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In his data driven book “India Uninc”, Prof. R Vaidyanathan explains the significance of “non-corporate” sector in the Indian Economy.
Non-corporate sector, comprising of proprietorships and partnerships, is the biggest contributor to Indian GDP leading far ahead of Corporate sector, Government and Agriculture. It is also the fastest growing as “Uninc” holds the biggest share in the fastest growing service sector.
I think Marketplaces are more efficient in such decentralized systems. Platforms, enabled by internet and mobile, can scale up faster than “corporatization” of these unorganized sectors. What are these sectors? Almost everything in India is dominated by unorganized – Education, Transport, Real Estate, Restaurants, Hotels, Retail, Warehousing, Construction, Manufacturing.
While growing up in a small town, we used to have Thursday markets in outskirts. Local sellers as well as sellers from nearby villages would come to sell their stuff – vegetables, groceries, home decor, kitchen utensils and almost everything one needs in a town. Later, I realized that all the towns had dedicated days in a week for setting up markets. “Setting up markets” is what marketplaces do.
After an unsuccessful attempt at setting up a marketplace (Eduflix) as well as working with a successful marketplace (Flipkart), I have realized that there are three very important things needed to set up marketplaces.
Liquidity implies there is enough supply in the market to meet the demand and vice versa.
Setting up a day in a week makes sure all buyers and sellers come together on a single day and generate enough “liquidity” to make it interesting for buyers as well as sellers. Spreading thin across the week would result in lower choice or unavailability of required merchandise for buyers. On the other hand sellers will be left with unsold inventory. By bringing liquidity in the markets, marketplaces remove the inefficiencies from the markets as well as add value to both the buyers and the sellers. Thanks to those wise men who found this “liquidity” hack to create weekly marketplaces. Some marketplaces also leverage geography to generate liquidity – they gathers buyers and sellers together at one place (malls, commercial streets etc) to generate sufficient demand and supply.
Lets move to the Internet. The concept of marketplace fundamentally aligns with Internet (which itself is a marketplace in one sense). And similar to physical marketplaces, liquidity remains the most important success criteria of any marketplace. On internet, network effects drive the liquidity. Travelers visit TripAdvisor because it provides trusted reviews from real travelers, while real travelers prefer writing on TripAdvisor because most of the travelers visit TripAdvisor. The same logic applies to all the social networks including Facebook. Imagine logging on to Facebook and not seeing any update from your friends (something that happened with Orkut) or booking a cab from TaxiForSure (or much hyped Uber) and no availability?
We can safely conclude that “liquidity” is the single biggest contributor to the success of a marketplace. What drives liquidity? This is a million dollar question or rather a billion dollar. There are some usual tricks to drive liquidity in a marketplace, however, such tricks don’t apply to all marketplaces. Here are some such known tricks
Fake it before you make it
Reddit founders created fake accounts to seed the content. Even Paypal faked it by creating bots to buy from sellers and insist on paying through Paypal. You can find more examples here.
Start as a one-sided marketplace
Marketplaces need buyers and sellers, however if marketplace can be seeded either by one buyer or one seller, one can get the ball rolling. I cannot think of any marketplace with just one buyer and many sellers except for (may be) government buying from multiple sellers in a marketplace (FCI procures from multiple sellers in the market). However, there are many examples for marketplaces starting with a single seller, building consumer traction and then opening up to multiple sellers. Both Flipkart and Amazon are examples of the same.
Get big shots as participants
This is more of a social proof approach to building a marketplace. Etsy leveraged founder of Crafster as explained in this Quora post. LinkedIn created and aspirational brand by starting with successful and influential friends of Reid Hoffman (How LinkedIn got its initial traction). Similarly StackOverflow was promoted by influential founders Joel Spolsky and Jeff Atwood who had huge following on their blogs.
Leverage the existing networks
Lot of niche marketplaces started leveraging the liquidity of Craigslist, AirBnb being the most prominent. And many others started selecting verticals from eBay. On a different note, lot of niche marketplaces are being formed by unbundling of services from large and generic marketplaces.
There are many more liquidity hacks (just search on google) but every marketplace solves a different problem and these cannot be applied to all marketplaces in generic way. The key is to have absolute clarity on customer-needs marketplace is trying to meet and devise the hack accordingly.
Some more examples –
The problem of marketplace is not completely resolved after solving for liquidity. The second most important thing after liquidity is managing the quality of service of the marketplace. Liquidity drives the marketplace but quality helps it stay relevant. And marketplace rules (as defined by policies or algorithms) help in maintaining the quality.
Google’s page ranking algorithm maintains the relevance of the content you are looking for. If it fails, you would lose the trust with the search result and move to another search engine. And so would content writers start optimizing their content for another search engine. Similarly Facebook uses edge ranking algorithm to show what you see on your feed. In spite of the complexity of the algorithms, they simplify the interpretation to content creators to create meaningful and engaging content. This simplification is done using simple rules (e.g.,google, Facebook ). These apps are so good that one never cared to read the rules.
Similarly, stock markets are governed by very complicated rules and policies for traders (check BSE india for instance). However, i can say that very few people have actually gone through these details. Most of the traders / investors would know may be 5% of simplified rules that might be applicable to 95% of the transactions.
E-commerce marketplaces also define the rules in terms of various policies like return policies or payment policies. These rules make a marketplace as managed marketplace. Some marketplaces are going extreme when it comes to managing the marketplace, creating rules that make marketplaces almost homogeneous experience no matter who is the seller (the new marketplaces). These are almost on the verge of being aggregation services than being marketplaces. It is very hard to say whether Uber is a marketplace or just an aggregator. On the other hand, open marketplaces leave a lot of levers for differentiation for sellers.
Most of the marketplaces fall in between open marketplaces and aggregators. Some use “libertarian paternalism” to nudge participants for desired behavior.
Whatever be the case, these rules define the marketplace. These rules define what is allowed to sell, how transaction occurs, what happens if transaction fails and so on. I see these rules are no different from rules of any other game. Participants play the game following these rules to win. And that’s why, designing a marketplace is no different from designing a game. The rules of the game drive the quality of the services on the marketplace and also govern the engagement levels of the marketplace.
Participants succeed when a transaction happens (buyers succeed in buying desired product at desired price while sellers succeed in selling).
The third problem is relatively simpler. While rules of marketplaces define it but you need tools and capabilities to enable participants to follow these rules. The third problem is just about building the platform to enable the liquidity and gamification of marketplaces. Platform provides capabilities to list products, enable transactions and fulfillment, generate feedback mechanisms through reviews or ratings, avoid fraud etc. The value transaction is not possible without this platform. For an ecommerce marketplace, an order management system between buyer and seller is a platform and so is the actual implementation of ratings and review system.
1. Marketplaces need liquidity to generate value
2. Marketplaces are defined by rules that manage the service and engagement levels
3. Marketplaces are built on platforms that provide capabilities to generate liquidity and follow rules
Here are some examples of some (successful) marketplaces
|Marketplace||Value emerging out of liquidity(not comprehensive)||Rules of the game (some representative examples)||Platform capabilities(some representative examples)|
|Relevant search results||Generate engaging content, Search using keywords||Search Engine|
|Find what are friends sharing||Add friends, Share, Like||Social Graph, Feed|
|What is the latest?||Update in 140 characters, Follow People||Social Graph, Timeline|
|Resume of everyoneConnections||Update your profile, Connect with people||Social Graph, Profile, Content|
|TripAdvisor||Discover places||Write reviews, Upload pictures||Ratings and Reviews, Fraud detection|
|Stock Markets||Trading of listed stocks||Bid for stocks to buy or sell, Settlement in T+3 days, Circuit filters at 20%||Stock Exchange, Settlements, Fraud detections|
|Front page of the internet||User generated news links, Votes promote stories to the front page||Content Sharing platform|
|StackOverFlow||Get answers to your tech questions||Questions and answers are voted by the community, Users earn reputation when people vote on your questions or answers, The person who asked can mark one answer as accepted||Q&A platform with voting|
|Quora||Learn / know from others||Be nice and respectful, Make a page more helpful (Quora’s rule are slightly vague but they make up for it by imbibing the rules in user’s subconscious mind. Heres link to Quora policies)||Q&A platform with voting|
|Über / TaxiForSure||Connects you to a cab||Book from point to point, Cancellation charges||Mobile App for Booking, Driver Assignment, Cab tracking|
|eCommerce (Flipkart / Amazon / eBay)||Product Selection, Low Prices||Buyers can return products, Cancellation charges, Shipping policy||Order Management,Product Listing,Ratings and Reviews|
I think these are the top three education technology trends that need attention (short term perspective for 2 to 4 years) –
In year 2012, we saw a deluge of online courses offered by Ed Tech companies like Coursera, Udacity and edX. The number of students enrolled in these courses is a proof how online education is in great demand across the world. However, of the millions of students who enroll for online courses, only a small percentage of students actually complete the course. Coursera founder, in an interview last year said that courses at Coursera have retention rates of 7% to 9% depending on the course. The retention rates are of similar order or lower with other MOOC providers. Very soon, we would see solutions coming out to solve this problem and hopefully see improvement in retention rates. Some attempts would be in form of providing more structured education around MOOCs, especially in countries like India. We would also see some startups focussing on bringing the web product principles and improving the engagement of courses offered by employing personalization, gamification techniques etc.
Content plays a key role in education but the methods currently used in online education are still old and somewhat linear. Going forward, we will see a lot of innovation happening in how education content is presented to students and how it can be made more engaging. One good example from year 2012 is Edmodo, that is bringing social aspects in the way content is consumed with more than 19 million students and teachers on board. We might also see startups coming up with technologies to bring more interactions in video lectures and other rich media. The core learning experience would depend largely on the way education content is delivered and consumed online.
Mobile is increasingly replacing PC for lot of activities including education. In addition, higher penetration of mobile in some countries makes it a preferred medium over PC. For instance, in India with population of 1.2 billion, there are just 15 million broadband connections but more than 850 million mobile connections (source)
The learning experience over mobile is still in infancy and in future, we will see a lot of attempts in improving the same. With the changing perception about mobile usage for certain activities, education would be a key contender and we would see Ed Tech companies working on mobile experience.
Other than these, I also think we will increasingly see more “teacher” involvement in EdTech instead of just bunch of techies solving education problems.
It has been more than two years I quit my job and started my startup journey. One year back I had written this post – Lessons Learnt As An Entrepreneur For One Year. Since then I have learnt many more lessons and I thought it would be good to revisit and write down all the lessons. So here they go –
Looking forward to learning more in coming years.
When it comes to product design, there are people like Steve Jobs and then there are rest of us. Product design is mix of art and science. For lessor mortals (like me), science plays a bigger role in providing the framework for product design. There are many existing frameworks that have helped me immensely. Here I am putting down my thoughts based on my experiences and ideas from other sources.
Going back to first principles, a product is a product only if there is a user. So product design has to start with a user. Two fundamental questions to ask
The first questions is the most fundamental question and analogous to what Peter Drucker said about the definition of the business – ‘The purpose of the business is to create a customer’. Well, the purpose of the product is to create a user. Given that we know so little about human beings, answering these two questions is not so simple. The most common mistake, we do here is that we assume something and fool ourselves that we know the answer to these two questions. And since we are rationalizing species, we figure out many justifications to rationalize our assumptions. The better, and less risky, way is to create a hypothesis – with a promise of testing it before moving on next steps.
[This is the most frustrating part I have experienced in the product design cycle. Some call it idea-searching phase. Most of the user needs or problems cannot be just thought of. And I have seen many people, including myself, spending many hours brainstorming about that right idea. One of the suggestions from Paul Graham (How to get startup ideas) is to think about problems faced by oneself. Or problems you have seen firsthand. Another problem is that at times you have to imagine the future, say 5 years from now, and imagine the problems faced by your user in that world. In hindsight – how would you have come up with the idea of iPad 10 years back?]
How do we test the hypothesis? The most logical way is to ask the users. But unfortunately, it does not always work (it took me a venture to realize that, fortunately I did not invest much time and effort to it). Users are human beings and they are complicated. So if you ask them “Would you like know crop prices on SMS”, they would say “Yes”. “Will you pay for this service”, “Yes”. And then you create an awesome(?) product that nobody uses or pays for. Thats when people say, you should listen to your customers and listening is not about just hearing what they are saying. It is an art to figure out what customers are saying and this might be mastered with practice. But here we are trying to simplify this process using scientific methods. This course on Human-Computer Interaction on Coursera has a lot of tricks on customer needfinding.
One of the non-so-smart-ways to test it out is to actually developing the product and try it out with the real users. And that how we are going to do it. But intelligently. How? We will create a minimum viable product that users can try and pay for. Payment need not be in terms of direct money transaction. If a user
spends invests time in using the product, keeps using it and tells about it to friends, that is a kind of payment. It is up to you how you define the payment (see point 6 – Product metrics). So we move to the next question to ask.
MVP is easier said than done. Once thing I need to remind myself is MVP has the word “minimum”. In some cases even a landing page with right messaging or product screen shots should be enough. In others, we might need a decent prototype to show it to users and test the user experience. Or going further, our hypothesis might also test whether user pays for the product and hence MVP might also mean collecting cheque from the user.
However, in all the cases, one thing is common. We need to come with “minimum” set of functionality the product can do so that we can test our hypothesis. Sometimes there are multiple hypotheses to test and MVP also means to cut down these and test only the most important and risky ones. For instance, if the core value of a test preparation company is adaptive learning, the set of important hypotheses can be –
1. adaptive learning is effective
2. users will understand this and pay for it
And hence these will be the first ones to test. Next step is coming out with minimum set of features to test these. Some hypotheses can be extremely difficult to test [like the example we have picked] and designing the feature set and user experience can be a daunting task.
Even when you are convinced that the product needs the real needs of the user, it is always very easy to make a scrappy product that the user will not use. In fact, it is extremely hard to create something that user would use – and continue using it.
If it is improvement over existing product, your product needs to be 10x better than the existing one. Because there are two things always against you. a) Users resist discarding the products they are using and 2) Users resist to try new product.
On the other hand, if your product is fundamentally first one, the onus lies on you to convince your user about the need for such a product.
In both the cases, a behavior change or habit change is required. And designing new behavior is not really easy . But again, for non-Steve Jobs kind of people, there are frameworks to study and apply selectively (Notes on Behaviour Design).
Going into further details, I would go through the following checklist
Is the product value clearly visible to the user? How is it going to help the user? To what extent?
How does user start using the product? Is there a onboarding process or a starting plan? How easy it is for user to try the product?
What are the behavior changes required? How is the product tackling those changes?
How easy is it to use the product? Is it giving enough liberty to make mistakes? How much does user have to think before using the product or while using the product?
Does it give continuous feedback to the user? Is there social proof about using the product?
Had penned down some of these sometime back (7 Questions To Ask While Designing New Consumer Products)
There are two reasons to measure the metrics – to test out the hypothesis and to improvise.
Metrics give well-defined qualitative and quantitative facts to answer the following two questions
1. Is the hypothesis correct?
2. How to correct / improve the hypothesis?
If you are designing product without leveraging the data, either you are shooting in the dark or are just too good in understanding the consumer behavior and designing for them.
Again, defining the right metrics is very dependent on the type of product it is. In any case, one need to define set of numbers that can measure these metrics. Some usual metrics for software products
2. user activity
There are many others. Here is a great presentation from Dave McClure (Startup Metrics for Pirates)
One can leverage effective tools like A/B testing or multivariate testing to get more meaningful data.
It is highly unlikely that we will get the right product the first time. And this is where the science takes over from the art. The lessons learnt till now can be ploughed back to generate better ideas. This neat figure from the book The Lean Startup explains everything.
Good products never get completed. They keep improving – by providing more value or better user experience.
I think all the sexy work in product design end in the first two points. But the most dirty work starts when we start productizing. Productizing needs testing your product for all the corner cases, managing the product workflows, creating ancillary stuff around the product, packaging, versioning, support and many other non-cool things. Heres what I wrote while having such an experience – Lessons From Productization
A product is just a project before it is productized. It’s that last 20% of the work that consumes 80% of the time in product development.
One of the best ways to find the early adopters is to simplify the problem so that the target market becomes very small. Analogous to MVP, we should hunt for MVM – that is Minimum Viable Market.
The ideal cycle would be as follows:
1. Discover the MVM
2. Crack it with MVP
3. Increase the scope of MVM
4. Crack it with new MVP
5. Go back to point 3
Again it is easier said than done [and I have not succeeded in doing this yet]. Be it LinkedIn, Quora, Facebook or AirBnB, this is how they have done it. LinkedIn & Quora hacked the inspiration value in the product by first going to successful and renowned people (friends). Facebook started with a single college network. AirBnB started with letting out their own apartment.
Check out this topic on quora to read about more companies and their inital traction – How Did X Get Traction? Questions about how companies got success early in their history.
To write the story in short, all the above points answer these 3 questions
1. Why? Point 1
2. What? Point 2,3
3. How? Point 4, 5,6,7,8
I think it is very important to start from “Why”. It sets the vision of the product. I also think there is no unique process to design good products. On the other hand it is still possible to design suck-y product even after using hundreds of frameworks or checklists. It is important to be ready to fail.
To end the long post, check out this video from Simon Sinek: How great leaders inspire action
[thanks to Ashok I for reading through the draft and proving the feedback]
Few days back my three and a half year old daughter asked me what is a startup. This question got me thinking about an answer she can understand. And here I am preparing to answer her question through one of her favorite stories.
Once upon a time on the banks of river Narmada, there was a village named Vedeshari where everybody was unhappy. All villagers were unhappy because of a crocodile who lived in the river. Whenever women went to the river to fetch water or wash clothes, the crocodile would scare them away. Even children were not able to swim in the waters lest the crocodile attack them. The crocodile had mastered the art of taking villagers by surprise and attack them. The things were out of control.
One day all villagers gathered together and decided to present their problem to Vakil Saheb, the most respected person in the village. Long time back he used to be the Sarpanch of that village – the highest decision-making authority. He listened to villagers problem and promised them to come with some solution in few days. His granddaughter, a wise girl who was studying in Bombay and visiting him during her school holidays, overheard the problem of the villagers. She resolved to help her grandfather and the villagers.
The wise girl walked to the river and called out the crocodile. The crocodile had its moment of happiness when it saw its new prey and started swimming faster to attack the girl. But as soon as it opened the mouth to attack her, she put a stick straight inside its mouth and the stick got stuck in its mouth. The crocodile got helpless and started begging her to remove the stick. The wise girl said “I will remove the stick only if you promise that you will go far away from the bank and never trouble the villagers”. The crocodile agreed. She removed the stick and the crocodile swam away far away never to be seen. All villagers lived happily and thanked the wise girl.
Startups start with problems. You find a problem in the world and you solve it. This is called problem-solution fit. The crocodile in the river was a real problem and villagers would have done anything to get rid of it. Check 1.
But to grow your startup you need to see if this problem is big enough that you can replicate this problem-solution fit to a bigger market. So you answer things like how many villages exist that are suffering from this crocodile problem or when will this crocodile you scared away will start haunting the villagers again. This is when you are trying to find a product-market fit. Check 2.
But how will the wise girl provide this crocodile scaring services to 5000 other villages. She will have to build team, hire people, train them to stick sticks inside crocodile’s mouth and do many more things. The work has just started and now its all about executing (she has also started calling herself a CEO). Check 3.
But there is no startup without hiccups. Some smart chaps in the nearby village poached her employees and started to learn this art of scaring crocodiles. And they started to create new startups competing against her’s. Even the bigger businessmen from nearby cities started getting into the market of scaring crocodiles. The wise girl started thinking about creating relationships with village heads, create better and cheaper methods to scare crocodiles, offer better service to villagers, getting exclusive rights from village Panchayats etc. She wanted to get unfair advantage over her competitors. Check 4.
It was no longer a startup now. It morphed into a sustainable business and fledgling organization. Check 5.
She started looking at other problems (new startup).
PS1: The idea about sticking the stick inside crocodile’s mouth has been stolen from a chacha chaudhary comic book I read many years back.
PS2: The answer did not turn out to be interesting enough to my daughter. I guess I will have to work harder. Suggestions?
Lets take a look at some of the factors that determine success or failure of a startup in very early stages
In early stages, most of these tasks are done by founders.
In early stages, startup == founders. And when you say that you are working on a startup, the fact is that you are actually working on yourself.
Now most of the people are smart in most of the things but there are some critical things that they suck at. And the primary reason this happens is because we are uncomfortable in learning these things. Instead of generalizing, let me just put down some of these uncomfortable things I had to deal with in my experience as a founder. I still suck at many of these but important thing is that I am aware about this fact.
Asking for help: Recently I attended a leadership summit and one of the speakers was talking about his experience of turning from a CXO in a large company to an entrepreneur. When he was a CXO people lined up to meet him, but when he turned up an entrepreneur, he had to line up to meet people at very junior levels. It was not an easy thing to do. Similarly, when we were pitching our product to schools, some of them made us wait for hours before giving us time slots. Some times we were shown doors without even a meet. As Subroto Bagchi had put it sometime back – corporate executives are pedigree dogs, entrepreneurs are like mongrels. And its very difficult to turn from a pedigree dog to a mongrel. Asking for help is a big ego hurt!
Pitching: Have never been good with pitching. When I was working for someone else, pitching was not difficult. It was mostly about pitching new ideas to your team members. There was no time limit for pitching. And also the people you are pitching to, knew you very well. Most of the times it was actually other way round. Your boss is pitching you about the new projects. Or a candidate was pitching you in an interview to recruit him/her. In a startup, you are always pitching. You are pitching to your customers, you are pitching to investors and you are pitching to new hires. It actually needs a lot of practice.
Rejections: With pitching comes rejections. In fact just the fear of rejection made me a bad seller. Before I started Eduflix, I had worked on an interesting idea in education space. We had made a decent product but never actually sold it to anyone. The reason was that I was just too scared to call or visit customers. This time I crossed that boundary. Having a sales guy in my team helped (thanks to my cofounder). I got rejected many times. But I sold. Not just customers, we also got rejected by investors. I learnt that rejection does not mean that we are not capable or we are bad. There are n number of things that don’t work out. One has to live with that.
Doing things that you dont like: I hate paperwork. I hate doing repeatedly same things. I hate operational work. I hate processes. However at some point, these things need to be done – for sake of the company.
Changing domains: From Microelectronics to software engineering. From embedded systems to internet and mobile. From technical marketing to product marketing. From Verilog, RTL, simulations to Python, Django, Apache. From managing people who are coding to actually coding self. From B2B to B2C. Changing domains has been the easiest thing to cope with. Being a founder has meant unlearning lot of things learnt in the past and learning new things in completely different domains. I am sure two years from now, things that I will be dealing with will be completely different.
So the next time if I say that I am working on my startup, mostly it would mean that I am working on myself.
Recently I got a chance to see a very interesting lecture by Dr. BJ Fogg on Behavior Design. He is Director at Persuasive Tech Lab, Stanford and runs tinyhabits.com. On the other hand I have also been following Nir Eyal’s blog and his concept of Desire Engine. Here I am trying to do something I usually not do – that is, write down some notes and try to compare these two different models. All credits for this post goes to them, all mistakes are mine. It would be even more interesting to try bringing in perspective of “The Power of Habit” by Charles Duhigg – a book I am currently reading in these notes. Maybe Later.
My interest in behavior design comes from designing new products. Whether we are designing a web application or a mobile application or a physical product, we aspire to change the user behavior in some manner. And above all, we want to inculcate habit in users to use our product. And heres where behavior hacking starts [Hacking has been the buzzword lately from program hacking to growth hacking to now behavior hacking].
1. Types of Behavior changes
There are 15 ways behaviour can change. Here is the grid that Dr. BJ Fogg puts down to simplify the behavior design
Now for each type of behavior change, we need a different strategy. And according to him, a strategy befitting one type of behavior change might be completely different from the other. If he is right that this grid makes our life a lot easier by focussing on one type of behavior change or set of behavior changes for designing products. Another interesting point is that sometimes, one may want to move to a particular behavior change with a two-step process (eg. first going for Span Behavior to Path Behavior)
2. Motivation, Ability and Trigger
Behavior change is initiated by a Trigger and there are two things that determine whether user pulls the trigger – Motivation and Ability. Let me come up with a simple example – Lets say a user is looking to buy a smartphone (motivation) and somehow lands up on the relevant webpage (ability), she presses the call to action button (trigger). As a product designer, one’s job is to maximize the motivation to use the product, make it extremely easy to use the product and design an appropriate trigger. Dr. Fogg puts this in a very nice model as shown below (from his website) –
The point he is trying to make is very understandable – For behavior change to occur, one has to be above the Activation Threshold. A good user experience design can make up for low motivation and that is why user experience design is one the most important thing in product design. On the other hand, if motivation is too high and even when behavior change is hard to do, a trigger can lead to behavior change [to use the product]. An anti-UX guy can think that one can always build products that have high motivation value without an easy way to use them. Here comes the third point.
3. Motivation Curve
Practically speaking, our users and human beings and their motivation does not stay the same forever. For instance, a student who is preparing for an exam goes through ups and downs with his motivation levels to get good marks. So if your product is hard to use, the trigger might not always work. And this might hamper the habit formation – the most important thing we want with our products. The motivation curve can vary across people and the behavior change solicited. The point is that with Hard to use product or bad user experience design, one can risk product adoption in lean periods of motivation. And it is difficult to change habits if user goes on and off with the product.
4. Tiny Habits
Dr. BJ Fogg further suggests a way to make behavior change “Easy to do”. This is what he terms Tiny Habits. In his words – “I created a new way to tap the power of context and baby steps. Over 6,300 people have since joined in. The results are the best I’ve ever seen in any program.”
My understanding of this is that desired behavior change can be broken down into mini behavior changes with set of contexts around that can nudge one towards these mini behavior changes. From product design perspective, we can apply it in many different ways. One way clearly I can see is that instead of shoving off a full blown product on the face of the user that require GreenPath change [Do new behavior from now on], we start with simpler things that require smaller behavior changes.
Nir Eyal’s Desire Engine is different to some degree. His examples relate more with web products. These two figures (from his website) describe his model.
It starts with a trigger. External or internal trigger. Habits are created when internal triggers become part of routine. And internal triggers are formed with frequent external triggers.
Trigger initiates action and it depends on two things whether action succeeds – motivation and ability.
I think these two points are same as the behavior model of Dr. Fogg.
3. Variable Reward
Nir Eyal’s point is that a feedback loop with predictable response does not create desire. The expectation of a reward to certain action create a dopamine surge but if there is variability in reward, the effect is much more.
Once user is in the action, some kind of commitment improves the experience of the user in the next usage cycle. Although he does not mention it, I interpret it similar to what Robert Cialdini talks in his 6 principles of Persuasion – “If people commit, orally or in writing, to an idea or goal, they are more likely to honor that commitment because of establishing that idea or goal as being congruent with their self-image.” Commitment can be in any form – talking or endorsing the product or paying for it.
I think both the models start with the same three elements – Trigger-Motivation-Ability – that initiates the product usage or behavior change.
However, the two models diverge after that while dealing with enforcement of habit formation. While Nir Eyal talks about variable reward and commitment as two important steps to complete the desire cycle. This desire cycle is then frequently presented to users with improved experience and thus creating an internal trigger and hence habits. On the other hand, Dr. Fogg suggests tiny habits with the power of context to lead to bigger behavior change.
I would love to discuss any other such scientific models we can use to design user behavior.
Indian Education sector is hot. We see innumerable startups popping up all around us. I wouldnt be surprised, if stats say that there is one EdTech startup per day. And I think the trend has been similar in last few years. But we havent yet seen online education taken off in India. On the other hand, we are seeing lot of action in online learning in higher education in US. Be it massive online open courses like Udacity, Coursera, EdX, MITx etc or informal courses at K12 like Khan Academy – we have been hearing a lot about success of these programs. There is also lot of action on collaborative learning and lms front where companies like Edmodo, Coursekit, Piazza etc are growing fast.
Why havent we seen any success story in India so far? I do not know the reasons but let me try to list down some possible reasons.
1. We are not ready yet for online learning? There are some 100 million+ internet users in India. But when it comes to usage of India, learning is not really the priority of these online users. Online learning competes with entertainment, social networks, ecommerce, news and many other things. In addition, learning is a serious engagement that needs some good amount of time allocation. So although, we say that there are so many internet users in India, and out of these there would be some percentage of students online. But how many of them really get through all other distractions and sit back for learning. I think in India we are still in those lingering stages where students are yet to commit themselves for online studies. Just a clarification, joining an online portal or discussion board in not what I count as serious online learning.
2. Investment ecosystem is absent. Coursera has secured more that $22.5 million with a model where they are yet to think about monetization. Edmodo has raised more than $40 million. And here again, there was no monetization model, though things might have changed with their platform model now. There are many other examples – Code Academy, Knewton, LearnBoost etc. We have not seen many such stories in India. Companies like Educomp, Everonn etc have raised lot of money but they are more of an infrastructure/ content stories. Education+Internet is missing. To be fair to investors, maybe they believe in point one above or may be they havent found teams that can execute like some of the american counterparts have done.
3. The right product is missing. I think we are yet to see an online education product (or service) with right user experience that is suitable for Indian students (specially K12). Some of the products are half-baked products released too early to be firsts in the market. Take the tablets for example. There is a deluge of 7 inch tablets from many companies (I can count at least 10 of them) that promise bundled K12 content along with the hardware. Take the best of them all and just try it out, you will know what I mean. Also consider other products like online streaming classes, or factory made animated content available from tens of companies. It is understandable that these companies are trying to crack the market and some will be successful. But in the long-term, things act against because online learning ultimately looses trust from parents, who pays for the product and student, who is the consumer. Scrappy products will make money in the short-term but will lose out in the long run.
It would not be fair to compare online learning with e-commerce. But if we look back 6-7 years from now, we were facing something similar in e-commerce. There were too many companies around, none making a real mark in the market. But then, suddenly something changed – due to market dynamics or changes brought by the leading companies today – and then we saw this gold rush in e-commerce. Thereafter, imitators and laggards followed.
I just like to think, that one day, things will change, this jigsaw puzzle will be solved and some company or set of companies will change the dynamics of online education in India.