Mentoring Beyond Bragging Rights and Looking Good

This is part five from a series of insights drawn from 50 in-depth interviews taken over the past two years and 126 responses to a survey we sent out recently. To better understand our process and the methodology behind these findings, make sure to read Disciplined Accelerator: Introduction.

Most programs face issues with mentoring—from finding the right mentors to keeping them engaged, to getting feedback and improving the mentoring program.

Findings

  • Matching mentors with startups is a tedious process for various reasons. Many startups chase famous/known mentors, who have less availability, while disregarding less popular mentors who might be more willing to give time and help. Matching mentors with startups in the beginning is not a guarantee of effective mentoring throughout the program.
  • A lot of programs present an impressive mentor pool to startups, however more than 70% of the mentors fail to deliver on the initial expectations. Lack of commitment and engagement is a frequent problem and few accelerators have managed to find the right incentives. Some accelerators rely on paid mentors (whom should rather be called “consultants”), an approach that results into better retention of mentors but is hardly affordable for most programs.
  • Remote mentoring sessions are harder to schedule and keep track of (mostly because of mentor commitment/engagement decreasing after the start of the program). On-site, face-to-face sessions are more effective usually, as mentor can dedicate a longer period to mentor 2-3 startup teams.

Insights

  • Motivation and behavior is radically changed by including any external incentives (money, equity). Each approach needs a different mentor selection, onboarding, and managing process. “Free” mentoring often means low commitment and the solution is counter-intuitive: ask mentors for more. By getting them involved in scouting, reviewing applications, onboarding, evaluation sessions, demo days, and other activities will increase their motivation and engagement.
  • Build a diverse mentor pool by including several categories: industry executives have an increasing interest in the startup world, the energy and grind being different from their regular workplace, and can be a source of great connections and customers; successful entrepreneurs and alumni who have already gone through the program and had their startups funded are happy to share their unique experiences and viewpoints; investors have an ongoing interest in your startups and will provide healthy and candid advice, while keeping them engaged might result in easier follow-on financing and support; accelerator staff might know a lot about what startups go through, especially in the early stages.

“We get some of our best coaches/mentors from BigCo execs leaving their corporate jobs and who want to get into the startup space.”
— Jackie Willmot, XLerateHealth

  • Onboarding and training the mentors is often overlooked. One of our survey respondents, Accelerace (Denmark) has been referenced many times for having one of the best training programs for mentors. Introduce your mentors to all the steps in the program, the people involved, the deadlines, the schedules. Brief them in advance on the stage of each startup entering the program. Train them on how to be better teachers. Some mentors may know the business side of things but lack skills in teaching forward their knowledge. They know science, and data, and metrics but often encounter issues in dealing with the entrepreneurs at an emotional level so understanding also the different aspects in startups vs corporates (Lean Startup approach, validating experiments and assumptions, dealing with uncertainty and chaos etc.).
  • Keep your mentor accountable by signing a commitment agreement when you onboard them (similar to a volunteering agreement). It might seem too much to ask busy people to do this, but if they won’t do it how can you expect them to deliver on their promises? Another thing is to separate your pool into “mentors” (the ones who are truly committed and deliver on their promises), “experts” (the ones who will help once or twice in a while, but won’t commit to get involved recurrently), and “contacts” (the ones whom might not be committed or engaged but still be a useful connection). Ask your engaged mentors to bring other people in their network as mentors, as long as they are involved in their onboarding and engagement—this way you will be able to create a strong support team for your programs. In the end, it’s nothing different than a volunteering program for successful, busy people.

Education Is Essential for Incubation but Disruptive for Acceleration

This is part four from a series of insights drawn from 50 in-depth interviews taken over the past two years and 126 responses to a survey we sent out recently. To better understand our process and the methodology behind these findings, make sure to read Disciplined Accelerator: Introduction.

Before sharing the findings, I’d like to clarify the classification system that we use when it comes to startup programs. The market uses acceleration, incubation, and other terms in a very inconsistent way (it seems everyone has a different understanding of what the terms mean).

We aim to establish a consistent naming system based on semantic consideration first (incubation means to bring something to hatching, while acceleration means to increase the speed of an already moving object).

  • Pre-incubation: Applies to founders/teams with an intention to start a business or a rough idea. The process consists mostly in education and primary market research (customer discovery). The end goal is to get to a complete & researched business plan, canvas or pitch deck.
  • Incubation: Applies to teams with an initial business understanding (not just an idea). The process involves education, customer discovery, mentoring and solution development. The end goal is to launch an MVBP (a minimum viable business product — that helps prove business assumptions, not product usage assumptions).
  • Acceleration: Applies to teams with an MVP or even initial customers. The process should include minimal education, and be a more customized approach to help teams to get from initial revenue to predictable/recurring revenue. From our experience, education in this stage is defocusing founders from having clear goals.
  • Growth: Applies to teams with recurring revenue and modest growth. The process should be focused on sales, marketing, mentoring and support, the end goal being increasing growth and retention metrics.

Some programs may include more phases, but in our experience, building a successful business takes at least 3 months per each stage (especially considering that in the pre-incubation phase many founders have other commitments or jobs preventing them from being available 100% of their time).

Findings

  • Each accelerator has different requirements when selecting candidates and startups are at different stages of maturity when they enter the program. Applying the same curricula to all of them is not efficient but seems to be the ‘default’ approach because ‘everyone is doing it’.
  • Founders lack interest and don’t pay attention if they participate in a workshop that does not fit their current needs. They come to see this part of the program not as an opportunity to learn and grow, but as a tiny box they need to mark done in their quest for funding.
  • The topics approached are not often relevant to both the stage the startup is in, and the people participating in the workshop, their experience and specific needs in each journey. The less homogenous a program cohort is, the more difficult is for the curricula to be helpful and relevant to the teams. Earlier stages (pre-incubation programs) can fit a curricula easier than later stage (acceleration or growth programs).
  • Some workshops defocus teams from focusing on the end goal, as they jump to the opportunity of applying in practice what they learn, despite not being strategic.

Thoughts

  • Pre-incubation programs should have 50-75% educational content (the rest being dedicated to research). Mentoring is not very useful at this stage (unless mentors are the educators).
  • Incubation programs should not have more than 50% education, to allow time for experimenting, testing assumptions and ‘getting out of the building’. Too much education will distract teams from connecting with customers. True useful knowledge in such programs is found in customer conversations, not workshops.
  • Acceleration should not be an educational program ending with a Demo Day, but a process aimed at helping build successful businesses by offering the right support. Build your acceleration process to help you reach your end goals, considering the available resources. In any case, education should come in the form of mentoring and customized support to help each startup on their journey.
  • Consider creating a library with curated educational resources (and experts at hand) that will be accessible to your teams and be a reference point in case of need.
  • Don’t forget to educate your mentors. Some of them have different views on building businesses (especially those who work in larger corporations), which can result in conflicting or hard-to-implement advice in a startup. At least an introduction to Lean Startup, Business Model Canvas, and Disciplined Entrepreneurship is recommended.

Lack of Reporting Discipline Is Most Often the Accelerator’s Fault

This is part three from a series of insights drawn from 50 in-depth interviews taken over the past two years and 126 responses to a survey we sent out recently. To better understand our process and the methodology behind these findings, make sure to read Disciplined Accelerator: Introduction.

Findings

  • Collecting data from startups takes up a lot of time and energy. There are no proper incentives that are strong enough to keep founders from moving on to their next stages of their startup journey, leaving accelerators stranded.
  • 42% of all accelerators struggle with startups reporting. 30% face this issue mostly after the program ends. 28% deal with it both during and after the program.

  • There is a strong connection between the number of startups each accelerator takes per program and the number of accelerators mentioned reporting as a main challenge. Half of the accelerators which accept fewer than 20 startups/program have mentioned no problem with reporting, while 60% of accelerators that take in from 30 to over 100 startups/program mentioned having this issue.
  • Reporting issues are considered to be caused by lack of a proper system to collect metrics, knowing the correct metrics to track for each type of startup based on their business model and the stage they are at, and a lack of discipline from founders that fail to comply with this request.

Thoughts

  • Most founders are talented business or technical professionals, but lack of skill is not among the top causes of startup failure. Execution capabilities are, and most often these are caused by the lack of internal accountability processes and systems. The role of an accelerator is also to help a startup get better at execution. Reporting is an essential part of accountability (not only external—to the accelerator), but also internal (between team members).
  • Therefore, reporting discipline should start during the acceleration/incubation program and should be enforced through the acceleration contract/agreement. Regardless of whether the accelerator has invested cash in the company, reporting should be treated as a main priority in building execution excellence.

“Startups are so focused on the next challenge, reporting metrics falls behind on the priority list.”
— Matthew Forman, Portland State Business Accelerator

  • Accountability should be first understood, then enforced. Reporting is a form of reflection/focus that is essential in building a healthy, functional company. Lack of reflection, focus or prioritization does not only cause potential issues between startup and accelerator/investors but also within the founding or extended team. This symptom is often correlated with a lack of accountability within the team.

4 Essential Metrics for eCommerce Startups

We’ve discussed previously about marketplaces and how dynamic and fast-growing they are. We looked at how the type of businesses that fall into that category have evolved from platforms for online shopping (eBay) to go-to places for other commodities such as accommodation (Airbnb) or workforce (Upwork). Now, we are taking a step back and looking at eCommerce startups and what metrics to track to see how well they are performing and how viable they are as businesses.

While the giants of the business world (Amazon, Walmart, Alibaba) are dominating the space, there is still room for a lot of growth when looking at the fact that 1.8 billion people have made purchases online in 2018—a number that is expected to grow to 2.14 billion in 2021. One way upcoming startups have found to enter the e-commerce sphere is to focus on niche markets and address to a very specific type of need. One proof is that in the retail section the ones that experienced highest-growth rate are companies like Thinx, Figs and Brooklinen.

Everything involving e-commerce happens at a faster pace so tracking data is a must. There are a lot of metrics to take into account for a proper evaluation (e.g. growth rate tells you all you need to know at the surface), but here are some specific metrics to look at when dealing with eCommerce startups.

Conversion Rate

One of the main things that is top-of-mind in eCommerce is getting the visitors through the funnel and executing conversion points. The main focus is the final purchase, however, newsletter signup, add to cart or simply downloading more information are also relevant points that allow future retargeting and conversion. These conversion rates are simply calculated using the formula below or straight out of the analytics tools (starting with Google Analytics and continuing with any other tool you use)

Conversion Rate = Total number of users performing an activity (e.g. sales) / Total number of visitors

Knowing how many of the people that end up on the website actually become customers is crucial for obvious reasons: survival ones. But other than that, it gives you good insights on how well the platform is designed to attract, keep and convert visitors. The fast-consumption pace of the world today means that most people won’t spend too much time on something unless they really need it. Which is why each shopping experience should be constructed as an intuitive, easy to follow and de-cluttered process.

While many focus on the end conversion rate (purchase) tracking the entire funnel correctly and optimizing the conversion rates of each step is key to increasing sales.

© Statista

Benchmarking this rate is slightly difficult as it needs to take into account a lot of factors such as product type, product cost, location, and traffic source. A startup selling high-end jewelry will experience different conversion rates than one that sells books. However, if you would put a number on it, a normal conversion rate is somewhere between 1-3%.

Funnel Abandonment

This metric is very common for e-commerce companies to track. It represents the percentage of people that started the process but called it quits at the very last minute, before making any purchases.

Funnel Abandonment Rate = 1 – (Number of Orders Placed / Number of Shopping Carts Created) x 100

The main insight that can be drawn from measuring this is how intuitive the checkout process is. Setting an objective of decreasing this rate impacts the revenue stream so any sort of product improvement, website upgrade or marketing campaign thought out with this objective in mind can help the company grow.

However, if a startup is experiencing a high rate it doesn’t necessarily mean it is underperforming. The global average rates for cart abandoning range from 65 to 75%. Online shopping is chaotic and sometimes based on impulses so oftentimes this metric has nothing to do with the company’s performance.

© Statista

Most successful companies focus their energy on re-engaging these lost customers. Looking at the rates at which they manage to re-convert some of these leads gives a better look of the startups well-built process and its strategy of growth. A high re-engaging rate shows a healthy startup with a website built with customer experience in mind.

Customer Retention Rates

Trust in the online sphere is essential and the most successful companies are the ones that manage to convert customers into repeat or regular ones. To calculate this you need to look at a period of time (monthly, quarterly or yearly) and use the following formula:

Customer Retention Rate = ((CE – CN) / CS) x 100

Where:
CE = Number of customers at the end of the period
CN = Number of new customers acquired during the period
CS = Number of customers at the start of the period

Having this rate on the plus side of the scale is important because of two reasons:

  • It shows that the startup is already building up a community of fans by having repeat customers (which also indicates how trustworthy and valuable the brand is)
  • It reduces the costs of acquiring customers. Acquiring a new customer is somewhere between 5 to 25 times more expensive than retaining one, and an increase of 5% in the rate increases profits from 25% to 95%, according to a research done by Frederick Reichheld of Bain & Company (the inventor of net promoter score).

Retaining customers also has to do with the type of products the platform is selling. The timeframe in which this rate is calculated should be in sync with the frequency of need that a person might have for the product.

Average Order Value

The average order value (AOV) is the metric that tracks the value of each purchase made by one customer within a timeframe. This is calculated by using the following formula:

Average Order Value = Total Revenue / Total Number of Orders Placed

Measuring AOV and combining this with the repetition rate (how many purchases does a customer make over his lifetime) gives a better grasp on what the lifetime value of a customer is and how much revenue is forecasted to come in.

A startup with an increased AOV for repeating clients will naturally perform well as there are little to no extra costs involved in generating these purchases. The customer acquisition cost for one customer that spends more on the platform is the same and if they spend more on the platform the growth rate increases. In 2018, the benchmarks of global AOV depending on traffic source (social, email, direct and search) range from $73.83 to $107.37 (US dollars).

© Statista

Final Thoughts

E-commerce businesses are very dynamic and competition is fierce. Growth is something all investors are looking for but as the benchmarks show, some percentages that would be a reason for concern for other businesses, in e-commerce, they are the status quo. We strongly believe that data beats gut feeling and e-commerce startups need to track a lot of data. Conversion rate, Funnel abandonment, Customer retention rates and Average order value are just a few of the metrics you need to keep an eye on. Revenue, Customer Acquisition, Customer Lifetime Value also play a huge role in a proper evaluation.

 

We’ve only scratched the surface. You can go more in-depth with this article:

ON customer lifetime value in ecommerce by Hacking Analytics dives deeper into how to calculate and forecast the LTV.


Focus May Increase Efficiency, But Doesn't Guarantee Better Deals

This is part two from a series of insights drawn from 50 in-depth interviews taken over the past two years and 126 responses to a survey we sent out recently. To better understand our process and the methodology behind these findings, make sure to read Disciplined Accelerator: Introduction.

Findings

  • Today, there is an abundance of options for startups. This makes the competition fierce, so accelerators have to find ways to appeal to top startups. Specialization is the most common strategy to tackle deal flow quantity and quality.
  • Focusing vertically (on an industry), horizontally (on one or more disciplines, such as AI, blockchain, FinTech, etc.), or both is a strategic option aiming to improve the efficiency of the accelerator’s programs. Of the accelerators we’ve interviewed, 61% have a focus, 48% having a focus on one or more industries (at least).
  • 87% of accelerators with a horizontal/vertical focus reported difficulties in getting enough applications. The narrower the focus, the fewer the applications. On the other hand, the quality of the applicants is much less of an issue.

Since we focus on specifically mediatech content tech startups the deal flow is very fragmented and it's hard to come by good leads by standard deal flow tools and methods.
— Sten Saluveer, Storytek Accelerator

  • Expanding or narrowing focus geographically helps balance the vertical/horizontal focus shortcomings. Roughly ⅓ of our respondents focus locally, another ⅓ focus regionally (across countries/states) and the rest ⅓ try to appeal to a global audience.

Thoughts

  • It’s an assumption we will check further, but despite focus being an obvious strategic option for improving the deal flow, we believe that it has an inconsistent influence on deal flow. Focusing decreases the quantity of applications (already an issue) but increases the quality of startups (mostly because of better marketing positioning).
  • Choose your focus based on your strategic assets: corporate partnerships, mentor and expert networks, other strong relationships, access to consumers or corporate clients, the availability of talent. Again, ask yourself what you ask your founders: what is our unfair advantage (something that cannot be copied or replicated) and is key to our success?
  • Expanding across borders or even globally is a way to increase the number of applicants, but unless you have access to strong international networks (customers and partners), you won’t be able to further support your startups to reach their potential. So it might be more useful to adopt a few good cockroaches, rather than a delusive unicorn.
  • Focus won’t improve your top of the funnel (on the contrary) but it will improve the outcome of your accelerator programs.

Deal Flow Is a Major Challenge for 2/3 of Accelerators

This is part one from a series of insights drawn from 50 in-depth interviews taken over the past two years and 126 responses to a survey we sent out recently. To better understand our process and the methodology behind these findings, make sure to read Disciplined Accelerator: Introduction.

Findings

  • 2 out of 3 accelerators we’ve talked to have challenges with their deal flow.
  • 59% of all accelerators get low-quality applications. 31% don’t get enough applications. 26% of all accelerators get both insufficient and low-quality applications.
  • Reasons for these challenges are lack of awareness and reputation (especially for new accelerators), competition (with other accelerators, investors, grants or various startup programs) and unbalanced offering (cash vs. equity).
  • Accelerators offering $100,000 or more in funding have fewer deal flow challenges. On the other hand, the ones offering less funding have quality issues (startups don’t perceive the mentoring and support as bringing enough value to justify the amount of equity).
  • Marketing budgets are too limited to allow being effective on all fronts (awareness, trust, lead generation, qualified staff).
  • Applications coming in as a result of marketing campaigns are of much lower quality than the ones coming in from mentor/partner recommendations.

    Over 70% of our deals come from introductions from our mentors or overall network, not by marketing efforts.
    — Les Schmidt, BRIIA

Thoughts

  • Ongoing scouting: Getting better applicants starts long before promoting your new program. The advice you give to your startups to GOOB (get out of the building) applies to you too. Conferences, meetups and other events are a good place to connect to good startups. Be proactive about it and set metrics for your team. The good old days when startups applications flooded every accelerator program are gone. Competition is fierce for top startups. Even though you’re part of those lucky 33% accelerators without deal flow problems, scouting can only increase the quality of your deals and the size of your network.
  • Build a stronger network: Many accelerators don’t have the YC luxury of getting more applications than you can handle. In many situations (one example is Thailand’s ecosystem, driven by corporate accelerators), the number of applicants is often too small to get a decent quality across your cohort. Therefore, recruiting through referrals and recommendations is a much better source for quality, vetted deals.

    Going to events not only for networking but to give back is important. All startup communities are local, so you have to give back to the community—this is why, for us, 80% of the deals came through recommendations.
    — Cosmin Ochișor, former Hub:raum Krakow WARP, now partner at Gapminder.

  • Involve your network in the deal flow: Mentors are some of the best deal sources. Involving them in generating deal flow (beyond sending an email begging for them to share your marketing page) and in judging/vetting will bring a lot more value in the process—often much higher than what your small team can handle.
  • Go beyond Google forms and emails: Use a CRM to handle the deal flow. Of course, we would recommend Metabeta, our portfolio & deal flow suite, but Hubspot, F6S, and Gust are also good alternatives to generic forms. They allow you to involve external judges and have all the information available in one place for your team.

Disciplined Accelerators: Introduction

Our experience tells us that the things that make an accelerator are not as intuitive as they seem. Copying models that work in one place (such as YC or Techstars) and expecting them to work in a different place (with differences in capital availability, know-how, and culture) is a failing strategy. The ones that survive change their strategy (reorganizing as funds or different types of organizations). So we set out to look into what makes an accelerator successful.

We also wanted to understand things beyond the accelerators we’ve worked with. Experience is useful but it leads to biases and a limited vision. While our goal is to build better tools for accelerators and investors, we are confident that you’ll find at least one insight or approach in this series that will nudge you to change your strategy or approach. This change can lead to only a handful of startups becoming more efficient or successful—and that means “making the world a better place” for their customers too. This may not mean much for one accelerator, but the power of compounding can create a great deal of impact if more of you find this useful.

That being said, we have to tell you this is not a proper market research study (but, hey, it’s free). The conclusions and insights were definitely influenced by our past experiences and our view of the field. Any proper research expert can easily poke holes in our methodology and make this report look worse than Swiss cheese.

We sent out this survey to over 500 accelerators and got 126 detailed replies. We also interviewed in-depth over 50 accelerators over the past two years. Here are some details:

  • 38% of the respondents are based in North America, 32% in Europe, 17% in Oceania, 6% in Latin America, 5% in Asia and 2% are Global.
  • 45% of the accelerators are Private Programs (fund-backed), 12% are University Programs, 10% NGO Programs, 7% Corporate Accelerators, 5% Governmental Programs and 21% are other types of programs (not for profit programs and hybrids between private, governmental & co)
  • 85% of the respondents have Executive positions in the company, the rest of 15% are in different positions (Communication specialists, Marketing people, Business Analysts, Mentors & Advisors)

While the sample we used to draw the conclusions is not particularly impressive in terms of quantity, keep in mind that there are only around 10,000 Accelerators worldwide, to begin with.

It was a lot of work on our side (if we had done this only to sell our products and services, believe me, that buying an email list, spamming everyone on it, then paying the GDPR fines would have been more efficient). In the end, we found out quite a few things we did not know, so we thought it’s worth putting it out.

If you find it useful, share it further. If not, tell us how we can make it better next time!

Report contents

  • Introduction and Methodology
    Introducing a series of articles detailing the findings and insights from a research study carried on more than 170 accelerators.
  • Part 1: Deal flow is a major challenge for 2/3 of accelerators
    59% of all accelerators get low-quality applications. 31% don’t get enough applications. 26% of all accelerators get both insufficient and low-quality applications. Lack of awareness and reputation, competition, and an unbalanced offering are the top deal flow challenges.
  • Part 2: Focus may increase efficiency, but doesn’t guarantee better deals
    Today, there is an abundance of options for startups. This makes the competition fierce, so accelerators have to find ways to appeal to top startups. Specialization is the most common strategy to tackle deal flow quantity and quality.
  • Part 3: Lack of reporting discipline is most often the accelerator’s fault
    Getting startups to report during and after the program is a challenge for most accelerators, but the discipline of reporting should be enforced and grown within the programs.
  • Part 4: Education is essential for incubation but disruptive for acceleration
    Acceleration should not be an educational program ending with a Demo Day, but a process aimed at helping build successful business by offering the right support. Build your acceleration process to help you reach your end goals, considering the available resources.
  • Part 5: Mentoring beyond bragging rights and looking good
    Matching mentors with startups is a tedious process for various reasons. Many startups chase famous/known mentors, who have less availability, while disregarding less popular mentors who might be more willing to give time and help. Matching mentors with startups in the beginning is not a guarantee of effective mentoring throughout the program.
  • Part 6: Corporate vs Private vs University vs Government accelerators
    Coming soon
  • Part 7: Business models and metrics of accelerators
    Coming soon
  • Part 8: The power of alumni communities
    Coming soon


4 Essential Metrics for SaaS Startups

SaaS, short for Software as a Service, is a software delivery method in which the products are accessed through online subscriptions and the software is hosted by third-party providers, usually in the cloud. For the end user, this means having access to tools on a pay-as-you-go system, without the hassle of any hardware or the pain of paying for a license upfront.

For SaaS companies, this is not only a good sales approach but a more predictable long-term cash inflow through these subscriptions (monthly or yearly). Hootsuite, Salesforce, Adobe are just a few of the most successful SaaS companies, out of a very long list that has grown immensely in the past years (Adobe has even shifted from their one-time license approach to a subscription business model by packaging its products in the Creative Cloud platform).

Today, as more and more companies are integrating SaaS tools to help with their processes, the forecast for annual revenue growth over the next five years is over 21%. Growth is key for any SaaS startup, but there are more important key metrics when evaluating such a company:

Monthly Recurring Revenue (MRR)

The SaaS subscription model highly relies on small increments of money coming in. MRR is calculated by simply adding the subscription (recurring) revenue from each customer—or by multiplying the total number of customers by the average revenue per user (ARPU):

MRR = Number of customers × Average Revenue per User

For example, if you have 4 customers, two that paid $100, one $50 and one that paid $1,020 for a yearly subscription, you have an MRR of (2x$100) + $50 + ($1,020/12) = $335 and an ARPU of $84.

MRR is very important because it allows you to predict future cash inflows (unless you have a high churn rate—which we’ll discuss next). A stable growth in MRR also allows you to evaluate the health of the company, which can be misleading if there are some yearly, higher-volume subscriptions, which have a high risk of not being renewed.

This seems fairly simple but for more complex businesses there are a couple of things to factor in for a better understanding of the revenue stream:

  • New MRR — the total amount of revenue from new subscriptions added each month
  • Expansion MRR — the total revenue made through upgrades and upsells from existing customers
  • Lost MRR — the revenue lost through cancellations and downgrades

Net New MRR = New MRR + Expansion MRR - Lost MRR

Net New MRR is one of the most important ones for evaluating SaaS startups because by monitoring it you can see what type of growth the company is registering. That, in turn, tells you that the product that they are selling has a market and can become profitable or if it’s not growing as rapidly as intended, that the product needs adjustments to appeal to customers' needs. If the Lost MRR is higher than the New MRR, the company is losing more than it gains.

How much MRR growth should a SaaS startup register? Paul Graham reported that at Y Combinator he looks for a 5 to 7% growth on a weekly basis for starting companies from seed to series A.

Nathan Latka, one of the go-to guys for Saas advice, offers each year a lot of examples on his website. Taken from the benchmarks released in October of 2018, these are the startups that registered the highest growth in revenue: Ripple Recruiting (1122%), MarketMuse (900%), HYPR Brands (823%), Tagove (580%) and IdealSpot (570%).

Taken from Nathan Latka's Benchmark Spreadsheet released in October 2018.

Churn Rate

Churn rate is the percentage of customers or revenue lost over a period of time (monthly or annually) through canceled subscriptions and downgrades. Knowing this metric at all times is crucial for SaaS startups. It gives a good insight of the quality of the product itself—if the churn rate is low that means the business will succeed; if it’s high it tells you that it’s a red flag and that some pivoting on product features or strategy is required. The two types of churn, customer, and revenue tell a different story and should be calculated separately, especially if the SaaS startup has pricing tiers that include customized plans for enterprises or corporations.

Customer Churn Rate

Customer Churn Rate is the number of customers the company has lost within a specific timeframe. For SaaS startups, it’s better to measure this metric monthly rather than annually.

Customer Churn Rate = Lost Customers / Total Customers

Let’s say that you have 100 customers in the beginning of January and 5 of them cancel their subscription by the end of the month. The churn rate is calculated like this: 5/100=0.05, which is a 5% churn rate. On a monthly basis that is a high churn, which is a bad sign, but for early-stage companies, it is still fixable as they are just starting to shape their product and adjust based on feedback.
Customer Churn Rate is also important when it comes to calculating the Lifetime Value of a customer, which we will explore later on.

Tom Tungusz from Redpoint Ventures makes the observation that lower-value customers churn at higher rates:

Revenue Churn Rate

Revenue Churn Rate is the percentage of monthly recurring revenue the company is losing. This is more important to look at when the startup is more mature and has complex pricing tiers and different types of features and offerings.

Revenue Churn Rate = Lost MRR / Total MRR

If we take the same 5% churn rate from before, but the 5 customers that you lost are higher-paying customers, either on an Enterprise or Corporate plan, which account for $5.000 out of a $10.000 MRR, the revenue churn rate is: 5.000/10.000= 0.5, which is a 50% revenue churn rate. That high of a rate is cause for concern.

Having some churn rate is normal, though. There are people that change profession, or companies that go out of business. In these cases, your product or strategy has nothing to do with why they stopped using it and there is no reason to panic.

Something very important to remember is that churn rate as a metric is merely a starting point in your analysis. By looking at it you can conclude first and foremost if the product is good. All the sales and marketing efforts that follow are meaningless if the product is losing more customers than gaining and isn’t able to retain them for a longer period of time. Especially in a winner take all type of market, where SaaS products are usually integrated with other tools and people/companies find it hard to switch from one product to another.

On average, the benchmarks for a healthy revenue churn rate is between 5 to 7% annually, which means less than 1% monthly churn rate.

Going back to Latka’s spreadsheet, the same companies that experienced the biggest growth in revenue, are not exactly models to follow in terms of churn rate. Ripple Recruiting and MarketMuse have a 0% and 1% churn rate, while Tagove and Ideal Spot show a 15% and 20% churn.

Here are a couple of other companies, segmented by the type of industry their product is in:

Customer Lifetime Value (LTV)

The customer lifetime value is an estimate of the revenue a customer will bring in before they churn. It’s a useful metric when assessing the financial value of a customer, but it is based on predictive analysis of future actions, therefore its accuracy isn’t always on point. The complexity of properly calculating this particular metric deserves a separate article (something to tackle in the future, perhaps). For now, we are just going to go through the basics of it.

The customer lifetime value is equal to the average revenue per user (or account) multiplied by gross margin and the customer lifetime.

LTV = Present value of (Customer Lifetime × ARPU × Gross Margin)

Customer lifetime is the total amount of time that a customer will be using your product/service, and is calculated as 1 / Customer Churn Rate.

ARPU is the monthly average revenue (sales) per user (or per account, in the case when the customer is an enterprise).

Gross margin is the percentage of own revenue (after subtracting from revenue the external costs, such as credit card processing fees, hosting or other costs related to the delivery of the software to the customer).

Money has a different value if you have it now versus if you have it over—for example—60 months (5 years). So you need to use the Present Value formula to calculate today’s value of the money you will get from your customer each month for the next five years.
For early-stage startups, this customer lifetime value is harder to track since there aren’t that many customers and out of the few that exist most haven’t gone through the lifespan of the product to be able to conclude with better accuracy what the value is.

Customer Acquisition Cost (CAC)

The customer acquisition cost is the total value of marketing and sales costs necessary to acquire one customer.

CAC = Total Marketing & Sales Expenses / Number of New Customers

This looks simple enough but to have a correct assessment of the CAC there are a few things that shouldn’t be overlooked.
First of all, the cost of sales and marketing isn’t equal only to the salaries of your team from these fields, and the cost of marketing ads, or trade shows, but also the myriad of tools used by the company since automation of all these processes is top of mind nowadays. Also, the costs of partnerships that bring in new customers.

Secondly, the formula should take into account the average time of conversion, since it’s not standard all the time. Each SaaS business has a different type of pricing model, and the time it takes for them to actually convert a customer varies. With freemium models and free trials, it can take up to 60 days for one of your sales and marketing tactics to actually see some fruition.

Ratio between LTV:CAC

Note that looking at one metric independently doesn’t point to how viable the business model of the SaaS startup is. Metrics like LTV and CAC should be evaluated in rapport to each other. As a general rule of thumb, the ratio between LTV:CAC should be higher than 3:1. Also, in the beginning, it’s typical for a startup to have a very high CAC, but the time it takes for it to recover (known as CAC Payback) should be less than 12 months.

Final thoughts

This market is a very competitive one and it is surrounded by uncertainty. In order for a SaaS startup to stay ahead of the crowd, it needs to put in a constant effort. And the metrics need to be evaluated at a more granular level, monthly or even weekly, depending on the stage of the startup. Looking at the current MRR, Churn Rate and Ratio between LTV and CAC of the SaaS will give you insight into the health or potential of the company.

We’ve just scratched the surface with this. Smarter people than us have more insights into the SaaS world, so if you want to go more in-depth and upgrade your knowledge on this topic we recommend you to read more from and follow these guys:

  1. Tomas Tungusz — Benchmarking Exceptional Series A SaaS Companies
  2. Christopher Jansz — The SaaS Funding Napkin 2018
  3. Andrew Chen — The red flags and magic numbers that investors look for in your startup’s metrics

3 Essential Metrics for Marketplace Startups

Some of the biggest players in the game, the unicorns that made it on every startups’ “when I grow up” list, are companies that have achieved success by creating platforms which ease transactions between two different sides. Amazon, Airbnb, eBay, Craigslist and Uber are a few examples of marketplaces that became giants in the industry. In Asia, marketplaces are some of the fastest-growing startups.

Typically, marketplaces can be very powerful in terms of growth. But tracking them and measuring their success isn’t always simple. Marketplaces need to address both the supply and the demand side of a business—two types of customers that need different kinds of hooks. Which is double the trouble.

The spectrum of markets in which these types of businesses activate is wide, which is why each calculation should be tailored to the specifics of their market focus, whether it’s horizontal or vertical, B2B or B2C, global or local and so on. But how do you know if a marketplace startup is on its path to becoming huge?

Here is a rundown of the key metrics that any accelerator or investor should look for when dealing with marketplace startups:

Gross Merchandise Value (GMV)

The GMV shows the total of the goods and services transacted within the business. You can calculate it multiplying the number of transactions with the average order value over an extended period of time (usually done yearly).

GMV = Number of transactions × Average Order Value (AOV)

Some consider this metric to be a vanity metric. And the reasons are twofold:

  • discounts, cash-backs, returns, and cancellation are not included in the equation.
  • GMV is an indicator of the volume of money transacted within the platform, but not how much money it actually makes (i.e. revenue).

For example, eBay’s GMV amounted to $95 billion in 2018. That looks impressive. But when you look at its net revenue, the company made only $8 billion through its marketplace transactions. While still a lot of money, the difference is sizeable.

Another example would be Etsy, which reported in 2018 Q3 a GMV of $923 million and its revenue of $111 million.

Achieving a high GMV means either:

  • having a high number of transactions but with low AOV,
  • or a low number of transactions but with very high AOV.

Experts don't agree on which of the two is the better one in terms of strategy. It takes looking at other metrics, such as the customer acquisition cost (CAC) to be able to assess the real monetary value of the platform. But ultimately, a growing trend line in the GMV value shows how popular that marketplace is becoming, how well it is performing, and if it is worth investing in it. In a seed to Series A type of startup, the growth seen should be 100% annually.

If the startup is at its early-stage it will not have a lot of GMV growth to measure. In that case, it is helpful to look at companies with similar business models and pricing strategies to see when their growth spur occurred. Understanding more about what others have done in the past, and at which point in their business life the boom happened, will make it easier to conclude if the startup is heading in the same direction.

Rake (Take Rate)

The revenue of a marketplace company is the total amount of commissions and fees applied to the transactions within the platform. You've probably heard it mentioned as the “take rate”.

Rake = (Commission + fees) / Sales

Much like regular pricing models, these rates come in various shapes and sizes. Founders can choose to apply this rate either to the demand or the supply side (sometimes both), it can come as a fixed or flexible commission, a flat fee or a percentage, it can even be subscription-based. The value of this rate varies based on the type of good that is being transacted and the business model of the marketplace. On average, it is somewhere between 5–30%.

Upwork uses a regressive take rate model, charging less when billing more, scaling down from 20% to 5%. They apply this fee only to the freelancer, so it is one-sided.

Airbnb has a double-sided commission. While the percentage for hosts stays put at a 3% fee, the service fee for guests fluctuates around 20%. And as the cost of booking increases, that percentage decreases.

Etsy does not have only one type of fee. They have standard fees that apply to all sellers (which is a 5% take rate on each transaction, or a US$0.02 fixed fee for each item listed), fees that are optional based on extra services they provide (such as a tool for creating personalized websites) or a subscription-based fee.

Each startup has to choose their own rate model based on the specifics of their market. That rate does not have to stay the same, anyone can adjust it as they see fit. Price increases are not pretty but sometimes necessary and if done correctly, the way Etsy did, they come with benefits. After years of growing their user base and gaining their trust, they went from a 3.5% to 5% rate and added their subscription-based plans. That resulted in a 43% revenue increase (comparing 2017 Q3 to 2018 Q3).

Early stage startups can (and should) opt for lower rates, for the sake of cash flow but also to be able to enter the market and compete with the giants. Once they scale and reach exponential growth, marketplaces tend to take up most of the space leaving little room for competition. A good example of a new player that disrupted an industry that seemed untappable is Booking.com. They conquered the European market by providing smaller fees that smaller hotels could afford. That increased their supply, which met the already high demand. And later on, they compensated for the small fee by adding optional promotional features that hotels were willing to pay.

Liquidity

Which leads us to one very important aspect of why choosing the right take rate matters: liquidity. Appealing rake models bring in users which in turn affects the increase of the GMV. And ultimately makes for a steady revenue stream—which is the interconnectedness of things.

Liquidity in a marketplace is the balance between the demand and the supply sides of the business. Having enough buyers and sellers, or a good ratio between them (or items sold/booked) is essential for a marketplace to grow.

Etsy had around 34 million active buyers and around 2 million active sellers, in Q3 2018, which does not seem like a good ratio. Measuring liquidity, in this case, means looking at more than the number of buyers and sellers, so other aspects factor in the equation:

  • number of listed items that each seller has;
  • variety of products;
  • number of purchases;
  • return purchases;
  • geographic distribution (shipping destinations vs website traffic);
  • other things that are particular to the marketplace.

Service-oriented marketplaces vs product oriented ones should have their liquidity measured by different standards, or within different timeframes. A working contract on Upwork could take months before it ends while buying a photo on Shutterstock only takes a second. The same goes for global vs local marketplaces. Deliveroo needs both the buyers and the sellers to be in the same code area to reach liquidity, while Bookdepository ships worldwide and the same rule doesn’t apply to them.

This chicken-and-egg conundrum proves that in a marketplace the number of buyers and sellers is co-dependent, that having one without the other is pointless, and on which of the two a founder should place their primary focus is unknown. With competition being so intense, it’s critical for each marketplace to have liquidity. The business needs to have a strong value proposition and provide a great user experience, in order to gain the trust of both sides. Not having enough (in terms of quantity but also quality and variety) supply is dangerous, as anyone looking for anything can quickly find it elsewhere. It goes without saying that a marketplace without an increasing demand points to a dead end, or that a market-product fit doesn't exist.

Ending thoughts

Marketplaces are growing strong and investing in them is wise. These three key metrics show without a doubt the company’s performance, viability, and growth. There are many other metrics that you should take into account for a full evaluation. But at an overall level, Gross Merchandise Value, Rake and Liquidity are the three musketeers that tell you everything you need to know about the health of the marketplace startup.

 

To go more in-depth, these articles provide a good deal of details and more metrics:

How to measure your success: The key marketplace metrics (Sharetribe) looks further at usage metrics, customer conversion funnels and user satisfaction metrics.

Marketplace Liquidity (TechCrunch) tackles the importance of liquidity in a marketplace at a more granular level.

A Rake too Far: Optimal Platform Pricing Strategy (Above the Crowd) although written a while ago, Bill Gurley's thoughts are still applicable to today's marketplaces.


The Problem Statement Canvas for Startups and Innovation Teams

The number one cause of startup failure is the lack of a real need in the market, according to a recent post-mortem on startups. This reminded me of probably the most important lesson I’ve learned from my mentor and friend Bill Aulet, Managing Director of the Martin Trust Center for MIT Entrepreneurship, a professor at the MIT Sloan School of Management, and author of the Disciplined Entrepreneurship books:

“The single necessary and sufficient condition for a startup to succeed is a paying customer”
—Bill Aulet, MIT

I’ve worked with Bill for the past few years, helping to spread the Disciplined Entrepreneurship approach, also teaching and coaching teams at the MIT Global Entrepreneurship Bootcamp, MIT Enterprise Forum, Singularity University, Future Innovators Summit, and many other acceleration programs around the world. During all these years, I saw a recurring pattern among startup founders, which is their obsession with the solution. They are so driven by their vision of a better technology, that they forget the most important things about startups, which I annoyingly remind to every founder I talk to (including myself):

A startup is a business, not a product.

Most of these founders are passionate engineers, designers or business people who want to build amazing things—apps, platforms, robots and more. They end up sacrificing their job, their lifestyle and sometimes their personal relationships for this passion and their vision. At the same time, this is also one of the main reasons they fail.

The hunt for unicorns driven by Silicon Valley investors requires entrepreneurs to be delusional, considering that there are only 174 unicorns (startups valued at over $1B) in the US. It is a mindset that encourages the ‘can’t-possibly-fail’ startup syndrome, an unfortunate wishful thinking on the part of many brilliant startup founders. Eventually, they build great technology but fail to identify the right problem and end up joining the startup graveyard.

As a startup founder, investor, accelerator manager, or mentor you want to do everything you can to mitigate these failure rates and the one way to achieve that is by obsessively focusing on the problem in the early stages, instead of the technology. The real talent in all entrepreneurship—not only in tech startups—is finding the right problem, not building the right solution. In other words, it is vital to have the skills of Sherlock Holmes, not only those of Doc Brown. Once the problem is correctly identified and understood, building the right solution that will lead to a good business is much easier.

The problem statement canvas

Let me walk you through the process of defining problems using a problem pitched by one of the startups I’ve recently mentored:

“People have a huge problem with traffic in São Paulo. We’re going to build the leading ridesharing app for them.”

It was a good start, but the “problem” with this problem statement is that half of it talks about the solution. I could not really understand who those people were, how huge the problem was, and could not be convinced by yet another “app” solution for a systemic problem. Truly identifying a problem means looking deeper at the symptoms, the customer, the impact, the alternatives, the opportunity, and the relationships between them, while avoiding the “solution bias” (often known as “The problem is that the customer does not use my solution”):

Problem statement canvas for startups and innovation teams | DE Toolbox
The problem cycle

After coaching and mentoring hundreds of startups around the world, learning from some of the best mentors and successful entrepreneurs, I’ve created a simple tool for defining problems in the right way: the Problem Statement Canvas.

While far from being perfect, this way of stating the problem helps everyone better understand the complexity of the problem, completely leaving out the solution. The generic format of the problem statement can be summarized as follows:

When context occurs,
customer type who has characteristic and characteristic,
have problem.
Because of this, they feel emotion, then experience quantifiable impact.
Currently, they use alternative solutions
despite disadvantages.

For those of you who are more visual, the canvas can also be used in a visual format.


Problem statement canvas for startups and innovation teams | DE Toolbox

Download the Problem Statement Canvas here.

Regardless of whether you’re the founder, or you’re working with a startup as an investor or mentor, this is something you want to go over together. Having a common understanding of the problem at each level in the company is critical. Let’s go into each area of the canvas.

Customer type

One of the early stage mistakes is not focusing on the right customer, because of the mirage of keeping multiple opportunities open. “Closing a door on an option is experienced as a loss, and people are willing to pay a price to avoid the emotion of loss,” concluded an experiment ran at MIT by Dan Ariely, a renowned behavioral economist.

You want to focus, and find the 10% of the people for whom the problem is a real pain, not the 90% for whom it’s just a nuisance. Who are they? Where do they live? What is their income? What does their regular day look like? As a founder, you want to be able to walk in their shoes, do their job, live their life, talk to them over breakfast, lunch or dinner, observe them and even ask to shadow them. You want to understand the customer through a demographic and psychographic lens, using at least 2-3 relevant criteria.

To get back to our initial example, instead of:

“People in São Paulo”

we successively refined the customer profile to:

“Young men aged 25–35, with middle-low income, who live in suburban São Paulo and work in a corporate office in the city center.”

Focusing on a single customer segment, which could be your beachhead market, has many benefits:

  • You avoid the Chinese glove market fallacy.
  • You get an in-depth understanding of how the problem affects people’s lives.
  • It’s easier to find those people and discover patterns of behavior, which makes it easier to market the product to them.
  • From a business point of view, it’s better to build the best solution for a specific group of customers, than to build yet another average solution for a larger market.

Remember The Social Network movie? Today, everyone imagines that Facebook achieved total world domination by, well, just thinking like a unicorn. But that’s not true. Facebook started as a network for Harvard students, solving student-specific problems. Then, it scaled to other Ivy League colleges. Afterward, it went to other colleges in the US (remember when you could not get a Facebook account unless you had a .edu email address?). Only later on did it open up to everyone, but this strategy helped them focus on what mattered to their customers. They did not start by taking on MySpace or Friendster.

Context

When does the problem occur? Most of the problems are not permanent, and understanding what triggers them will help you further understand the root cause of the problem. More than this, you will understand what is the window of opportunity—when the problem becomes acute and most painful for the customer, and also when he is also most likely to take action (which in the future could be acquiring your solution).

For our startup, the context then became

“Every workday, in the mornings and evenings, for an average of 2-3 hours per day.”

Root problem

Working with the team, we initially came to this refined problem:

“Are stuck in traffic.”

However, this is not the root problem, but rather a complex of symptoms. Identifying the root cause, not the symptoms, is essential to building the right solution. Identifying the root is often difficult, but fortunately, a technique called root cause analysis will help us get to the real issue.

Focusing on events/consequences that exist and asking “why is this a problem?” several times will help you get to the real root cause that you have to address. For example, you might have a problem: your car does not start. But that’s not really a problem, it’s a symptom. You can usually find the first cause of this problem by asking “Why?” The answer is “The battery is dead.” Many entrepreneurs will stop here, then embark on a journey of building better car batteries.

By applying the process we get different answers:

  • Second why: The alternator is not functioning.
  • Third why: The alternator belt has broken.
  • Fourth why: The alternator belt was well beyond its useful service life and not replaced.
  • Fifth why: The vehicle was not maintained according to the recommended service schedule. (the root cause).

Do you still think that building better car batteries is a viable solution in this case? Or rather coming up with a different solution that solves the servicing schedule?

We applied the above thought process for our team:

  • First why: Because it takes a long time to get to work
  • Second why: Because they are wasting precious time
  • Third why: Because they might use that time to do something more valuable
  • Fourth why: Because they could earn more money in that time

So the final problem could be stated as:

“Could do something more valuable in the time they lose in traffic.”

Emotional impact

It’s not enough to understand the problem as a phenomenon or as an event; you also have to consider its emotional impact, because this helps you walk in your customer shoes and understand their behavior. Each problem causes an emotional response (joy, sadness, anger, fear, trust, distrust, surprise, anticipation) and its magnitude is directly linked to the person’s interest in using your solution. If someone is merely annoyed by something, they are much less likely to try a solution than if they were angry when the problem occurred.

Fully understanding these emotions is essential in identifying windows of opportunity and triggers that will make your customers use your solution. “When customers are in homeostasis their habits are set and you’re not going to move them,” says Bill Aulet in the Disciplined Entrepreneurship Workbook, who has analyzed recent insights from behavioral economics, in order to identify when a startup has a greatly increased chance of influencing customer decisions and to understand what triggers the use (and then the purchase) of a new solution.

In our above case, the emotions are frustration and boredom.

Quantifiable impact

At a certain stage, a startup has to determine its pricing strategy. For this, it needs to quantify its value proposition which is difficult without understanding and quantifying the impact in the current state.

The impact should always be expressed in a currency. These currencies can be more legible (money, goods, time) or less legible (energy, health, relationships). Ideally, you would want to express the impact in a currency that is as legible as possible, because the impact is more visible in loss of cash, goods or time than the loss of relationships or health. This will also help to communicate it more convincingly to the customer.

Problem statement canvas for startups and innovation teams | DE Toolbox

In our case, we identified the impact as being:

“Lose on average 40 hours per month.”

Alternative solutions

For many disciplined founders, the work stops with the previous step. But before jumping to a solution, shouldn’t you look at what your potential customers are doing to treat their pain or some of its symptoms? If what you discovered to be a problem is really a problem, your customers are likely to be using different tools and actions, or combinations of them, to ease or manage the pain.

Sometimes they might be improvising ingenious things to fulfill their needs, something that MIT professor Eric von Hippel describes in his Free Innovation book. Looking at these alternative solutions and breaking down each of them into pros and cons, will be a great help in identifying opportunities for a painkiller solution.

Flipboard, for example, looked at the success of read-it-later tools like Instapaper or Pocket which allowed users to read interesting articles without the clutter of their web pages. They took the time to understand how users were reading traditional paper-printed magazines, before creating a great reading experience with their iPad apps. Eight years later, it’s still one of the top News apps in both App Store and Google Play.

Slack did not reinvent the wheel, they just looked at what people were already doing by using email and group messaging tools like ICQ or IRC chats to improve their productivity, and made a rather simple tool that better enabled those behaviors in a work context.

Our São Paulo startup identified a few behaviors of which one later became a critical element of formulating their solution:

“They sign up for Uber but only accept rides when they go to work or come back.”

Alternative solution disadvantages

Competition is good, it proves the problem is real. But what if you can’t beat the competition (which is the case in many mature markets)? That’s the reason why finding the disadvantages or shortcomings of alternative solutions will help you understand where the core of your solution (your unfair advantage) resides.

For our team it was easy:

“Driving for Uber requires you to spend more time waiting for a ride in the area, as the origin and destination of the trip might not coincide with your home-work itinerary.”

Taking a step back

At this stage, we can look at the initial statement, which rather sees the systemic size of a problem (very hard to solve):

“People have a huge problem with traffic in São Paulo. We’re going to build the leading ridesharing app for them.”

Then compare it with the one we came up with after going through this process:

Every workday, in the mornings and evenings (for an average of 2-3 hours per day),
young men aged 25–35, with middle-low income, who live in suburban São Paulo and work in a corporate office in the city center
lose time in traffic instead of doing something more valuable with it.
This makes them feel frustrated or bored,
as they lose on average 40 hours per month.

Currently, they might sign up for Uber and accept rides when they go to work or come back.
However, driving for Uber requires them to spend more time waiting for a ride in the area, as the origin and destination of the trip might not coincide with their home-work itinerary.

Or in the visual problem statement canvas:

Problem statement canvas for startups and innovation teams | DE Toolbox

What’s even more interesting is that at the intersection of the above areas we will discover some key elements for turning the problem into a viable solution and business, as you can see in the canvas below:

Problem statement canvas for startups and innovation teams | DE Toolbox

This process led the São Paulo team to come up with a rather different solution than the initial one they imagined, one which would have been hard to identify without looking at all the above. The solution was a ride-sharing platform that allowed their customers to generate revenue while driving other people in their neighborhood to work. Unlike Uber, their solution was subscription-based and a very ingenious way of generating not only revenue but also quick growth.

Maybe, in a few years, this will even solve the systemic traffic problem in São Paulo. But until then, their startup has the change of becoming a profitable business that generates true value for their customer.