Ask any successful startup founder to narrate a story of their journey to success, and you are most likely to hear about the decision to pivot at a particular point. Tales about startup success are incomplete without reference to the founders undergoing a pivot one time or another. From Honda to Twitter, every successful startup had to pivot or implement multiple pivots to be where they are now.

Interestingly enough, this realization about the ubiquitous nature of pivots in the life of a startup does not deter notions about them being considered last-ditch options employed to transform a struggling startup. Pivots are synonymous with startups and happen all the time. All startup founders are aware that they will have to pivot at some point; however, they are unsure when and how to do so.

What is a Pivot and why is it necessary?

According to Eric Ries, a pivot is ‘a structured course correction designed to test a new fundamental hypothesis about a product, strategy or engine of growth’. From this, we can deduce that it is an activity steeped in experimentation and learning. It is triggered when founders recognize from experimentation feedback that their findings differ from the earlier assumptions that they created at the beginning of the startup process.

All startups must expect to pivot more than once before finally achieving success. For most, pivoting will occur at every stage as the founders realize that their assumptions about customer segment, problem, solution, channels, or technology are not valid.

Startups that cannot bring themselves to pivot to a new direction based on feedback from the marketplace can get stuck, neither growing enough nor dying. If left unchecked, such startups end up failing.

If Pivots are so important, why don’t more startups implement them?

Despite widespread knowledge of its importance to ensuring success in startups, pivoting is still not a common occurrence for many startups.

This is because recognizing that there is a need to course correct for most founders who are emotionally attached to their product is a challenging undertaking. Such recognition goes against the typical human behaviour to admit that the initial course of action was wrong. Doing this takes putting egos and convictions aside to accept that a certain action plan was incorrect.

Other reasons why pivots are not implemented by founders include:

• The use of vanity metrics by startups can allow founders to reach false conclusions about their performance.

This is most common during the product-market fit stage when founders rely on metrics that do not provide a critical reflection of their performance, and as such, do not see the need for course correction.

• Arrogance on the part of the founders.

Most founders tend to have an absolute belief in the viability of their ideas that they become very resistant and hesitant about the need to change their business model. This commonly leads to a situation where products/solutions are created for problems that prospective customers have not validated yet.

• A refusal to approach the startup process as a learning activity.

While there are examples of startups that have been successfully founded with little input from anyone else apart from the founders, most founders tend to approach the startup process and create a product based on their ideas and conjectures.

Thus, there is very little room for them to learn anything as they do not believe the customers know what they want, and it is their job to tell the customer what they want. They see no need to test assumptions about customers, problems, solutions, etc.

When do startups decide that it is time to Pivot?

Executing a pivot is a strenuous activity. It is difficult for founders to recognize their need to implement a course correction and even more challenging to achieve one when they have decided to go for it. There is also no guarantee that the course correction to be taken will be successful or change the direction of the startup.

This notwithstanding, founders must understand that implementing a pivot/multiple pivots is inevitable and must be prepared to do so if the need arises. However, to do this successfully, founders must know when it is the right time to pivot.

The decision to pivot represents a combination of both art and science. Often, most startup founders decide to pivot on the back of a gut feeling or intuition they have that their current course is no longer the right one. This gut feeling can come from prior experience gained from running an earlier startup or from feedback gotten from other stakeholders (e.g., partners, advisors, customers).

In addition to this, founders may also decide to pivot on the back of the metrics/numbers generated from testing their ideas, problems, and solutions with their customers. Key questions to ask when considering this include:

• Are the numbers (e.g., acquisition rate, activation rate, retention, and revenue rates) coming from customers’ interaction with the solution, thus validating the original hypothesis?
• Are the experiments being run (e.g., tuning product features, interviews with customers) yielding outcomes that increasingly deviate from the initial expectation?

If the answer to any of these questions is YES, it is time to pivot!!

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How do you successfully execute a Pivot?

As previously argued, executing a pivot is an arduous activity. A key reason for this difficulty is the indecisiveness or refusal by the founders to accept the need to implement one. Thus, to successfully execute a pivot, the first thing required from the founders is decisiveness.

Startup founders must be aware, recognize and accept the need for a correction in their current course. One recommended approach is for startups to schedule periodic pivot meetings. During these meetings, the startup team reviews the numbers, discusses their perceptions about performance and their current direction, identifies the need to pivot, and obtains all stakeholders’ buy-in regarding the need to pivot.

Once you’ve achieved this and founders have accepted the need to execute a pivot, they must begin experimenting. Since pivots can occur at different stages in the life of a startup, running experiments can help founders identify where the issues exist and how to correct them. A framework based around the principles of experimentation, which will guide the pivot activity, such as the Pivot Pyramid, can be of great use here.

The pivot pyramid is a visual guideline to help founders make changes and run experiments in different business areas to drive growth. The pyramid looks at all the elements of a startup business model (customers, problem, solution, technology, engine of growth, channel, revenue, unique value proposition). It then tests assumptions that founders have made about a particular element with data from either interviews or running usability tests.

By running such experiments, founders can quickly realize whether the problems they have identified are a must-have for their targeted customer segments and, if not the case, recognize the need to adjust it. They can also determine whether the solution they have designed addresses the customers’ problems and, if not so, recognize the need to adjust it or redesign a new solution.

Types of Pivots

When most founders hear about pivots, the first thing that comes to their minds is fundamentally changing the solution/product they are creating. This is, however, not always the case. While a good number of product pivots exist (e.g., Airbnb, Starbucks, Nintendo), there are other types of pivots that can lead to success. These include the following:

1. Zoom-in Pivot: a zoom-in pivot is a type of product pivot that takes a single feature in an earlier iteration of a product and makes it the centerpiece of the new product.

This pivot typically happens when early adopters use a product because of a particular feature rather than the whole set of features accompanying the product. An excellent example of this type of pivot is the photo-sharing startup Flickr.

Flickr started as a massively multiplayer online role-playing game called ‘Neverending’. Back in the days of ‘Neverending’, there was a feature in the game that allowed users to share photos and save them on a web page. This feature turned out to be the most fun part of the entire game’s experience and later became the company’s centerpiece.

2. Zoom-out Pivot: In a zoom-out pivot, the startup realizes that a single feature is insufficient to support a complete product and decides to make the feature part of a larger product or ecosystem.

This typically occurs when the earlier development is not gaining enough traction and customers have requested additional features that enable them to use the product more.

3. Customer segment Pivot: Under this type of pivot, a startup realizes that its product addresses a must-have problem for a specific group of customers (its early adopters) but may not be a must-have problem for its originally-intended or mainstream customers.

This type of pivot is typically associated with startups trying to scale their activities into their proposed mainstream market.

4. Customer need Pivot: This type of pivot occurs when founders realize from their interactions with customers that the problem earlier identified is not crucial to its customers.

However, from its interaction, the startup can identify issues that are actually relevant.

5. Engine of Growth Pivot: In an engine of growth pivot, a startup realizes that its assumed growth engine (viral, paid, or sticky) may not allow it to achieve rapid growth and decides to change this for a new strategy to seek faster or more profitable growth.

6. Channel Pivot: In a channel pivot, a platform realizes that its earlier assumed path to reaching customers may not be the most effective and decides to change this to a different channel with greater effectiveness.

Other types of pivots include the Business Architecture Pivot, Technology Pivot, Platform Pivot, and Value Capture Pivot.

Final thoughts

Pivots are a permanent facet of any startup. It is the rule, not the exception. As such, all startup founders must expect to pivot multiple times throughout their startup process.

For startups to become successful, founders must be willing to learn and experiment. They must go into the startup exercise with humility and the knowledge that their initial assumptions will most certainly change.

They must be decisive in their attempt to execute such change and try to separate themselves emotionally from their startups. Only when they achieve these things will they have a good chance for success.

In the previous episode, “Going From Good To Great – Ideas That Your Investors Will Love“, we’ve talked about the risk of focusing on the wrong features after the prototype is successfully tested. It is now time to learn to get the right features right early on.

One of the most instructive examples of how easy it is to get them wrong and be blinded by the initial success is the story of how MySpace lost to Facebook. What’s scary is MySpace lost almost “overnight”, despite being the dominant social network for four years in a row before that.

A bit of history helps seeing how things unfolded:

• MySpace had been launched in August 2003 and Facebook 6 months later, in February 2004;
• In October 2007, Facebook was still behind by a large margin, with 20 million accounts, 27.9 million unique visitors, and 14.8 billion page views, vs. My Space’s 200 million accounts, 71.9 million unique visitors, and 46.4 billion page views;
• In May 2008, Facebook overtook MySpace internationally, with 123.9 million unique visitors and 50.6 billion page views versus 114.6 million unique visitors and 45.4 billion page views. From then on, things went downhill for MySpace pretty fast.

While it is good to know what happened, the reasons why that happened are the ones relevant for any startup.

It all started with a bug. Back in 2003, MySpace site had been developed in a matter of weeks, in a very agile way, as a clone of another successful social network at that time, called Friendster.

That rushed development resulted in a bug. Due to it, the users could change how their pages looked like by inserting HTML code in places where they were supposed only to write plain text. It goes without saying that was a very dangerous cybersecurity flaw. Fortunately, instead of doing bad things, the overwhelming majority of the users simply exploited the bug to make their pages look unique.

Seeing that, MySpace “listened to the customers” and turned the bug into a feature.

Soon almost everybody took advantage of the possibilities to personalize their pages. That led the MySpace management team to conclude the ability to customize one’s page was indeed one of the essential features for their users.

In the short term, the decision seemed to pay off: musicians and other creative professionals took advantage of the possibility to embed sound and video into the pages and started to showcase their work directly to the public. 2.2 million bands, 8,000 comedians, thousands of filmmakers had their MySpace pages. As a result, MySpace became even more attractive, and membership went through the roof.

Then Facebook happened.

While anybody could register on MySpace, until September 2006, Facebook membership had been restricted only to college students. In addition to that, all the Facebook pages had the same look because the only two things users could do were post text and pictures. Video would only be added in 2007. Audio files have yet to be allowed, 17 years after the launch.

Yet, in spite of all the restrictions on members’ creative ways of expression, once Facebook opened membership to everybody, MySpace lost most of its members to Facebook within the next two years.

Three questions come to mind:

1. Why did the MySpace users leave in such large numbers?
2. Could this have been predicted?
3. Could we learn anything useful for any startup?

Image via Unsplash

Why did they leave?

The most frequent complaint of those who left was MySpace had a “ghetto vibe”. All the “bling” and photos occasionally revealing a bit too much skin was quoted as the main reason for labeling it “ghettoish”.

However, independent studies done at the time showed the majority of the pages, while very colorful, actually had very decent content. But, as the saying goes, “perception is reality”.

Once the users felt “the ghetto vibe”, they concluded the “aseptic” or “boring” Facebook look and feel was preferable. After they left in large enough numbers, even their “ghetto-tolerant” friends had to follow them. A social network’s main appeal is our friends are also on that network. When our friends leave, there’s little for us left to do but follow them.

What made matters worse and enhanced the unflattering perception was MySpace had a cavalier attitude to spammers and advertisers of dubious products. As long as those spammers and snake-oil peddlers paid the fees, they were allowed to bombard the users with their unwelcomed messages.

This tolerance might be explained by the pressure exercised by News Corp, MySpace’s managing parent company. For instance, in early 2008, News Corp boss and media mogul Rupert Murdoch announced that MySpace would make $ 1 billion from advertising by the end of the fiscal year.

At the time of the announcement, the platform was generating less than 10% of that target. One can easily understand the pressure put on the MySpace management by such statements. They had to monetize the social network by any possible means by the end of the year. Even then, they failed in coming close to the target.

All in all, the combination of “ghetto vibes” and aggressively spamming users with ads for shady products resulted in antagonizing enough members and pushing them to Facebook. And that opened the floodgates.

Could this have been predicted?

Let’s start by looking at the fundamentals:

• MySpace was a social network.
• Its founders knew it was a social network.
• Its founders wanted it to be a social network.

In such a case, one would have expected all the 70+ years of scientific knowledge about social networks would have been used to design the features of MySpace. That didn’t happen!

Sociology and psychology started to study in the 1930s how people network with each other and form groups. By the time MySpace was launched, it was well known social class, ethnic culture, race, and religion are four compelling factors in shaping the connections people form.

People live in specific neighborhoods, go to certain pubs and clubs, take part in certain public events, go to certain places of worship according to their social class, ethnicity, race, and religion. Those are places where people from the other groups don’t go. We may like or dislike such self-segregation, but that is how things are in any society.

MySpace allowed people unlimited freedom of expression and, at the same time, failed to provide an equivalent of the separation existing in the real world. That unfettered freedom of expression made apparent the class, cultural, racial and religious divisions while “forcing” everybody to “live” in the same “place”. This meant most of the MySpace users would leave for a platform providing a better “separation” as soon as such a platform became available.

Facebook, with its limited freedom of expression, offered that equivalent to physical separation. Inside Facebook, people would still group themselves mainly according to class, ethnicity, race, and religion because they would be connected to the same people they know in their real lives. As it’s often quipped, people on Facebook live in their own bubbles.

Nevertheless, their social class, race, ethnicity, and religion would be less “in your face” thanks to the uniform design of the Facebook pages.

The phenomenon of physical separation and social class and racial lines even had a consecrated name in sociology: “the flight to the suburbs”. It started in the 1950s when the upper- and middle-class left the downtowns of the American cities.

The advertisers covet most the upper and middle class, and social networks make their money from advertising. So, when MySpace decided to allow users to do anything they wanted to their pages, they were setting themselves up for a “flight to the suburbs” and the loss of advertising revenue resulting from it.

So, what are some valuable lessons to remember?

1. Users might love our prototype simply because that’s the best available solution at that moment in time. Iteration, by itself, can only confirm a prototype is acceptable. Meanwhile, the investors and we need to know if the prototype is actually good;
2. A good product could hold its own against the competition, buying us time to redress the situation. An acceptable one would be replaced quickly before we have time to react;
3. The iterative process of improving prototypes needs to be combined with other methods, like checking our prototype against the relevant body of scientific knowledge. If we discover discrepancies, we make the corrections and then iterate with the users to see how they like the new prototype. This is the privilege of starting anything: corrections are cheaper to make earlier than later.

If we join the right accelerator, we will benefit from a whole set of methods to sort out the good from the acceptable. However, checking the scientific state of the art should be done first, as scientific knowledge is public and generally freely accessible.

Our team has come up with this fantastic idea. Even better, we know how to both build and sell it. The catch? In order to actually build it, we need more money than we currently have. In addition to this, we will need more money to set up the business, which would sell, deliver, and service it until we break even.

Since that’s a great idea and we have a great team committed to making it happen, finding funding should be easy, right?

Except it’s hard. It’s hard despite being an otherwise great time for startups in the early stage, with $6.8 billion dollars seed money invested in the first three quarters of 2020.

The good news is being at the very beginning makes it much easier to pivot. Changing is easy in the early stages. Altering the features of the product or service, changing the market segments we target, shifting the pitch to the investors are all less complicated if we’re just starting.

However, pivoting aside, what’s the first thing we should analyze when looking to create a company worth investing in? Well, naturally, the first thing we should look at is the idea itself. We know it is great, so we should first explore what prevents others from investing in it.

Seeing is believing

As the running joke goes, the fastest way to tell the difference between Machine Learning and AI is to look at what it is written in: if it’s written in Python, it’s probably Machine Learning. If it’s written in PowerPoint, it’s probably AI.

If we are to convince others to invest in our idea, we need to first invest ourselves in it. That means more than just taking the time to create a bunch of nice PowerPoint slides. Here is a 2-item checklist we should go through before we even consider pitching our idea to investors.

I. We have a product/service/software to show

Since what we show was developed without external funding it will miss lots of features.  We will have to use our spare time, our savings, and money from family, friends, and whatever else we have as resources until we have something else to show, in addition to a PowerPoint.

II. The product/service/software does the right thing better than the existing alternatives

Since this iteration will be missing many, if not most, of its features, compared to the final version, we need to ensure the important ones are already present in the prototype.

On the one hand, the lack of resources at this crucial stage could be a blessing in disguise, for it could motivate us to focus on what matters. On the other hand, we might run the risk of spending those few resources on the “nice to have” instead of on the “must-have”.

Therefore, one excellent piece of advice is “fail fast, cheap, and often”.

What that means is:

1. get the prototypes as fast as possible into the hands of the users;
2. get feedback on what needs changing;
3. implement the required changes as cheaply and quickly as possible;
4. test the prototype again;
5. repeat the process until the majority of the users are happy.

The merit of this approach is we get a prototype that we can confidently showcase to investors. We will also show footage of how happy the users are with the prototype. That works wonders convincing them to write us the checks.

Nonetheless, there are two critical challenges we must solve when taking this approach:

Image via Unsplash

1. It might take a lot of iterations

The first Dyson vacuum cleaner took 5,126 iterations before it was production-ready. All the venture capitalists refused to fund it, so Sir James Dyson had to mortgage his own house to cover the expenses.

In 1980, Edison stated he had made at least 3,000 iterations before finding a satisfactory material for the light bulb filament. However, unlike Sir James, Edison already had a successful business and a modern, well-staffed lab where he could carry out his experiments. So, he didn’t have to seek funding for the development stage.

Both Sir James and Edison were already experienced inventors by the time they managed to put together a finalized, working version of their product, yet they still had to refine it a lot before being investor-ready.

We should indeed fail fast, cheap, and often because we very seldom get it right from the first try. Furthermore, we need to do so in ways we can afford, which implies we need to innovate two things at the same time:

• our product/service/app;
• our way of iterating without running out of the initial resources. That’s usually something much more personal, like commitment, which can also be sapped by having to redo things again and again.

Joining the right accelerator helps with both. It provides us with the necessary guidance and creates the supportive environment we need in difficult times. Picking the right one can be tricky but not impossible. We simply have to look at what happens in the programs they run, and we’ll get a good idea of what’s in store for us.

Beyond this, we’ll also have to create a series of blog posts about making iterations more effective. That way, the teams working on these iterations can develop a better prototype before applying for an accelerator, increasing the chances of being accepted in the good ones.

2. We may latch onto the wrong features when our tests show users loving our prototypes

There are several reasons why that might happen:

• The users who accept to test our prototypes might not be representative of the market we would be targeting;
• The idea might be so new that users are enthusiastic about our proposal only until a better one shows up.

While the seeds of our idea’s demise could have always been identified beforehand, experience shows they become “obvious” only after the fact. The initial success of the prototype masks them or makes them seem unimportant. On top of that, human brains are hard-wired by evolution to seek confirmation instead of rejection. “Think positively” and “see the glass-half-full instead of half-empty” ring a bell?

Experienced VCs have seen this happening many times before. As a result, they might be skeptical even when we show them both the working prototype and the testimonials of the happy first users.

We need to go the extra mile of showing how we have investigated what could go wrong and how we can adjust quickly in the future, should a competitor come up with a better approach or if hidden problems surface. Or better yet, we should do both of these things! If they feel secure about their investment, they will be more likely to fund us.

That’s where a good accelerator can help. The accelerating programs worth participating in help startups avoid the pitfall of choosing the wrong features (even if they show early signs of success) and create a very agile business that can adapt quickly when conditions change.

Final thoughts

As we can see, coming up with a good idea and finding funding feels like cooking at rush hour – you have to be ready for anything your customers demand.

Summing it up, in order to be successful when seeking funding:

1. We need to have a prototype to show;
2. We need to have the prototype validated by a sample of everyday users;
3. We need to have a convincing method for future-proofing the product/service/app;
4. We need to have the three aspects mentioned above before drawing the business plan.