iSPIRT works to transform India into a hub for new generation software products, by addressing crucial government policy, creating market catalysts and grow the maturity of product entrepreneurs. Welcome to the Official Insights!
Author: Thiyagarajan M
M. Thiyagarajan (Rajan) is a Co-Founder & Fellow In Residence at iSPIRT and leads the M&A Connect program. Prior to this he was the head of products for Quickbooks India, a Saas accounting software. Rajan was an entrepreneur earlier and was involved in 2 mobile startups in product & engineering role.
Rajan holds a Bachelor’s degree in Computer Science Engineering from IIIT-H
Twitter : @mtrajan
LinkedIn : http://in.linkedin.com/in/thiyagarajan/
Views stated in here are personal opinion
The journey is unstoppable. India has started building software products that the world recognizes… a far cry from the days when it was known only for software programmers and not for software. Through its successful Playbook RoundTables and Community platform, iSPIRT’s ProductNation initiative has touched the lives of hundreds of product entrepreneurs across India.
ProductNation thrives on the strengths of our Volunteer community who are people just like you. This community is proud to announce the ProductNation Summit coming this December in 2013. We will soon be on twitter, just follow us @Product_Nation and the #PNSummit hashtag.
#PNSummit is selflessly hand-crafted by Product folks, a Summit attended exclusively by Product folks. A lot is going to be talked about Customer Discovery and Growth Hacking. #PNSummit has lean forward and lean back sessions and is practitioner led with over 70% of the sessions being interactive. These sessions are no holds barred. They are practical, frank and maybe even brutal. It will be a gurukul, where teacher and taught share the same platform, only the roles are reversed. Yet there is no sage on stage, only like minded peers.
If this sounds like just what you are missing, we’ll be delighted to send you an invite. Just let us know a little more about you, so we can ensure the other folks in the room are also passionate Product folks. Seats are extremely limited and there is a marginal Attendee fee. What gets you in is not the fee, but your passion, i.e., what you do.
Once you’ve been there, you can take back a lot more that what you learn in 2 days. Insights from great like minded people like you, a platform to share and learn for 4-6 months after the summit, and friendships for a lifetime. Seats are extremely limited and open only for the first 100 who get invited.
Your current situation is not important. If you have the mindset, Invites for the lucky 100 will not remain available for long. Gates close on 30th September.
One of the most difficult things in a product startup is to know when has progress happened and if it is in the right track. This is an even more difficult problem for first time product entrepreneurs. Not to say that it easy for a second time entrepreneur but in that case experience intuitively guides.
Most prevalent thinking is to go from idea to a product build phase leading to a launch in alpha & beta followed by several product releases. Sales & marketing gets somewhat sprinkled on top of this mostly spread after the beta release.
Another way to think about this that I have found very useful is the following.
When the anatomy of an idea is examined it leads to revealing of problem and solution hypothesis inside it.
Problem/Solution Fit
The first stage or milestone therefore lends itself to a problem/solution fit. This is the stage when product idea under question has established that it addresses a large pain point and demonstrated a solution that works well for the problem faced for a specific set of users/customers. For a B2C company this occurs when a few 1000 of users exists and some amount of recurrence or stickiness exist. In case of B2B or SMB product 1- 5 paid or evangelist customers.
User/Experience Fit
Subsequently this milestone involves having identified the right architecture/flow, copywriting that connects & forms right positioning in the mind, visual and graphic design to create an element of identity for perception and recall. Essentially providing an experience to the identified user/customers that truly delights and helps improve acquisition and create retention.
Product/Market Fit
Product/Market Fit is a term that was coined by Marc Andreessen. It means being in a market with a product that can satisfy the market. It is the stage where the product is used or adopted repeatedly by a sizable number of users/customers
Sean Ellis further refined the definition to say that in a survey with customers they are told that product that they are have been exposed would be discontinued and if at least 40% of customers will revolt at that the thought.
In B2B/SMB it is few 50-100 customers and beyond, In B2C it is at least 200,000 users with a good repeat usage could be roughly called to.
Business Model/Scale Fit
It is the growth stage where the right business model for growing at scale is identified at which truly phenomenal growth happens.
Up until the Product/Market fit it is phase of learning and discovery and several iterations & pivots can and do happen. While this happens it is also important to keep in mind another stage though not related to the product but an important one.
Founder/Problem Fit
Sometimes founder starts with a big vision about the product idea however having to identify a problem that is truly worth solving can be highly iterative process and can look very different from what was originally envisioned. It is important for the founder to re-establish that the revised version is indeed something that continues to motivate to build. This stage ideally should be post problem/solution fit and before user/experience fit.
This model is not an original one or not even the only model of thinking about stages of a product startup but it helps frame answers for many things.
Each successive stage marks reduction of uncertainty and better modeling of risks in product success journey.
Visits, Page Views, number of downloads are not good enough for product/market fit. It may be necessary but not sufficient.
Product/market fit success is not equal to business success. In my previous startup I built a mobile app (turn phone into webcam) with over 1.5 million downloads and very high daily active usage and along with an excellent NPS. Product was super success but with no business model ( in the pre iOS era of no app store or mobile ads) the business did not succeed.
Early business traction is not equal to product success (not even problem/solution fit). Ex: Several of the Indian e-commerce companies.
Job of an accelerator is to help take companies beyond Problem/Solution fit. If the market structure allows smaller cycle feedback loop then it should even achieve User/Experience fit by the time startups graduate from these accelerators. Unfortunately many view accelerator as a way to get funded forward.
In India most of the product startups are stuck at just before reaching problem/solution fit and also just before product/market fit.
What are the mental map of your product startup progress ?
When building a product it is very easy to make a list of features to build. One could brainstorm to create an initial list, copy features from a similar product or ask others (including potential users or customers ) via a feature wish list.
However which feature to prioritize and what to build first? is one of the most burning question for startup founders and early employees.
There will always be more features to build and add than there is the capacity or bandwidth to build.The additional challenge is even after building it is not clear if it was the right decision.
These decisions typically happen based on what one thinks is cool to build or someone has asked to build first. For lack of a better framework to use to decide that is how things move forward but time runs out, product builder stand clueless what should have gone in the first place.
LeanStartup principles offer a framework for thinking about this. BUILD gets complemented by MEASURE & LEARN and which further loops.
At the beginning of an idea building an MVP is good step forward (which as we previously is tool for learning & may not be any feature of the product) to learn a little bit more.
With learning from MVP additional features can be decided upon. List each feature in terms in terms of the learning that they should yield along with a defined metric.
At various stage of a startup different metrics matter and come into play. For instance in the very beginning along with the MVP – validation of problem & solution is the important metric. Once that is established metrics relevant user acquisition, retention, referrals become important.
The first step to decide before periodization is to decide the metric for startup to focus on. Once the metric identified picking the feature become easy.
For instance for a product the problem/validation is established the next important stage is to acquire users really fast then to prioritize a feature ask the question “Does feature X allow to acquire users more by Y%”. Pick the feature first that will have the higher score for this. If development time comparison for the feature is steep then factor it in the trade-off.
In essence the question “Which features to prioritize to first” is to be really framed as “Which learning to prioritize first ?”
You may find it useful to read the previous post on importance of ambiguity tolerance and questioning for an engineer transitioning to a product guy before reading this post.
When I was first tasked with writing new features for an existing product that contained thousands of lines of code I earnestly started reading through the documentation & code to understand how it is structured and to figure out the APIs to use. My then engineering mentor said to me
” Reading through the documentation & code you will spend days or even weeks forming mental model which you will learn may not be accurate as you implement your code later on, leading to a lot of wastage of time and redoing. Instead setup your environment, load the code inside a debugger, put a breakpoint and run it through. If there are specific areas you want to learn then ‘step in’ to that function. This way you will learn about it faster, more accurately and spend less time redoing“
I found this advice to be a great insight and I think it extends in many places.
As a product startup one always start with an idea and then forms mental models around that (business plan or business case studies) and then build things based on these models to later realize they were not accurate thus wasting a lot of time. In the harsh world of startups you don’t get another chance to re-write.
You have to know very early if your idea will work before you can commit a lot resources on it. Things that determine if your idea works are some of the following –
Will it be adopted by users,
Will it talked about to friends,
Will it paid for by someone,
Or even celebrated & craved.
Essentially will it create the impact for you and the world that you dream it will.
MVP – your Idea Debugger
To know if your idea will work you should run it through a debugger that can tell you that the logic of idea will lead to its intended impact.
Enter the Minimum Viable Product (MVP), a term first coined by Frank Robinson and further popularized by Eric Ries. Today it is a term that is quite loosely & liberally used and at times even abused. MVP is a misnomer in the sense it is not the stripped version of the product but it is really a tool about learning & risk reduction around customer & market. It is employed to uncover critical learning of your idea. MVP is best thought of as the debugger of your product idea.
Before we start getting into the details of an MVP, let’s examine the anatomy of an idea first
Idea Anatomy
An Idea consists of the following elements
Vision – A new state of the world that will be in place if the idea becomes successful.
Problem – A friction that is coming in the way of job that a beneficiary is trying to get done
Solution – A proposed alternative for removing the friction
Beneficiary (also called as Customer* or a User**) – Someone who is going to benefit from the idea
* Customer is one who writes the cheque for the service consumed. **User is someone who uses the product or service
Example:
Let us take an example to illustrate. Suppose you came up with an idea for creating a mobile SariApp that shows how to drape a sari. It could be dissected the following way.
SariApp Vision: More women in the world in touch with their Indian traditions (or traditional Indian dressing)
SariApp Problem: Would like to wear a sari for attending an Indian function but have no past experience or knowledge of draping a sari.
SariApp Solution: A screen by screen illustration of each step of sari draping.
SariApp Beneficiaries (customer): Women who have been fascinated by this Indian dress or those who who grew up outside of India never bought a sari before.
Once you do this you realize that problem, solution & beneficiaries are all at best guesses or assumptions that you make. The task of debugging your idea thus becomes one of converting each of these guesses into verifiable facts that either proves or disproves them.
How MVP clarifies Idea logic
After you list down the things that are big unknowns in your idea you build something minimal (your MVP) to question it. The interesting thing about the MVP is that you have to build one for every idea, the same debugger can’t be used for every idea and the same learning does not apply everywhere. You could design an MVP to test or uncover learning one element or combination of elements (about just problem or combination of problem/solution/customer segment in the idea).
An example of an MVP for the above SariApp could be a simple landing page that articulates clearly the problem statement, the solution and call to action (such as leaving an email address to get contacted when solution becomes ready). Responses from traffic directed to the landing page will help learn about the merit of the problem/solution. If there are high number of clicks on your landing page but very few clicks on call to action a most likely interpretation of that could be those who visited care about the problem but not the solution. If the visits itself was very few then it is most likely they don’t care about the problem itself as you have stated it and so on and so forth.
Few things to keep in mind
The fidelity of the MVP is very important aspect to note which describes the minimum-ness of the MVP and plays a key role (see diagram) on the learning and how fast you get it. You have to start with testing the value proposition (a concise statement of problem & solution together) of the idea and increase the fidelity to learn more.
In most cases MVP mostly tells what does not work rather than what works or even why it works. One has to iterate over changing the MVP and increasing the fidelity of it.
So what are the debuggers (MVP) you have built for your idea?
In the next post we will look at “Four critical stages of Product Startup Fitness”
When you work as an engineer regardless of whether it is startup or a big company (in consulting services or products) you are always given guidance on what you should build. Even the most autonomous programmers when working independently has someone tell him what to do. However when you become the founder of a startup the most stressful thing you immediately encounter is ‘What should be built?’.
This decision is guided by what-if scenarios or even based on what is cool to build and show off to others. If you are somewhat disciplined then you document these thought somewhere before you start writing code. In software engineering language this is also referred to as requirements analysis document. Little thought is given to how does one know that this is indeed something needed by someone. To address this one of the best techniques known to engineers is applied – abstract it away. You decide to assume that whatever conjured up is indeed correct to help make further progress as sitting idle without any doing any coding is a waste of time.
When you were just an engineer working elsewhere the impact of such assumption is someone else’s problem but now the impact is on you. Also given that you have limited runway the stake for making mistakes about that question is very high.
You thus face two scenarios which as engineers you may have never faced.
To make a decision in the face of unknown
To own the decision you make
Product entrepreneurs realize this situation and resist the urge to make any assumption and proceed with a learning mindset. They make decision to the extent to which they can learn. Infact the really great entrepreneurs mentally sequence their unknowns (assumptions) in the order of most negative impact and move forward to uncover them.
These are in fact the two key skills that a startup product manager should become excellent at – owning the decisions & discovery (learning) before making decisions.
“It doesn’t matter how beautiful your theory (idea) is, it doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s wrong” – Richard Feynman
Building a successful product startup is like trying to win a race driving a vehicle that has less than half its fuel tank filled, whose controls you don’t fully understand and moreover don’t know where the finish line is. What is known is the visibility of runway for next few meters and inspiration from stories of how many has won such race to gain riches.
While the analogy might look far-fetched but startups work under the circumstances of extreme uncertainty. They might herald around a great idea that they think will change the world there is many things that are unknown – the problem being solved, if their solution is the right one, they have the right team to make it happen and so on.
Risk
Risk is the common language that is used to describe and address the elements of uncertainty in life. There are few kinds of uncertainty that a startup has to eliminate as it goes forward on its road to success. Some of these risks are the following
Technology Risk – Can the startup build what it is planning to build with the current state of the art technology? In many cases this may not be a question but products that are at bleeding edge of technology has to evaluate this question. For technology entrepreneurs this is where the motivation for them to build the product would have first started and thus they start the journey here and spend their most of the time.
Product Risk – While the aspect of can build or not is one thing, the other element startup faces is what kind of feature to build first. What is must-have & nice to have feature.
Execution Risk – Is the startup staffed with right team to get things done. Are they able to pull off what they plan to do or are just paralyzed while coping with ever changing conditions on almost everything.
Customer Risk – Finally whether what the startup is building will be used by a set of users, if they will or somebody else will pay for the usage, recommend it to friends after they have used it.
Market Risk – This is aggregated customer risk, are there enough number of customers who will use, pay & recommend? Is there a viable way to reach to them, interact with them and also collect from them?
Resources
While startups address these risks an important law of life – “Resource are limited”
‘Time is limited’ – Startups would have setup or planned a certain time duration during which they wanted to try out their startup.
‘Money at disposal is limited’- Regardless of how financing is done (self or external) money is always in short supply
‘Energy is limited’ – Ask any entrepreneur who has been at it for couple of years and has not seen any breakthrough in progress, he would tell how jadedness and fatigue starts to set in.
‘Even a supporter’s patience is limited’ – In initial days many encourage to give support , after not seeing much tangible progress for a while there is degradation in their support in kind or even words.
Given that the resources are limited how startups approach addressing the risk matters.
99% of the time the following is how startups address risks
Many startups try to extend their resources by raising money. But that alone is not the resource that is limited. Moreover even after extension through infusion of money if startups can’t remove customer risk then the same fate applies.
A workable approach however could be trying to address elimination of customer risk first and also broaden it to market risk.
The most important thing for any product startup is to reach product/market fit .
By focusing on eliminating customer risk is the fastest way to reach there.
Over the last few years a lot of learning has been understood on how to eliminate customer risks, these learning are well documented as customer development and lean experimentation.
Few key principles of these are the following
All statements are assumptions or guess
All answer lie outside the building
Change guesses into facts using experiment with customers
Start by building uncomfortably small prototypes to test with customers.