(2017-06-28) Balfour Why Product Market Fit Isn't Enough

Brian Balfour: Why Product Market Fit Isn't Enough. (Four Fits) There are certain companies where growth seems to come easily, like guiding a boulder down hill. These companies grow despite having organizational chaos, not executing the “best” growth practices, and missing low hanging fruit. I refer to these companies as Smooth Sailers

In other companies, growth feels much harder. It feels like pushing a boulder up hill. Despite executing the best growth practices, picking the low hanging fruit, and having a great team, they struggle to grow. I refer to these companies as Tugboats - a lot of effort for little speed

what the difference between these two types of companies isn’t...

It’s Not Just Great Product

Building a great product is a piece of the puzzle, but it’s far from the full picture.

The problem with the answer of “build a great product” is that it leads to something that Andrew Chen and I talk about extensively in the Reforge Growth Series called the Product Death Cycle

These are the phases of the product death cycle:

• Add New Features: Team adds new exciting product features.
• Launch: Features are launched with some press.
• Spike: A short term spike in growth occurs.
• Growth Flattens: Within weeks the growth flattens off.
• (repeat) Add New Features: Team ends up back where they started, adding new features to get another spike.

It’s Not Just Product Market Fit

The issue with the product market fit mantra is that we have taken it to the extreme and developed tunnel vision. Statements like “Product Market fit is the only thing that matters” have become more common

There are plenty of companies that have all the product market fit signals (I’ll talk about these signals in the next post) but still struggle to grow, and definitely don’t reach a $100M+ product.

It’s Definitely Not Growth Hacking

While the term started with good intentions, it has morphed into a concept around hacktics

Before tactics you need a growth process. But before a growth process you need a strategy. This framework is all about how you construct your strategy and position yourself for "Smooth Sailer" growth.

What is the difference between Smooth Sailer and Tugboat companies?

make four pieces in a puzzle fit:

There are four essential fits: Market Product Fit, Product Channel Fit, Channel Model Fit, Model Market Fit. I'm going to dedicate a post to each of these fits, along with how you can apply this framework.

The Road to a $100M Company Doesn’t Start with Product. In the introduction to this series I made the point that Product Market Fit isn't the only thing that matters. It is actually only one of four fits needed

I'm going to focus on the 5 elements of Product Market Fit that I believe are most misunderstood and overlooked:

In 2008 I co-founded a company called Viximo

We had a solution (virtual goods platform) that was looking for a problem and a market (dating sites, social networks, etc.).

What we should have done instead was to focus on the problem and market, then search for the solution. This common mistake is why I prefer “Market Product Fit” over the terminology “Product Market Fit.”

The reason for this is because the real problem is something experienced within your market and by your audience, not something that lives within your product

Searching For Market Product Fit The Right Way

When I got to HubSpot, I joined a brand new division in the company with just six other people. We were tasked with building the road to a second $100M line of business

Rather than focusing on the product first, we narrowed in on defining the market.

There were four key market elements that we looked at:

• Category. What category of products does the customer put you in?
• Who. Who is the target audience within the category?
• Problems. What problems does your target audience have related to the category?
• Motivations. What are the motivations behind those problems? Why are those problems important to your target audience?

While I find most companies really understand the “category” and the “who,” defining the problems and the motivations behind those problems is far more important.

We explored multiple things in each bucket

ended up the following combination of market elements

Out of this problem and market definition, the team started thinking about the product (solution). Through the awesome work of Christopher O’Donnell, Dan Wolchonok and a few others, they formed a really simple tool called Signals, which was then rebranded to Sidekick, and then rebranded again to HubSpot Sales (more on this later).

The product was extremely simple. It consisted of a Chrome extension that, with a click of a checkbox, let you track your emails and get instant notifications on who opened and clicked on your emails.

They now had an indication of where the prospect was -- if the prospect saw the email, if they clicked or viewed a proposal, if they forwarded it around their company, and more. The core product was free, with a $10 tier for unlimited notifications

This brings us to the next group of elements in defining Market Product Fit -- the product hypotheses elements.

• Core Value Prop.
• Hook
• Time To Value.
• Stickiness. How and why will customers stick around? What are the natural retention mechanisms of the product?

For the Signals product, the hypotheses looked like this...

These hypotheses are extremely important to lay out. As you will see in future posts of the series, it informs and deeply affects the other components of the framework like Channel and Model.

The Reality Of Searching For Market Product Fit

In practice, the search for market product fit is never a straight line. Instead, it happens over multiple cycles of iteration. You start with a market, build an initial version of the product, look at who actually gets value from the product, then redefine the market and redefine the product.

we found a lot more target personas outside of our sales audience hypothesis were getting deep value out of the product

The refinement didn’t stop here. We had another major shift about a year in which I’ll talk about in future posts.

Market Product Fit Is Not Binary

Market Product Fit is not binary. It’s also not a single point in time.

There are two primary ways that the market changes for a startup.

1. EXPANDING MARKET DEFINITION

To expand into these concentric layers, the product typically needs to change to maintain the strength of market product fit.

2. THE MARKET EVOLVES

markets with which you have strong Market Product Fit will evolve over time.

think about the shift from web to mobile.

Signals Of Market Product Fit

If Market Product Fit isn’t binary, then how do you know if you have Market Product Fit?

How do we combine qualitative, quantitative and intuition indicators

1. QUALITATIVE

my preference is to use Net Promoter Score (NPS)

higher probability for generating a false positive result, so take it with a grain of salt.

2. QUANTITATIVE

Retention Curves and Direct Traffic.

In 2013 I first spoke about how flat Retention Curves indicate Market Product Fit.

for 80% of B2C and B2B products out there, flat retention curves is what you are looking for.

The second quantitative indicator is direct traffic. Direct traffic is typically the result of word of mouth. If you are truly solving an audience's problem, they tend to tell friends. It might not be a lot of direct traffic, but there should be some. (organic growth)

Sometimes I like to ask the question, “If you turned off all your marketing efforts today, would you keep growing?” The answer should be yes. The growth might be slow, but it should still be naturally growing.

3. INTUITION

It’s hard to understand intuitively if you have Market Product Fit unless you’ve been part of some situations where you don’t have it and some situations where you do have it. I’ve been in both situations.

It really feels like everything in your business has gone totally haywire. There's a big rush of adrenaline from customers starting to adopt it and ripping it out of your hands. It feels like the market is dragging you forward.

Product Channel Fit Will Make or Break Your Growth Strategy.

false beliefs such as “Product Market Fit is the only thing that matters.” A byproduct of that false belief are statements such as:
“We are focused on product-market fit right now. Once we have that we’ll test a bunch of different channels.”

two major issues with this statement

1. Products Are Built To Fit Channels, Not The Other Way Around

Products are built to fit with channels, not the other way around. The reason for this is that you do not define the rules of the channel. The channel defines the rule of the channel.

What are some general elements of products that fit with different categories of channels:

Paid Marketing. To have product channel fit with paid marketing: Quick Time To Value

Medium to Broad Value Prop -

Transactional Model -

2. The Power Law of Distribution

at a given moment in time a company that has product channel fit will get 70%+ of their growth from one channel.

you look at most $100M+ companies, you will find this to be true:

• UGC SEO: TripAdvisor, Yelp, Glassdoor, Pinterest, Houzz all got 70% of their growth from UGC SEO.
• Virality: WhatsApp, Evernote, Dropbox, Slack all got 70%+ of their growth from some form of virality.
• Paid Marketing: Supercell, Squarespace, Blue Apron all got 70%+ of their growth from some form of paid marketing.

Companies that are able to achieve product channel fit with multiple channels are rare, but end up being monsters. LinkedIn is the perfect example where over time they've achieve Product Channel Fit with Virality, UGC SEO, and different forms of Inbound and Outbound Sales.

Product Channel Fit has a few immediate implications:

1. You shouldn’t take a shotgun approach to testing channels: is better to prioritize and tackle one or two at a time in pursuit of your power law channel

2. Over time you shouldn’t seek to diversify channels for the purpose of diversification.

3. Don't have team members focused on user acquisition and team members focused on product in silos from each other.

Product Channel Fit Is Your Blessing and Your Demise

Product Channel Fit (just like all the other fits) is always evolving and can break as a new channel emerges or an old channel gets killed off.

1. New Channels Emerge

There has been no clearer example of this than the gaming industry.

In the early 2000’s desktop web portals were the major channel. You had big flash gaming companies emerge like PopCap

Then in early 2007, social emerged as a new channel with the Facebook platform. The flash web gaming companies tried to just copy/paste their games into the new channel and it didn’t work. They left the door open for companies like Zynga and Playdom to emerge and build products that fit with the new channel.

Online Dating is another category where there are tons of examples:

1. Old Channels Get Killed Off

Many companies were also effected by Facebook killing off this channel.

Pinterest was one of the few that transitioned successfully. They ended up transitioning to a UGC SEO channel which has driven their growth ever since.

Part of that transition over the long term was that Pinterest also changed their product focus from a social product to more of a personal utility.

Get Out of the ARPU-CAC Danger Zone with Channel Model Fit.

Channel Model Fit is simple - channels are determined by your model.

The two most important elements of your model are:

• How Your Charge -
• Average Annual Revenue Per User - (ARPU)

A common question I get at this point is: “Why only look at average annual revenue versus full LTV?”

The reason is because most startups need to keep their payback period to less than one year.

The ARPU <-> CAC Spectrum

Every business lives on the ARPU ↔ CAC Spectrum. On far left you have businesses that have low ARPU and as a result have to use low CAC channels to drive customers. On the far right you have businesses that have high ARPU and as a result are able to use high CAC channels

Most B2C companies driven by an ads model — companies like Facebook, WhatsApp, and Yelp — live on the left hand end of the spectrum. They have low ARPU, and therefore have Product Channel Fit with low CAC channels like Virality and UGC SEO.

One step over on the spectrum you have slightly higher ARPU businesses. Think of something like Dollar Shave Club or DraftKings. Businesses with transactional models (i.e. subscription e-commerce) typically live here.

In the B2B world you also have B2B products like MailChimp, Slack, or SurveyMonkey that live on this end of the spectrum as they take advantage of viral and paid channels to drive most of their volume.

Shifting over to the right hand end of the spectrum you have higher ARPU businesses (typically B2B Mid Market companies) like HubSpot and Zendesk. They have higher ARPUs and can therefore take advantage of high CAC channels such as content marketing, inbound/inside sales, or channel partnerships

Finally on the far right hand end of the spectrum you have very high ARPU businesses (6 to 7 figures) and therefore take advantage of very high CAC channels such as enterprise and outbound sales. Companies like Palantir and Veeva exist on the very far end.

If you notice above, I left the middle of the spectrum blank. This is the ARPU-CAC Danger Zone.

companies that end up in this zone have a much higher failure rate because they lack Channel Model Fit. These companies' problem with Channel Model Fit can be broken down into two major reasons.

1: Too Much Friction For Low CAC Channels

Low CAC channels require low friction products (quick time to value) and low friction models.

The greater the friction, the less effective the lower CAC channels are because they just don't influence a user's decision enough.

2: ARPU Doesn't Support Higher CAC Channels

Companies in the danger zone also have ARPUs that are too low to support the higher CAC channels.

The danger zone does not imply that a business can't exist there. You can have a business here, but your acquisition strategy ends up a patchwork of bits and pieces from a lot of different channels rather than owning one channel

Channel Model Fit doesn't just exist for overall companies; it exists at a product tier level as well. LinkedIn is a great example of this.

LinkedIn Free - On the left end of the spectrum they have their free product driven by Virality and UGC SEO. Low ARPU (advertising) therefore low CAC channels.

LinkedIn Premium/Jobs - One step over they have LinkedIn Premium and LinkedIn Job Postings. Higher ARPU, therefore they can take advantage of higher CAC channels like Paid.

LinkedIn Talent, Sales, and Learning Solutions SMB - LinkedIn also has B2B products in Talent Solutions, Sales Solutions, and Learning Solutions for small and medium sized businesses. Here they use mostly Content Marketing and Inside Sales.

LinkedIn Talent, Sales, and Learning Enterprise - They also have enterprise tiers of their B2B products and use outbound enterprise sales to drive those.

Implications Of Channel Model Fit

1. Don't Treat Model and Channel In Silos -

2. Don't Treat Channel Model Fit In A Silo

The Model Market Fit Threshold & What it Means for Your Growth Strategy

Model Market Fit is the concept that your market (and # of customers within your market) influence your model.

The first time I heard about the underlying concept of Model Market Fit was from Christoph Janz @ Point Nine Capital

In Christoph's post he published the following graph:

Most companies end up falling in one of five areas that Christoph named:

• Elephants - Products that get 1,000 customers paying $100K+ year
• Moose - Products that get 10,000 customers paying you $10K+ per year
• Rabbits - Products that get 100,000 customers paying $1K per year.
• Mice - Products that get 1M customers paying $100 per year.
• Flies - Products that get 10M customers generating $10 per year

Your Model Market Fit hypothesis revolves around some simple math:
ARPU x Total Customers In Market x % You Think You Can Capture >= $100M

I recommend thinking through them in this order:

Total Customers In Market: how many target customers meet those criteria.

ARPU: understand what their willingness to pay is for your solution to build your ARPU hypothesis.

% You Can Capture: it is easy to overestimate the percentage you think you can capture. For example, if you are a SaaS startup and this variable comes out to 50%+ then you should be worried....for SaaS businesses where there aren't strong network effects, I use 10% as a rule of thumb

Moving from Market to Market

Often when you use the Model Market Fit equation with the niche market, it never ends up equaling >$100M. That's fine. In that case, you just need to have hypotheses for what the next expansion markets are and how big they are.

The more times you need to expand to get to a $100M+ business, the riskier your core hypothesis is.

Why Most Companies Fail At Moving Up or Down Market

You Need to Find All Four Fits to Grow to $100M+

Do you need all four Fits to build a profitable company? No. But, you do need to have all four to build a $100M+ product on a venture timeline.

Evidence of the four Fits is most apparent in the SaaS space. We can look at almost any category in SaaS and find multiple $1B+ companies who all essentially have the same core product. I look at that and ask how that can be?

In the email marketing space, we have multiple companies valued at $1B+: Marketo, HubSpot, and Mailchimp.

Marketo: Their market is the enterprise.

Because of that, they use Outbound Sales to sell (Product Channel Fit).

HubSpot: Their market is the mid-market

Mailchimp: Their market are small businesses. As a result they've differentiated their product on being simple and touchless (Market Product Fit).

The reverse also happens. Plenty of startups try to attack all three tiers of the market with the same product/channel/model. But it doesn't work.

You Can't Think About the Fits in Isolation

All of the fits influence each other

This doesn't mean that you try to prove all of the hypotheses at once. There is a difference between formulating a hypothesis, and proving a hypothesis.

You spend the majority of the earliest phases proving Market Product Fit, but you need to do that in context of having hypotheses for the other fits at the same time.

You Have to Revisit All of the Fits on an Ongoing Basis

In earlier stage companies you need to constantly revisit for a different reason. You are constantly proving or disproving your hypotheses as you learn. When you disprove a hypothesis, you make a change. But when you make that change you need to revisit the four fits to make sure they all still fit together.