapt and change their product strategy, particularly when they are developing a product from scratch. Changing product strategy (aka a “pivot”) is extremely hard work and tends to be very disruptive; however, the entrepreneurs which I have seen successfully emerge from the process do so with stronger teams and a superior product.
6. Analytics mindset
Developing a data-driven culture is fundamental to making consistent, objective decisions. Analytics provide a framework that makes it easy to measure, compare and evaluate trends, progress, targets, and achievements.
A data-driven culture does not mean that every decision should be based on numbers alone — gut-feel and experience are, of course, invaluable, particularly in early stage startups. In addition, using the wrong metrics or measuring them incorrectly/inconsistently can lead to poor decisions. However, when implemented correctly, metrics/analytics are critical to a business’ success. As Peter Drucker (the inventor of modern business management) said: “If you can’t measure it, you can’t improve it.”
Finally, having a data-driven culture does not mean trying to develop and monitor hundreds of metrics. Instead, you should identify those that are most important so that you are not overwhelmed and can detect clear signals from those metrics. These core metrics (aka “KPIs”) will generally align with your goals (see OKRs) and be summarized into a Product Dashboard.
A Key Performance Indicator (KPI) is a metric that measures how effectively a company is achieving key business objectives / goals. Note that all KPIs are metrics, but not all metrics are KPIs.
The definition of every KPI will…
- …start with a particular metric (e.g. Revenue generated from mid-tier business customers)
- …and has a clear, specific objective (e.g. Increase revenue by 20%)
- …that can be measured and tracked over a particular period (e.g. over 6 months)
- …measured on a regular basis (e.g. every two weeks)
- …with the ability to influence the outcome (e.g. by hiring additional sales staff, and by encouraging existing customers to buy more product)
- …and clear assignment of responsibility (e.g. The Head of Marketing is responsible for this KPI)
The choice of which metrics to monitor and track in a Product Dashboard will vary from company to company, and your objectives. The overall idea is to:
- Select a limited range of metrics, that can be tracked over time…
- …That focus on critical pages (e.g. Home Page), flows (e.g. registration; checkout), or events (e.g. live help interactions)
- …To allow you to detect when something isn’t working well, and give you insights as to how to improve your product.
For example, many companies start with an AAA (Acquisition, Activation, Activity) model:
- Acquisition (Where are users coming from?): #Users; $CAC (Customer Acquisition Cost)
- Activation (What do users do when they first interact with the site?): #Downloads; #Signups; %Conversion rate
- Activity (What do visitors do when they’re on the site i.e. engagement? How do users come back i.e. retention?): #Unique users; %Conversion rate; %Repeat visitors; %Churn; $LTV (customer LifeTime Value, particularly vs CAC)
7. Setting goals: Understand where you want to go
If you don’t know where you want to go, then there’s no way you can develop a plan to get there.
Successful entrepreneurs understand the importance of having clearly articulated goals. Well-defined goals complement a clear vision, and are particularly important when it comes to prioritisation decisions and building a roadmap.
OKRs (Objectives and Key Results) is a framework for defining and tracking objectives and their outcomes. OKRs aim to connect objectives to measurable results. When everyone in the company/team understands where they need to go, everyone can work together towards that goal.
An OKR can be generalised as “I will [Objective] as measured by [this set of Key Results]”.
OKRs are usually planned for a specific period of time e.g. next 3, 6, 12 months. OKRs consist of a list of three to five high-level objectives e.g. “Successfully launch V2 of our widget”. These can be set at the company, team, and/or personal level, as long as they are all aligned with those further up the hierarchy. Early stage startups will generally only set these at a company level.
Each of these objectives is accompanied by at least one (but generally three to five) key measurable results e.g. “Conduct at least 20 face-to-face interviews with users”, “Increase Net Promoter Score from X to Y”, “Improve sign up to trial ratio from X% to Y%”. Each key result is tracked with a progress indicator on a scale of 0%-100%.
In the early stage startup world — which is always a world of limited time and resources — prioritisation is probably the one task that separates successful startups from those that fail. Startups need a way to make the difficult decisions around ranking complex options. Prioritisation effectively helps teams make the “do the right things”.
I’ve seen too many entrepreneurs fall into the classic traps of not doing some sort of formal prioritisation exercise:
- Developing functionality demanded by an insistent client, rather than considering their broader use base
- Changing priorities week to week based on whatever advice a “guru” had most recently delivered
- Diving into new ideas, rather than optimising projects that have already been developed
The bottom line is that prioritisation forces you to think about why a project idea will have impact, and to be honest about the effort that’s needed to achieve it.
These two concepts — impact and effort — feature in many of the prioritisation frameworks in one form or another. In terms of potential impact (or benefits), the most important decision is to identify the metrics will you use to measure the success of your initiative. You can use real-world data — or, if not available, educated guesses — to score an initiative on its ability to affect those metrics e.g. “higher conversion rate for sign-ups”, “maximise revenue”, or “reduce internal costs”. In terms of effort (or costs), you can evaluate an initiative on its complexity or level of difficulty to implement, or its hard-dollar operational costs, or the risk that customers won’t adopt the new feature.
There are a range of prioritisation frameworks which vary in sophistication and objectivity. Multiple frameworks can be used simultaneously: each gives a slightly different perspective.
Three popular methodologies I see early stage startups are “Effort vs Impact”, “RICE: Reach, Impact, Confidence and Effort”, and “Weighted scoring (aka “Scorecard”)”.
9. Developing a roadmap
Once you know where you want to go, now is the time to develop a plan about how to get there. Armed with your product vision, a shortlist of clearly defined OKRs, and a prioritised list of initiatives, you are ready to develop a product roadmap.
A product roadmap is a strategic, high-level, visual summary that maps out the vision and direction of your product offering over time. It is used to:
- Describe the business activities that individually and collectively support the organisation’s goals. It connects individual features and projects into something bigger, which helps motivate teams when they understand how their work fits into the broader plan.
- Present high-level initiatives and the planned steps to deliver those projects. Transparency increases the buy-in from senior management even when things don’t go as expected. It also makes the product vision and associated priorities explicit, making it easier to have objective discussions about evaluating new initiatives and changes.
- Keep teams on track in executing that plan. Teams are clear about their priorities and expected deliverables. With a clear vision about what comes next and why it is important, teams are motivated to overcome day-to-day challenges
- Communicate direction and progress to internal teams and external stakeholders. By monitoring progress against planned goals, teams can assess whether they need to make minor tweaks or wholesale changes to the existing plan.
- Co-ordinate the development of different products. Many products have dependencies on other products. Roadmaps make these interlinks explicit and indirectly communicate the consequences of delays and missed goals; and
- Foster transparency in order to manage customer expectations. Customers can easily understand what is currently being worked on (and is expected to be delivered in near future), versus projects that need further work
- Start with your product vision. The product vision defines your outlook for the product, where it is headed, and what your team will build. The customer should always feature prominently in this vision.
- Incorporate the product environment/ context. Insights about market size, who the target customers are, what those customers need, and an understanding of the competitive landscape should be incorporated into both project selection and prioritisation decisions.
- Focus on goals and benefits. Focus on goals, objectives, and outcomes e.g. acquiring customers or increasing engagement. Focusing on solving customer problems shifts the attention from playing feature catch-up with competitors and avoid working on pet features of individual stakeholders.
- Tell a coherent story about the likely growth of your product and don’t oversell it.
- Keep it simple! Resist the temptation to add too much detail to your roadmap. Keep the features on your roadmap high-level and derive them from the goals
- Actively collaborate with stakeholders to ensure buy-in. The best roadmap is worthless if the people required to develop, market, and sell the product don’t buy into it.
- Make data-driven decisions. There will inevitably be questions about project selection and priorisation. Be prepared to justify your decisions with the right sort of data.
- Expect the unexpected. It is inevitable that some features will take longer to develop than planned, new requests will come in from stakeholders, and bugs will creep in. Best practice suggests incorporating 10%-20% capacity leeway to deal with these unforeseen events. Some difficult compromises may be required in the trade-off between quality, scope and time.
- Have the courage to say no, to prevent an overload of features in your roadmap. While buy-in from key stakeholders is important, you should resist saying yes to every request. Use your product vision to make the right decisions. Have the courage to say “no”. Steve Jobs famously said: “Innovation is not about saying yes to everything. It’s about saying no to all but the most crucial features.”
- Communicate timelines. This is probably one of the key objectives of a roadmap. Timelines are helpful for many reasons, from setting expectations and budgeting, to co-ordinating with other product launches.
- That said… think twice about adding timelines, dates or deadlines to your roadmap if used for external stakeholders. No stakeholder will understand or even be interested in the reasons why you haven’t yet delivered if deadlines are missed.
- Make sure your roadmap is measurable, by adding measurable goals and KPIs. These are the OKRs developed earlier. This means you can objectively measure progress (or lack thereof), and assess whether you have met the goal or not
- Create a rough estimate for each feature (number people and required skills) to determine the viability of a feature. Together with the development team, develop top-down estimates of the number of people required to deliver the project, and also the cost for facilities, infrastructure, materials, licenses, and other relevant items.
- Allocate responsibilities. Make sure that teams understand their priorities, responsibilities and time allocation from the start.
- Review and adapt your product roadmap on a regular basis. A product roadmap should be treated as a living document and updated continuously throughout the lifecycle of a product. Creating value for the customer is not about sticking to a plan, but being able to respond to change. Make sure you (over) communicate to stakeholders when these changes occur.
Finally, how will you know if you’ve been successful in creating your product roadmap? A good product roadmap is one that it’s visual, accessible and clear enough for anyone to scan for answers to the following questions:
- What are we doing?
- Why are we doing it?
- How does this tie back to our goals and objectives?
10. Testing and prototyping
“You can’t know every answer, and even if you think you do, your users may not agree with you.” — Me.
Too many entrepreneurs spend months or years developing a (what they regard as) an innovative product, only to have their dreams of fame and fortune shattered when their product finally sees the light of day because either (a) other people don’t care actually about the problem they were solving, or (b) that their solution isn’t suitable or (c) a better alternative already exists.
Individual features are equally vulnerable to this pitfall. Businesses often only find out that they’ve built the “wrong” product or feature after its launch, and hundreds of development hours have already been committed. For an early stage startup, with limited resources, this could have serious negative consequences.
Marty Cagan at SVPG, believes that there are “two inconvenient truths” associated with new product development:
- The first truth is that at least half of our ideas are just not going to work;
- The second is that even with the ideas that do prove to have potential, it typically takes several iterations to get the implementation of this idea to the point where it actually delivers the necessary business value
Like me, Marty is a firm believer that teams should “fail fast; learn faster”. Product managers understand that testing an idea before fully investing in it means many ideas can be evaluated quickly and cheaply, allowing the team to focus on those which show most promise. For example, one of the startups in the healthcare space at The Venture City ran over 50 experiments in just a few weeks around improving their user activation and activity. They were able to identify a handful of key changes that they then launched across the site, resulting in significant improvements to their user engagement and retention.
Along with prioritisation, I would suggest that having a mindset around testing, experimenting and prototyping is perhaps the most predictive success factor for an early stage entrepreneur.
It is probably worthwhile emphasizing that “fail fast; learn faster” is not an excuse for bad decisions and preventable mistakes. An experiment which shows no improvement in registration rates is not a failure, but launching a product which ignores a critical component of a customer’s workflow is. The experimental mindset focuses more on the “learning” aspect than the “failure” component.
Product Discovery is a set of techniques which allows you to to focus on learning as quickly and inexpensively as possible. It helps you figure out “what to build” (as opposed to “how to build it”, which comes later). It ensures teams focus on building products that customers genuinely care about, and aren’t simply a “nice to have”.
Product Discovery starts with a hypothesis, for example: “Reducing the registration process from three steps to one step will increase the registration rate for new visitors by 25% within 1,000 visits to the home page.” Or “This subject line will increase open rates for newsletter subscribers by 15% after 3 days.”
Once that is clear, you need to create a plan to test that hypothesis (aka an “experimental design”). Here are some practical tips for sensible experimental design:
- Be clear about what you want to learn and only change on variable at a time
- You can use both qualitative (e.g. surveys and customer interviews) and quantitative (numerical data) methods, but make sure you understand their limitations. For example, qualitative methods help us understand why something may or may not be happening but it can be hard to generalize beyond the observed specific findings. Quantitative research is great for uncovering how a large population behaves, but it can be challenging to uncover the reasoning behind their actions
- Always start with an insight as to why your change might drive the desired impact. Without this underlying logic, it’s easy to have false positive (e.g. where one design looks like it converts better than another, but the results are just due to chance)
- More variations lead to more false positives. Run fewer variations and have a good reason for testing each one
- Run the experiment with users/customers that fit the target market profile
- Before the experiment even starts, think through what data you will need to drive decisions at the end of the experiment. This will ensure you will collect usable data
- Before you draw a conclusion, ask: “What else could explain this result?”
- Do not blindly follow the results. This can lead to implementing false positives and over optimization
This has been a whirlwind tour of some of the core Product Management themes that we believe are critical to success for early stage startups. Each area probably deserves a separate, more detailed post, although this has hopefully given you a flavour for some of the considerations and challenges of each.
Of course, this is not a comprehensive list of all relevant Product topics for early stage startups. We also think about Product processes and tools, UI/UX flows, Product marketing (particularly e.g. CPA, LTV, and conversion rates), Customer support (associated processes and metrics), and how ready/capable the product is for Internationalisation, among others. Watch this space!