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The Product / Market Fit Cycle

ProductMarketFitCycleProduct / Market fit can be loosely defined as the point in time when your product has evolved to the point that a market segment finds it attractive so that you can grow your product / company scalably. In many ways, finding Product Market fit quickly allows you to focus on company growth rather than spending a lot of time and money on iterating your product to find that fit. Many companies linger in that limbo for quite some time unfortunately. Without this product market fit, it’s hard to inject nitroglycerin to generate the desired growth rate that all investors want when they invest.

Having spent time with several companies that have gone through the process of finding product market fit, I have observed that many get hung up on iterating only the ‘product’ part of product / market fit, rather than thinking of ‘product’ in a larger context. Speficially, the three things I notice are being omitted by several companies that have been religiously using the “Lean Methodology” product dev model alone to achieve PM fit, but failing to find it are:

1) A definition of a Minimum Viable (customer) Segment – As originally defined by Michael J. Skok
2) The testing of a well thought out positioning strategy alongside the testing of an MVP
3) The testing of a complimentary go to market / marketing strategy that tests your product vis-a-vis the chosen positioning strategy above

If you think of the three above as a bullet, visualise them as the lead pellet (product), the shell (positioning), and the gunpowder (go to market) that makes a bullet work. They only work when tested all-together, not separately. Testing only the lead pellet, doesn’t get your bullet very far.

In order to fit these three points into a more familiar framework, I have borrowed the Lean Methodology’s Build-Measure-Learn loop and expanded on it to create a larger loop designed specifically to help guide you achieve a series of test loops to achieve product/market fit. This isn’t perfect (and would appreciate any feedback on how to improve it) but I figure it’ll help provide a framework by which to test all in conjunction.

Here is the Product/Market Fit Cycle Model I propose (see attachment for illustration at bottom of post):

Start with a Product Hypothesis / Idea

This is effectively the way YOU think of your product the day you conceived it.
This should also have the rudimentary aspects of a defined value proposition for a set of customers.

Identify a Minimum Viable Segment (Customer Base)

The concept of an MVS comes from Michael J Skok’s observation of one of the flaws of the standard Lean Model. You can see his work on this here: http://www.mjskok.com/resource/gtm-segmentation. In summary, a Minimum Viable Segment allows you to test your product on a focused segment rather than leaving it too open ended across several segments, each giving your potentially different outcomes. The benefit of identifying a minimum viable segment is it allows for better differentiation of your product within your market segment, thus, you get easier referrals from this group as well as more efficient use of capital to acquire them.

Questions to ask yourself as you define your MVS:

*Who are my potential customers?
*How do I find them? (which blogs, which media, which social networks, which retail locations, which distributors, etc)
*What will they be willing to pay? (you may not know this off the start, but you’ll be able to determine this as you test it in the next step)

Build a Minimum Viable Business Model

The Business Model Canvas helps a lot in identifying a lot of the components needed for a fully operational Death Star, but what we are trying to test here is more ‘does it work’, rather than filling in all the components of the Business Model Canvas too early, and which you may not know at a start.

The three parts to the Minimum Viable Business Model include: A positioning strategy, an MVP, and a Go 2 Market Strategy.

*Build a Positioning strategy

As you create your positioning strategy, make sure it will resonate with your MVS and product hypothesis, or otherwise iterate these so that they are harmonious with each other. No point in having your positioning not be something that your MVS values, for example.
If you are not familiar with what a positioning strategy is, read the following book, it is the gold standard: Positioning by Jack Trout & Al Ries

*Build an Minimum Viable Product that fits the above positioning strategy

Most tech founders generally rock at this bit, so nothing I can really add here. However, take a look at my previous post on growth hacking summarising Traity’s experience in optimising their product to yield better conversions if you want to optimise your product for growth and reduce the potential of your product getting in the way of conversions: http://thedrawingboard.me/2013/04/15/on-growth-virality-loops-and-customer-acquisition/

*Build a Go 2 market strategy

A Go 2 Market Strategy is, simply put, a strategy that attempts to cost-effectively deliver the value proposition to the selected target segment(s). It is a strategy to help get the product or service out in the marketplace and includes pricing strategies, sales strategies, and marketing methods (internet marketing, direct marketing, PR, etc). It can include things like identifying key distribution channels and key partnerships required to get your product to the identified minimum viable segment. Clearly this will be different for B2B companies than B2C companies. The aim is to build a Go 2Market strategy that targets you MVS with your selected positioning strategy for best effect.

Once having completed and packaged the above three in a minimum viable form, assign a “cost” (what money you are going to spend on validating it) to the combination and set some expectations around target figures upon which to analyse your resulting metrics. How many users are you expecting, what constitutes an ‘active’ user? A churned user? A conversion? etc. Effectively, you want to have ‘targets’ for what you experiment will yield.

Test & Measure

As you know, a key part of understanding forensically whats happened after a test, you will need to have set up good tests to start with and also adequate data. A good book on this is: http://leananalyticsbook.com/  I’m in the middle of reading it, but so far it seems in line with what I’ve seen several startups doing.

Tests will include quantitative (Kissmetrics & http://newrelic.com/) and/or qualitative tests about how the product is perceived based on people that didn’t activate. Using the output from your tests find out how your users are behaving to gain intelligence.

However, keep in mind that testing will be different between the different phases of startups in how you can test. In the words of Andreas Klinger (co-founder of Lookk):

 I personally see product dev as a spiral. The further you go outside (mature) the more quantitative your approaches can be, the further you are yet on the inside the more qualitative. You repeat the same phases (build,measure,learn etc) but you use different tools.

 Most startups are in that inner core of that spiral but play games of outer ends. We can call this premature scaling or just inefficient behaviour (e.g. using metrics when there is no clear data). Many product hypotheses/ideas and especially customer segments can already be eliminated very cheaply before MVPs – eg by qualitative approaches (eg customer interviews).

Metrics are for me personally a bit further down the spiral.

Once you go down the path of metrics, use the Pirate Metrics framework (summarized below) to forensically analyse why (http://500hats.typepad.com/500blogs/2007/09/startup-metrics.html)  –

* Arrivals & Acquisition – How many people landed on your website coming from a marketing campaign that you are tracking and then you acquire the user. For a SaaS product, this usually means a sign up.
* Activation – The user uses your product.
* Retention – What is your churn? How many of the users you have in your userbase are active? How many stopped being active and why?
* Referral -How many of the users that are using your product are willing to refer to others?
* Revenue -How many users are willing to pay you of the ones that are using the service?

Learn/Debug your Minimum Viable Business Model (MVB – yeah ok, too many MV* acronyms, but too long to spell out)

Questions to ask yourself as you are reviewing the metrics:

Are you having high arrivals but poor Acquisition/Conversion? – Perhaps your Positioning is working, but your product isn’t living up to expectations. Think about this as you talked about a great party but when people showed up they thought the party (product) was lame.

Are you having high acquisition/conversions but poor arrivals? – Perhaps your positioning/marketing strategy is not working, and for those few people that are in your MVS that land on your site by luck, convert because they find the product useful. Perhaps you didn’t allocate enough cash to your Go 2 Market, or rather the cost of acquisition of the chosen MVS is higher than expected so you are just aren’t getting enough eyeballs on the site, but when they do they convert.

Are you having so-so arrivals, and acquisition at your target figure? – Perhaps your Go 2 Market strategy is not cost effective, or you didnt find the most efficient channels. Perhaps you didn’t allocate enough money to the Go 2 Market strategy.

Are you having high Arrivals, high Acquisition & Activation, but poor Retention? Then likely your product is failing in delivering ongoing value. There is something wrong with it. Use product analytics to find key churn out points and qualitative studies to find out what is pissing people off.

Are you having a hard time monetizing? – Perhaps there isn’t enough value in the product hypothesis for the MVS if you can’t get anyone to pay even if they are engaged (not enough of a pain).

No referrals? Well, likely a function of the above as well. Perhaps you haven’t build enough virality into your product (see Juan Cartagena’s work on this).

Decision point & New Ideas

Now that you have the output and a series of metrics and potential red flags as to where things went wrong.. you can consider various options before you go through the loop again:

Do I iterate on one of the factors of the Minimum Viable Payload? (try a different positioning strategy, go 2 market strategy, or product revision?)
Do I pivot to a different product hypothesis?
Do I pivot to a different minimum viable segment?

In conclusion, I hope you find this framework useful in helping you diagnose what you should try out. Let me know what you think and if you’d add/subtract anything to it.

Click here to see the full diagram of the Product / Market Fit Cycle.

Here is the slide share of a recent presentation I gave on the subject: