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[Published in NextBigWhat on May 19, 2014]
This blog post illustrates how products have used comparison and choice based user interactions to successfully reinvent consumer experience on mobile. The underlying concept is titled ‘Hot’ or ‘Not’, derived from the original website created by James Hong. ‘Hot’ or ‘Not’ is now used by many products including an accidental creation from an entrepreneur we all know very well.
Remember Facemash? – Facebook’s predecessor that asked visitors to choose between pictures of students placed side by side and decide which one was ‘Hot’ or ‘Not’. Facemash may have been a product of Mark’s intoxication…a joke…an experiment if you will. But as I see it, it could very well be a great product concept that can wow the consumer and exponentially increase engagement, especially on smart-phone devices. To illustrate this thought, let’s look at a few examples.
Tinder is a dating platform, which has used this concept and has been hugely successful. It lets you swipe ‘Liked’ or ‘Nope’ on images of women and men located close to you. So rather than answering a million questions on ‘Okcupid’ or ‘Match’ and relying on intelligent algorithms built by MIT/Stanford data scientists (who apparently understand dating), you just swipe on Tinder and get connected to people who have swiped ‘Liked’ for you as well. Simple, fun and it works!
What makes Tinder great and gives the application of ‘Hot’ or ‘Not’ credibility is the fact that it is absolutely frictionless. It connects people easily and instantly. Currently, Tinder gets 750 million swipes a day and makes more than 8 million matches. As compared to it, Okcupid, which is one of the most successful dating platforms, has 1 million daily users. Hence, far less matches when compared to Tinder.
Thumb is an app that lets you get or give opinions in real time. From asking people about their travel destination choices, to product preferences all the way up to soliciting opinions on love lives, Thumb transcends a host of categories. It quickly became an addition and a community before it merged with Ypulse. Though Thumb was not as successful as Tinder, it does represent the kind of exponential engagement ‘Hot’ or ‘Not’ type products concepts can derive.
Thumb reminds me of a show called “kaun banega crorepati” – the Indian version of “Who wants to be a millionaire?”, where the contestant can use a life line called the “audience poll” if he/she is unsure of the answer. And there are plenty of such situations, which are frequent in nature, where we need advice and we would rely on wisdom of the crowds rather than make the decision ourselves. Hence, presumably Thumb’s success was because the ‘Hot’ or ‘Not’ type product concept was applied to a simple real life problem encountered by every man and woman almost on a daily basis!
‘We heart it’ is an image based social network that has quickly grown to over 30 Million users serving 50 billion images per month. Users ‘Heart’ images that they love and put these images in their collections that are shared with their friends and followers.
‘We heart it’ is incredibly simple, yet a very powerful way for people, especially teens to express themselves – their personalities, feelings, preferences, opinions through images. Images based networks have existed for long (remember Flickr?) but they never achieved the kind of scale ‘We heart it’ has done. Secret to their massive and instant success – a simple application of ‘Hot’ or ‘Not.
Fad or science?
It is easy to pass this as a quirky fad. However, the concept of ‘Hot’ or ‘Not’ has deep routed scientific reasoning. For those who are familiar with market research techniques, would know Conjoint analysis to be a bedrock of research studies. The simple form on conjoint analysis asked consumers to rate and review products just like a lot of platforms on the web today. This was disrupted when CBC or Choice based conjoint came along and proved to be a much better alternative. CBC asked consumers to choose between different product or service concepts and say whether it is ‘Hot’ or ‘Not’. It was argued by scholars that CBC works well because that’s how human psychology works. It is natural and intuitive to choose, it is unnatural and much more difficult to rate. Also, the variance or the error in the latter was higher. For the curious souls, you can read about CBC here
‘Hot’ or ‘Not’ for Indian start-ups
Mobile is key to the growth of Indian start-ups. The mobile user is on the go, wants to be quick and fluid with his/her interactions with the device, does not like typing and is more visual. These aspects make it imperative for Indian start-ups to re-imagine their products for the mobile. Traditionally –
– Mobile products have been replications of web interfaces including the feature set and the sequencing of the user interactions
– The platform is not built around a single user input like a Pin, Thumb, Heart or Fancy. Instead, it is cluttered and asks users to do multiple things. For e.g. several buttons beneath an image asking the user to Comment, Like, Share and more.
This is where concepts like ‘Hot or ‘Not’ could help achieve a wow consumer experience and quick scale. – just like the examples illustrated in this post have done. Perhaps, soon we will see E-commerce sites moving to ‘choice’ from ‘browse’, Review/rating platforms giving up the age old 5 point rating system and new-age dating/marriage platforms innovating like Tinder.
If you think this article was ‘Hot’, feel free to write to me at email@example.com and/or visit the Lightspeed blog to leave a comment…Or just ‘Digg’ it.
[Published on NextBigWhat]
Your board should be an asset to your company, providing guidance and advice at critical strategic junctures, as well as functionally helping with executive recruitement, M&A and other liquidity options, and key strategic outreach into regulators, distribution partners, suppliers and customers.
In my opinion, the smaller the board, the better. When you start out with your company, perhaps there are one or two founders and an independent on the board, for a total of three. I have seen most boards at about five and some at seven to nine members. Six or above, in my opinion is too big and unwieldy to make fast and correct decisions.
In all the hubbub of starting and growing a company, it’s easy to overlook the creation of a strong and value-added board. Most times, the board consists of management (initially founders) and investors and remains that way for quite a while. But it can be even better.
I’ve seen independent board members help out a fair amount. So whether it is an empty seat set aside for an independent or no seat at all, I would recommend getting somebody onto the board soon. And constituting an ‘advisory board’ doesn’t achieve this purpose.
Some of the roles I’ve seen independent board members play are:
- helping resolve complex and difficult situations or stand-offs between the CEO and investors.
- providing a balanced perspective when management and investors may have drifted into extreme positions
- working closely with the CEO outside of board meetings to provide specific deliverables back to the board (eg compensation proposals)
- provide a sense of real perspective from a long and successful career in their industry
- serving as a mentor and guide for the CEO to enable the CEO to learn and grow in his or her role as a leader and manager
So, who should your independent board member be?
- Should have strong rapport with the CEO and not be just a ‘yes man.’
- Should ideally have a point of view/relationships/experience in an area that is currently under-represented in the senior team
- Should have a financial interest in the success of the company. Ideally would have invested their own capital into the company
- Has time to spend for board meetings and outside of board meetings with the CEO
- Is genuinely interested in seeing the CEO and by extension the company succeed
Some good posts & examples:
- From Brian Halligan of Hubspot: The Benefits of the Perfect Independent Board Member
- From Elad Gil: How to Choose a Board Member
- From Matt Blumberg of Return Path: Why I Love my Board
Have seen you seen independent board members play other constructive roles? Please let me know in the comments section.
(Source: Chiot’s Run)
[Published on Pluggd.in]
Founders of consumer businesses inevitably face the dilemma around when to start scaling their companies. Sometimes the decision is outside of their control, for example if their service starts to grow exponentially, but more often scaling is a deliberate decision and involves up-front investments to drive and support growth, such as filling out the management team, growing the sales and/or engineering teams, and increasing marketing spend. Because any of these activities result in increasing expenses and cash burn ahead of revenue or usage, the decision around when to scale is a critical one.
Our contention is that entrepreneurs should demonstrate product-market fit before investing in scaling up. In the Indian context, where new web services are cloned on a weekly basis, waiting to get to product-market fit can be difficult to do. Founders may feel pressured to scale prematurely, justifying this decision with reasons such as “it’s a land-grab” or “first-mover advantage”.
Scaling out prior to product-market fit can be very risky. In many cases, you have to be ready for a high-burn scenario – access to capital becomes a key constraint here, as evidenced in many of today’s ecommerce businesses. You may also cycle through lots of management (especially sales and marketing) if you haven’t got the product, value proposition and messaging right. And you may lurch around from product to product or positioning to positioning as the pressure to deliver financial results grows. All of this can distract the company from answering a critical question – do customers really value the product or service you are offering?
So, what is product-market fit? While there is no ‘silver bullet’ definition, we typically look for evidence that customers value the product or service offered by the company and engage in a manner that indicates that they cannot live without the product. For example, we look for signs of the following:
- Traction: Large and accelerating growth in monthly active uniques (MAUs) and daily active uniques (DAUs). Note the importance of the word ‘active’.
- Scalable customer acquisition: Ability to acquire customers cost effectively through scalable (and ideally organic or viral) channels
- Repeatability/Engagement: High amount of repeat visits from existing users and signs of ‘value generating’ behavior e.g. repeat purchases for an e-commerce site, songs streamed for a music service or community engagement for a social networking site.
- Virality: High k-factor
- An initial set of users who will pay money for what you have
Here are some examples from within our portfolio of companies that achieved product-market fit – along with illustrative metrics in each case of how this was measured:
- TutorVista: increasing length of stay / subscription and declining acquisition costs
- Itzcash: increasing organic transaction volumes
- Indian Energy Exchange: acceleration in trading volumes and number of participants trading on the exchange
- LivingSocial: Rapid viral adoption and repeatability of economics and customer / revenue ramp across cities
There are several different approaches or strategies to accomplish product-market fit – the blogosphere is full of wise advice from founders and investors on this subject (see below). However all these approaches hinge around a common core, namely proving that there is a reason for your company to exist before spending more money amplifying your message or building your expense base.
- iterating constantly, starting with a minimum-viable product (a la Eric Ries and Lean Startup)
- focusing maniacally on actionable metrics (a la Dave McClure and AARRR)
- keeping a low-burn with a small, nimble and technically-oriented team
- getting detailed feedback by directly observing users interacting with your product (a la Scott Cook of Intuit)
- clearly detailing a hypothesis on your value proposition and disproving and proving that through actual data
- making things people want (a la Paul Graham of Y-Combinator)
- optimizing customer sataisfaction, perhaps through tracking Net Promoter Score (NPS)
Once you have product-market fit, you have evidence of a strong value proposition for consumers, advertisers and other customers. This provides a foundation for a viable business model. Now you can – and should – scale.
[Published in Pluggd.in]
“The technology itself is not transformative. It’s the school, the pedagogy that is transformative”
– Tanya Byron, psychologist
As part of our upcoming founder-focused breakfast on education startups, I wanted to lay out my thoughts on the education space, which has proven to be a productive area for us through our investment in TutorVista. This post is focused on K-12 education businesses.
After Educomp and Everonn built large businesses over the last few years, many education-focused businesses are emerging, piping existing and new content into classrooms or homes using new technology platforms like web, cloud, tablet and VSAT. However, it is debatable if any of these businesses have measurably improved student learning outcomes.
Technology Adoption Lifecycle
Tech-enabled education businesses still have not crossed the chasm (they fall in region I and II above). In fact, of the ~80K private schools in the K-12 segment in India –only ~12-15% (# of schools doesn’t take into account # of classrooms per school, Educomp claim: 8000 schools) of them are using technology enabled solutions.
The key reason is that the perceived technology is being adopted by schools who buy those solutions that are vendor financed or paid for by the “early adopter” parent. To get to the main stream market (pragmatists, conservatives in the diagram above) a “whole product” needs to be stitched together that addresses the pain points of all the stakeholders of the education ecosystem effectively. Here are the pain points I see in the market:
- Parents pay for everything but still haven’t seen any impact of the solutions on the child. Simply a technology enabled solution can’t intrigue them for long
- Schools have benefitted from higher fees and more admissions with no investment. However with no measurable outcome, they have not been able to sustain high fee or any differentiation
- Students do not learn anything fundamentally different from their text books
- Teachers are negatively impacted by long execution lead times due to extensive teacher training
Though school as a distribution channel not only provides instant credibility but also a captive base of customers to the business, this channel might take time to scale since schools appear to be fatigued by a number of vendors offering similar solutions.
So how can a business create a bandwagon effect so that the product becomes a standard, a solution and a convenience?
Businesses need to have a strong value proposition by identifying the key intervention point (s) as well as by addressing some of the pain points mentioned above. Additionally they need to continuously innovate. They should:
- Make intervention easier by tapping areas such as designing student feedback platforms for teachers /parents, customizing remedial content and developing out of school learning aids through asset light platforms since these are relatively untapped opportunities. It is essential to have closer involvement of educationists, rather than just technologists, since educationists would help create products that blend with the core needs of existing educational setups.
- Design content which is easy to grasp, fundamental in nature and more interactive than text-book content. Elements of high quality animation or gamification makes learning more experiential and activity-based and hence more engaging for students.
- Figure out direct to customer (student/parent) “Edmodo”–like distribution channels to reduce friction in scalability.
- Provide affordable solutions to the school/parent. Although the parent is fairly price elastic, it is essential to cut across the affordability criteria for the ~80K schools in the country. The price can be a small percentage (up to 5%) of the school tuition fee or tutor fee depending on the distribution channel. Customer response/engagement can also be tested by giving the solution for free in the first 3-6 months of product launch.
- Develop simplified tech platform frontends so that the teacher/student doesn’t need much hand-holding. Should involve basic steps that can be easily understood by a non tech savvy person.
- Keep track of the key regulatory changes going forward since this space is unregulated. Introduction of CCE* (Continuous and Comprehensive Evaluation) is an example which has created new business opportunities .Some organizations such as Bureau of elementary/secondary education and CBSE, ICSE, IB, SSC, HSC, state education boards might be worth monitoring.
Potentially interesting areas for intervention (with examples):
- K12 curriculum: This is a relatively crowded space but requires high quality interactive content through scalable asset-light technology platforms (cloud/tablets/web etc.). Idiscoveri is doing some meaningful work in this space through non tech platforms.
- Student assessment/CCE*: These include adaptive learning methodologies with feedback, including remedial content so that teachers/parents understand the weak areas of each child. Additionally technology as an enabler can potentially improve efficiency of the teachers. Educational Initiatives is a relevant example in this space that resonates in my mind.
- Out-of-school tutoring: These solutions include self-learning interactive content/tutoring through tablets/web/cloud. Tutorvista, a known name in this space and also one of our erstwhile portfolio companies, was acquired by Pearson in 2011.
- Extra-curricular/counseling: Such models can be difficult to scale since this isn’t the basic requirement of the parent or the school, yet there is a possibility of building brands aimed at holistic development of the child. Edusports, a company that designs a K12 sports curriculum is one example in this area.
Though one might argue that the impact on the schools and the students would be more visible in the long term, there are a bunch of progressive schools such as Shri Ram (Delhi), La Martiniere (Kolkata), and Presidency School (Bangalore) etc. who seem to understand, appreciate and adapt meaningful products which should transform the pedagogy in the long term. As far as commercial schools are concerned they would follow suit once the models are proven.
[Published in Pluggd.in]
Several of our portfolio company founders and I have recently been debating whether to launch a new product/company quickly (and sometimes prematurely) or instead take more time to launch with a ‘fully baked’ product. The most compelling reason FOR launching early is to expose the product to real customers and begin the cycle of learning (and sometimes also to establish a first-mover advantage if relevant and important). The principal reasons AGAINST launching early are that you deliver a half-baked or imperfect user experience and worse, you risk failing to meet basic user expectations.
Through discussions with other CEOs it became clear to me that many entrepreneurs struggle with different variations of the same question. For example, while we’ve been debating this trade-off in the context of when we should launch a new company and how ‘perfect’ the product should be, other entrepreneurs whose companies are already in market wonder whether they should begin to scale-up aggressively or first invest in their infrastructure (provided they have validated product-market fit).
Clearly there is no generic answer to this question as many factors play a role – the nature of the business, competitive dynamics, user expectations, regulatory requirements etc. For example, Indian Energy Exchange (IEX), a Lightspeed portfolio company, operates a national, electronic market for power. The company’s platform is used by state utilities and industrial buyers to buy and sell power as well as ensure payment integrity and schedule power delivery. Given the company’s mission critical role in the power market, it is essential to launch with a pressure-tested product that works flawlessly at scale. However for many consumer internet or mobile companies that do not serve such mission critical use-cases, there is a strong argument to launch early with a minimum viable product and begin the learning cycle as soon as possible. The key question we’ve been debating is how early?
My current thinking is that entrepreneurs must focus on getting to market quickly with a lean or light-weight version of the product (note that this is different from an incomplete or half-baked product), PROVIDED that:
- The product supports the core customer use case,
- The company has a level of technical and organizational readiness that will enable them to iterate, innovate and improve the product post-launch rather than engage in months of fire-fighting because the product or service was launched prematurely and fails to meet basic customer expectations, and
- The company is ready to track user behavior, engagement, funnel metrics, cohorts etc so that iteration and improvement can be done in a data-driven manner – and the insight gained from an early launch can be actioned
Note that this does not require the product to be perfect or ‘complete’ but it does require that the limited set of features and functionality work well and support the core use case. For example, an online retail company need not have full product selection, support every payment method or offer a full feature-set on day 1, but it should offer a frictionless user experience and be able to accurately ship an order to a customer within a reasonable time frame. If the company has made appropriate investments in its organizational and technical infrastructure, it will be able to layer on additional products, functionality etc on a continuous basis post-launch and will be in a position to accelerate growth going forward. Flipkart is a great example of a company that did this the right way – by focusing on getting the user experience right and establishing product-market fit before aggressively investing in marketing to scale rapidly.
Conversely, a company that launches prematurely, simply to get to market quickly, runs the risk of demonstrating early success, only to have to pull back later in order to fix a long list of ‘bugs’. This can lead to unsatisfied customers, demotivated employees and a compromised competitive position. Worse, this type of company wont be in a position to run experiments, learn from its customers and make rapid product improvements.
Companies with purely ‘virtual’ business models such as social gaming or music streaming can launch even more quickly with very lightweight minimum viable products to help establish product-market fit. Once they see positive signs around traction, usage and engagement, they must prepare to handle scale prior to ramping usage. After all, what would have happened to a company like Instagram if the system buckled under the tremendous growth?
[Published in Pluggd.in]
I am speaking at IAMAI’s conference on Digital Commerce later this week in Mumbai. I thought I would put down a few thoughts here that I believe affect ecommerce in India as an industry.
There has been an increasing amount of debate recently around the sustainability of ecommerce companies in India. I believe that a key driver of sustainability is a sharp focus on long-term customer value and a deep understanding of customer metrics. Delivering strong value to customers results in high repeat purchase rates and low customer acquisition costs, while an analytical orientation enables companies to measure key metrics and take important business decisions based on real data.
Everyone understands intuitively that repeat customers are good for business. Yet very few e-commerce companies develop a deep understanding of customer behavior, measure and analyze key metrics and tailor their business strategy and internal focus accordingly.
Understanding the value of a customer – and how to measure it – is perhaps one of the most important questions for anyone running an ecommerce business. If you don’t know what a customer is worth, you run the risk of not knowing: (i) how much you should spend on marketing/customer acquisition, (ii) how much you should spend on customer support (customer service, fulfillment etc), and (iii) the levers that drive an increase in the value of your customers (and therefore the value of your business). Companies that don’t understand customer value may be able to grow rapidly, but this will be unsustainable over time, because the costs they incur to acquire, reacquire and support their customers may greatly outweigh what those customers are worth.
All e-commerce entrepreneurs I meet share a repeat customer metric (indicating an appreciation that repeat customers are valuable), but more often than not these metrics don’t reveal insight into customer behavior. Some examples include:
- “33% of the orders last month were from repeat customers”, OR
- “50% of the customers that bought last year bought again this year”.
OK, this sounds great, but what does it actually mean and how is this data actionable for the business?
Let’s take the first statement: “33% of the orders last month were from repeat customers”. Take a company that has been in business for a couple of years and during that time served over 200,000 customers. Assume that they currently serve 21,000 customers per month. So this statement means that 7,000 customers (or <4% of their cumulative customer base) in the month had bought at some point before. Is that good? Bad? What does it mean? What actions should be taken? It’s tough to tell because this statement is meaningless without more context.
Let’s take the second statement and apply it to the same company above: “50% of the customers that bought last year bought again this year”. This implies that 100,000 existing customers bought again this year. I think we would all agree that sounds pretty good. But is it actionable? What did they buy? How much did they spend? How often did they buy again?
To help answer some of these questions and drive specific, actionable insight for an online business, it helps to think of customers a little differently. On the internet, a customer is like a store in the physical world – you need to make upfront investments (acquisition cost on the internet; capex for a physical store) which will yield a margin stream in the future. Understanding the ratio of the upfront investment to the expected margin stream, as well as how you can reduce the investment and increase the margin stream, is critical. Just as the operator of a physical store thinks about time to break-even and pay-back, operators of online stores can do the same with their customers.
Once you accept this premise, you can use cohort analysis to estimate customer lifetime value. Cohort analysis tracks the behavior of a specific ‘batch’ of customers (for example the January 2010 cohort means customers acquired in January 2010) over time. You can do this for multiple cohorts as follows:
The table below illustrates the behavior of the January cohort, which is the customers that were originally acquired in January.
The next table indicates the order value generated by the January cohort.
What we see is that the January cohort of 1,000 buyers spent a total of Rs. 29L during the year. If this business has a contribution margin (i.e. shipped revenue less COGS and variable costs such as discounts, payment gateway, shipping & handling) of 15%, then the cohort of 1,000 customers generated Rs. 4.35L of contribution margin in the year or Rs. 435 per customer. Because the number of transacting customers as a % of the starting base has begun to asymptote in 12 months, you can project this forward and calculate lifetime value over 2 or 3 years (note, this is NOT year 1 value multiplied by 2 or 3). Lets assume the 3-year lifetime value of a customer based on this analysis is approx. Rs 800. This should become the maximum allowable acquisition cost you pay to acquire a customer in steady state.
Many of the most successful e-commerce companies in our portfolio achieve lifetime value to customer acquisition cost ratios (LTV/CAC) in excess of 3:1, which enables them to grow rapidly and profitably through aggressive marketing. Since acquisition costs can only be controlled to a certain extent given media costs, competitive dynamics etc, they do this primarily by focusing on customer economics, and specifically increasing: (i) frequency of purchase, (ii) margins, and (iii) order values (through effective retention marketing and initiatives).
Most companies that measure this data carefully allocate more of their resources to retaining customers and improving customer economics than companies that don’t. After all, it’s much easier to ramp up customer acquisition if you already have systems in place to maximize the value of those customers than it is to change the DNA of an organization that focuses only on customer acquisition.