Product leaders sometimes, struggle with the big question of whether their market hypothesis, when translated to minimum viable product (MVP) will achieve the product-market fit eventually or not.
They burn their grey matter cells, contemplating whether to scale the MVP to the next set of features imitating the competition or to quickly pivot to a new futuristic product idea, which can achieve them a unique competitive advantage and thus, the product-market fit faster, given the constraint of time and resources.
After all, it is all a game of timing and agility in the competitive market.
Move fast and break things. Mark Zuckerberg
Let me walk you through a story of an interesting pivot from my past entrepreneurial journey at GoodHealthapp.
Incorporated on 25 July 2019, GoodHealthapp (Three Comma Labs Private Limited) started building an app for doctor-on-call and ambulance-on-demand for Indian users, given the data in India that, the doctor-population ratio is 1:1300 and the lack of emergency care in India, providing an avenue for disruption in the healthcare sector through digital innovation.
The hypothesis was that once the doctor on call and ambulance routing technology disrupts the above uncatered and underdeveloped market, the profitability will eventually happen from the economies of scale in India even with zilch unit economies of low ticket size.
The unique Indian healthcare challenges at this scale paired with the above hypothesis and the strong founder backgrounds prompted YCombinator to accept it in its accelerator for Winter 2020 batch.
The MVP to test the hypothesis was not a full-fledged Android Application, but a simple web-based PWAs, which was installable and usable on any mobile device with a low turn-around time of development, cost-effective in terms of time, resources and even, skills (web development).
After iterating fast on the MVP PWA, GoodHealthapp went ahead to onboard 1000s of users and even, did pilots and partnerships with start-ups like Avail Finance and Colive etc.
But later, even after onboarding 1000s of users, GoodHealthapp Monthly Active Users (MAU) and the revenue were stagnant we were not growing fast enough.
We realised we will die soon reaching that dream scale of profitability.
Grow fast or die slow. Mckinsey Insights
Those seasonal users were not bringing any revenue or any new users (the Practo problem).
Realising and learning the issue of being a seasonal startup, GoodHealthapp quickly tried to test out another hypothesis in B2B space to provide doctor-on-call and ambulance-on-demand bundled with insurance packages for other small-scale enterprises and start-ups.
GoodHealthapp bundled the doc-on-call, ambulance-on-demand and mental wellness packages with the group health insurance packages from ICICI Lombard, Religare Health Insurance, Chola, Bharti AXA, Tata AIG and even, Third Party Administrators (TPAs) like Paramount Health Services.
As per IRDAI regulatory requirements, an Insurance Broker License is required to directly sell insurance. Also, a broker or a third party without a license has to mandatory provide multiple insurance offerings for comparison to the end customers like Turtlemint.
Hence, to enter the insurance space with this regulatory loophole, GoodHealthapp started providing multiple product offerings with the mandatory bundling of its digital HR benefits management SaaS platform, doc-on-call services, ambulance-on-demand services, mental wellness packages and even, discounted diagnostic tests through a partnership with Thyrocare and pharmacy discounts through a partnership with Apollo Pharmacy.
After entering the B2B market, GoodHealthapp acquired several business and start-up clients through the start-up network of YCombinator and Elevation Capital, which went ahead to fund an undisclosed amount in its seed round.
So, the new hypothesis was validated based on consistently growing revenue in a different vertical due to business customers through bucket testing.
Sales Cure All. Know how your company will make money and how you will make sales. Mark Cuban
And thus, GoodHealthapp pivoted to employee wellness and insurance platform for other startups like Vahan, Wakefit etc. from being an online consultation platform like Practo, which is even still struggling after its $55 million Series D raise in 2017.
GoodHealthapp later, went ahead to integrate with Humar Resource Management System (HRMS) SaaS startups like Qandle, 247HRM, Kredily etc. to envision the dream of becoming Zenefits (the YCombinator Winter 2013 batch and thus, the pivot inspiration from the accelerator) of India, managing employee HR, benefits, payroll etc for SMBs.
Next, GoodHealthapp joined forces with Clear, a tax-filling potential Indian unicorn SaaS as its exclusive insurance partner to sell GoodHealthapp employee health benefits offerings on Cleartax platform by building an embedded tile on Cleartax dashboard.
The embedded tile used to redirect Cleartax customers to GoodHealthapp custom employee health insurance and wellness offerings and thus, help companies and SMBs to avail tax benefits directly on Clear tax filling software after making the group health insurance purchase on GoodHealthapp, a very well-strategized partnership indeed.
The business customers almost doubled after the partnership soon and the demand for other insurance offerings like group accident insurance, inventory insurance etc. started pouring in.
Later, Cleartax sales and channel partners also got on-boarded on GoodHealthapp channel partner platform to start bundling GoodHealthapp offerings, pitching and selling them to SMBs and entrepreneurial India along with other Clear products like GST Billing Software, Invoicing Software etc. on GoodHealthapp channel partner referral program platform.
Seeing such growth and the disrupted insurtech sector, new players like Onsurity, Plum and Nova Benefits entered the market to imitate this concept post COVID pandemic and hence, followed GoodHealthapp hypothesis and the same solution approach based on competitor data insights.
Imitation is the sincerest form of flattery that mediocrity can pay to greatness. Oscar Wilde
Here is an engaging exercise to compare GoodHealthapp (incorporated on 25 July, 2019) and Nova Benefits (incorporated on 13 October, 2020) logos side by side to savour this interesting resemblance ;)
Nova Benefits Logo
May be not a co-incidence, given Saransh Garg, the CEO of Nova Benefits was in the founding team of YCombinator Summer 2018 batch start-up Prodigal and was in YCombinator network since 2018.
Onsurity ($16 million Series A raise in August 2021), Plum ($15.6 million Series A raise in May 2021) and Nova Benefits ($10 million Series A raise in September 2021) — all seem to be doing good now as competitors soon after GoodHealthapp’s last Annual General Meeting (AGM) in 30 November 2021 to shut down its operations.
It is better to fail in originality than to succeed in imitation. Herman Melville
However, the competition for such a niche insurtech market is fierce, where the revenue is from the brokerage margin, which is only 7.5% of the insurance premium charged to the end customer, which again gets split between the insurance brokers/TPAs as well as the channel partners.
Adding to the expenses is the cost of providing doc-on-call through part-time consulting doctors and wellness experts along with the salaries of the tech as well as sales resources eats up all the revenues, leaving very little margin for profit.
And thus, like other Indian startups, these insurtech startups are also, currently unprofitable and will take a long time to even, break-even and survive sustainably.
However, the tables can turn, when these insurtech startups start realising that their easily imitable Unique Selling Proposition (USP) is not the customer satisfying service through doctor-on-call, mental wellness packages or even, faster claim settlement concierge service or policy comparison portal like policybazaar.com, where all of these features and the service quality standards can again be copied and matched.
The real competitive advantage moat will be the Data and the ability of these digital insurtech startups to finally, be able to pivot futuristically to monetise that Data and become data-driven underwriters by mining the health insurance consultations and claims data using Privacy Preserving Machine Learning approaches like Federated Learning and Differential Privacy so as to eventually, enable the insurance players like ICICI Lombard, Religare Health Insurance, Chola, Bharti AXA, Tata AIG etc for insurance underwriting through sell-able APIs and thus, eventually negotiate more than marginal brokerage as an equal partner on the underwriting table.
Data is the new oil. Clive Humby
Having that self-learning information system will also, allow that insurtech firm to build an intelligent ‘financial infrastructure’ stack for insurance distribution in India for Banks, NBFCs, Brokers and even Retails with an Open pay-per-call APIs like Riskcovry over the top of that underlying system, which can automatically quote the most risk-free premium based on the input customer profile and background, thus completely removing the data information asymmetry in the insurance sector.
Implementing best practice is copying yesterday, innovation is inventing tomorrow. Paul Sloane
Only, the time will tell which insurtech will eventually stop imitating one other and differentiate itself with by pivoting technologically to embrace the AI future and eventually, completely capturing not just this niche group employee insurance and wellness market but also, the traditional insurance players, where there is a lot of scope for innovation.
The best way to predict your future is to create it. Abraham Lincoln
Thus, to avoid the Product Founder dilemma of when to pivot to a new futuristic product idea for gaining a competitive advantage in the market, the founders should adopt the scientific approach of inference.
First, start with a hypothesis of the market based on the customer problem anecdotes and corresponding data, then, figure out the right hypothesis testing approach like usability testing of a problem solving MVP, A/B or bucket testing, market analysis, competitor data insights and identify the corresponding metrics to capture the evidence for the product market fit.
In the above process, the ability of being cost-effective in terms of investment of time and resources for such a hypothesis testing based on data can be mastered through practice and experience.
The curious case of anecdote and data not matching for product-market fit!
Eventually, take data backed decisions, either from usability testing, A/B or bucket testing, market analysis, competitor data insights etc. Dive deep in the data, when the metrics and the market anecdotes differ and are not evident to establish the product market fit for your product, and then, identify whether to pivot or not to pivot.
It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts. Arthur Conan Doyle
To pivot, or not to pivot was originally published in Technopreneurial Treatises on Medium, where people are continuing the conversation by highlighting and responding to this story.