SMB SaaS is hard. Getting the positioning right, increasing ACVs, controlling churn – it all becomes harder when your customer is a small business that is resource constrained & perpetually dealing with its own execution challenges.
Despite this, given SMBs are the most frequent early adopters of new products, the reality is that most startups tend to start mid-market. Though, in my experience, a majority get stuck in unfavorable economics of this customer segment & are unable to achieve breakout PMF.
So, what is the secret sauce founders can learn to effectively scale SMB SaaS? Hubspot is a great case study. I recently came across this SaaStr podcast with the HubSpot CEO Yamini Rangan, where she shared some of the company’s SMB strategy & learnings. Here are the key highlights:
Go after a large TAM: given the fragmented nature of SMB verticals, it’s really important to have a large TAM. HubSpot made the smart decision to transition from marketing automation to CRMs, basically going after Salesforces’s lunch.
Mid-market verticals tend to have open opportunities for startups as SMB customers are usually sandwiched between either buying a host of solutions & stitching them together or buying an expensive, enterprise-grade solution. In this context, I had recently posted a Twitter thread about how Zoho followed a similar multi-use case bundling strategy to position itself as an “operating system for SMBs”. This strategy works well as SMBs have a tendency to simplify their tech stack & procurement processes by buying multiple solutions from the same vendor.
2. Customers gravitate towards competitively-priced, mission-critical products: in times of economic uncertainty like today, SMBs tend to become really sensitive about budgets. Customers start asking tough questions internally around (1) where are they spending?, (2) do they have a clear path to getting enough value from the spend? and (3) can they do more with less?
Acting per this analysis, SMB customers are then likely to consolidate their tech stack to a handful of mission-critical platforms that are competitively priced & deliver the most value. This is the bar startup products need to cross while selling in this tough macro environment.
3. PLG-based distribution is king: to achieve break-out growth in SMB SaaS products, startups need to have the widest possible distribution. The front door needs to be big enough so that most people can come in.
For the first 8-9 years, HubSpot was mainly driven by a sales motion comprising Direct Sales & Partner Sales. Around 2016-17, in order to exponentially grow distribution, the founders made a counter-intuitive bet to go from sales motion to product motion. Today, HubSpot has a massive user base of ~1Mn WAUs to monetize off of.
4. A strong “free” product is key to PLG: One of HubSpot’s truly differentiated product strategies has been to offer a strong, full-featured free product. Rather than making a “free” product free just for the sake of it, they have focused on making it really valuable.
Some important benefits of having a strong “free” plan:
Drives high top-of-funnel growth & user engagement, improving the probability of monetization once the value is proven out.
Puts product org. under pressure to deliver enough features at the top, in order to maintain the competitiveness of paid versions.
Forces the product team to maintain a “consumerized” ease of use, which benefits all customers, free or paid.
Irrespective of whether your GTM is sales-led or PLG-led, a founder should never give up on the “free” plan as it’s key to keeping your product competitive.
5. North Star Metric should be Net Revenue Retention: NRR is the best health indicator of an SMB SaaS business given it represents whether or not: (1) you are retaining the customer, (2) you are continuing to drive enough value so they buy more from you and (3) you are protecting yourself from churn.
6. Don’t underestimate the value of a Partner ecosystem: once you reach a certain scale, PLG & Direct sales aren’t enough. A thriving partner ecosystem can be a strong GTM moat. Interestingly, a majority of HubSpot solution partners *only* sell & deploy HubSpot as a CRM, thus creating valuable network effects for the company.
7. In geo-expansion, less is better: PLG-driven companies will always have customers in many countries eg. Hubspot has 130+. But in order to deeply localize for elements like language, currency, customer support etc., it’s important to focus only on a few markets. As an example, HubSpot has chosen 7-8 markets to deeply localize their offerings in, based on factors like TAM, existing installed base, net ARR growth being seen & the company’s ability to serve the market locally.
While SMB SaaS can be a tricky business model, it compounds beautifully once the founders figure out its key levers, as HubSpot has shown.
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As a long-time student of Charlie Munger, I eagerly wait for his musings at the Daily Journal Shareholders Meeting every year. This time was no different! Here are some of my notes capturing Charlie’s wisdom at the DJCO 2023 meeting:
Importance of under-served markets in software
Both Munger & Buffet are big believers in moats. Having witnessed the natural creative destruction of even the best companies like Kodak & Xerox, they understand the power of competition & what it can do to long term returns of investors.
Munger spoke about how the software business of DJCO, which offers a solution to automate legal courts, is operating in a large yet unaddressed market that incumbent software companies hate. It’s an unsexy business that has long sales cycles & as Munger himself said – “it will be a long grind”.
However, these same reasons also limit competition in the space. Munger believes that this combination of a large, underserved TAM + low competition is likely to drive superior long-term returns, as long as DJCO shareholders are prepared to ride through the grind & hold over the long term.
In my view, this idea also has some interesting insights for venture investors in the enterprise software/ SaaS space. Too often, investors start chasing the hot market of the year without realizing that a space that is obviously popular will end up attracting disproportionate competition & investor $$. And as history shows us, too much competition in a market drives down returns for everyone.
Therefore, there is some merit in looking at startups going after unsexy or under-served verticals. These non-obvious nooks & crannies often hold the most potential for contrarian-and-right bets.
2. Holding is tax-efficient
Munger spoke about how he hates to sell his holdings as California would straight-up take 40% away in taxes. As he went on a brief rant about how California is driving businesses away with its tax policies, the underlying insight stayed with me – how holding securities over the long term is a brilliant strategy for tax efficiency. A simple rule that anyone from Berkshire & DJCO to common folks like you and me can follow in our lives.
As the likes of Robinhood have leveraged the excess liquidity environment over the last several years to create a generation of young day traders, many of them don’t realize how tax-inefficient frequent trading is.
3. #1 bias is denial
When asked what the #1 behavioral bias is, Munger said “denial”. And it’s so true. Often times, when the present reality is too brutal to bear, our brain tricks us into living in a delusion. While this stems from an evolutionary survival mechanism our brains have developed, taking major decisions under this denial state can cause havoc in our lives.
Proactively trying to see & live in one’s reality at any point in time is the best way to behave rationally. If one thinks of all of grandma’s wisdom handed down to us in popular sayings (eg. “live within your means”), they all urge us to recognize & live within our own realities.
4. Betting big when the right opportunity knocks
I loved this sentence from Munger – “What % of your networth should you put in a stock if it’s an absolute cinch? The answer is 100%”.
While I am positive that Charlie wouldn’t like this to be construed as a stance against diversification, which is important for almost all portfolios in varying degrees, the spirit of this sentence is this – a few times in your life, you will come across a no-brainer opportunity with massive asymmetric upside. It will happen very infrequently, but when it knocks on your door & you are convinced about it, go all in & bet really big. Over a lifetime, these bets will drive the majority of your returns, financial or otherwise.
If there is one thing that separates the likes of Buffet & Munger from other investors, it’s the mindset of betting really big when the odds are extraordinarily in your favor. During the meeting, Munger mentioned how Ben Graham made 50% of his money from just 1 stock – GEICO. Also, he illustrated the importance of power laws by sharing how Berkshire’s initial $270Mn investment in BYD (made in 2008) is now worth $8Bn!
Munger admitted to having used leverage to buy Alibaba stock in the DJCO portfolio. When asked why he violated his own rule (his famous quote being “there are only 3 ways a smart person can go broke – liquor, ladies & leverage”), Munger responded with another fascinating quote:
The young man knows the rules. The old man knows the exceptions.
Charlie Munger
The insight behind this is something I say a lot – context is everything! Rules & checklists are great for driving overall discipline & avoiding foolish behavior but as Munger demonstrates, it’s not wise to become a prisoner of your own rules. With experience, one should learn to spot exceptions & when the context is favorable, be bold enough to break the rules.
6. On long-term economic trends
While both Munger & Buffet generally hate to predict macro trends, Charlie mentioned a few interesting observations:
-Inflation is here to stay over the long run, given most democratic govts. globally have shown an ever-increasing inclination to print money.
-Most govts. across the world are going to be increasingly anti-business, with tax rates steadily going up.
-If one looks at economic history, the best way to grow GDP per capita is to have property in private hands & make exchange easy so economic transactions happen (the essence of capitalism).
If these trends are even directionally true, it makes sense to hold assets that can fight inflation (eg. stocks), as well as invest in a tax-efficient way, over the long term. Developing an investor mindset that can operate in a high-inflation environment will be important.
7. The playbook for success in life – Rationality + Patience + Deferred Gratification
When asked the thing that’s helped him the most in life, Munger said – rationality! Loved this line from him:
If you are constantly not crazy, you have a huge advantage over 90% of people.
Charlie Munger
To significantly improve the odds in your favor, Munger prescribes combining 3 things:
-Rationality (which is often, just doing the obvious)
-Patience (take advantage of compounding)
-Deferred gratification (live within means, save & invest)
Like most things Munger says, the above ideas are simple & profound, yet hard to consistently follow for most people as their biases come in the way.
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I recently tweeted a really interesting insight I heard from Mike Maples, Jr of Floodgate at a recent Draper University closed-door event:
This is so true, and a common mistake that founders & product leaders make while building new products. Looking back on my own startup, while I rigorously tried to execute Paul Graham’s “Do things that don’t scale” philosophy, I still created unreasonable expectations in my own head around user growth for each MVP iteration. This was probably due to the baggage I was carrying from my previous experience of working at large companies like Alibaba, where numbers were talked about in Millions & sometimes, Billions.
When the absolute user numbers weren’t met, my morale as a founder would get hit with each iteration. In hindsight, hitting numbers shouldn’t have been the goal at all. The ideal 0-to-1 mindset is like that of a scientist, with curiosity being the core driving emotion, backed by an iterative product development approach. The target outcome of this approach should be to gather insights that help refine the hypothesis.
Similar to how scientists drive their research process one experiment at a time, I have realized that building any new product or service from grounds-up requires moving one “unit” at a time. It’s up to you to decide what that unit should be – acquisition, activation, frequency of use, revenue or even just getting qualitative feedback!
In a scientific process, more than just the number of experiments run, what’s important is taking the learning from each experiment & applying it to the next one so it becomes better than the first.
Similarly, a good approach to building anything new is to delight one person at a time. This automatically focuses the building process & anchors it on an actual customer, thus making it easier to ship something that solves a monetizable problem for someone in the real world. Trust me, this is a non-trivial hurdle that many startup teams are unable to cross.
The 0-to-1 stage can be highly fuzzy but breaking it down into one unit at a time helps give more clarity to the team around the exact short-term goals.
The most profitable way for a product to grow is via word-of-mouth. The above approach naturally optimizes for it. And once the testimonials & organic growth start kicking in, traction compounds with minimal incremental effort.
Of course, the key to executing this building approach well is patience. Again, think of a scientist. A larger research budget or more headcount can’t necessarily speed up a breakthrough. Similarly, building one unit at a time requires a small team committed to iterating over a long enough timeline for customer compounding to kick in. A lean & capital-efficient operating model is a requirement of this approach as a long runway significantly improves the odds of success.
Learning from my mistakes as a founder, as I have now started working towards regularly putting useful startup & investing content out there, I am consciously following the approach of publishing & learning one unit of content at a time – blog post, Twitter thread, LinkedIn post etc.
Same for my angel investing, wherein I am trying to help each founder, co-investor & startup employee I meet, one week at a time, with whatever resources I have – network, expertise, capital etc.
This approach is helping me to first put the core enablers of my venture investing craft in place that then, hopefully, self-compound. Therefore, I feel much better this time about hitting my long-term goals.
Also, in case you are interested in other similar startup insights shared by Mike Maples at the DraperU event I referred to earlier, check out my Twitter thread on it.
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As the fundraising environment continues to get harder in 2023, founders & investors are deep into rationalizing business plans & finding ways to cut burn. The first temptation is to follow what I call an “excel sheet” approach – starting with the largest expense items without enough strategic thinking around the revised set of goals, business constraints in this new environment, what is working well right now, & how capital should be most efficiently allocated going-forward.
As opposed to big companies, startups operate with a finite runway, trying to address significant customer problems that remain unaddressed by large incumbents. This requires constant innovation – essentially doing hard, non-consensus things across the stack, everything from technology & design to customer experience & business model, that incumbents aren’t doing.
While big companies can afford to be relatively unscientific in cutting costs & still tide through tough macros with the help of their existing PMF, startups unfortunately, have no option but to play offense at all times in order to continue innovating & thereby, give themselves a chance to survive & succeed. In financial terms, this implies investing incremental $$ into innovation that drives more revenue (& profit), which is what will ultimately save a startup, not investor cash sitting in the bank.
So how should founders think about playing offense while being capital-constrained? I would like to propose a thinking tool called the “Focus Canvas“:
As a first step, rather than focusing on P&L line items, break down your business into specific buckets. These could include customer segments (eg. Individual, SMB, Enterprise etc.), product lines (eg. shrink-wrapped, custom deployment, pure services etc.), platforms (eg. desktop app, iOS, Android, browser extensions etc.), distribution channels (eg. self-serve, inside sales, direct sales, channel partners etc.), geographies (eg. US, EU, India etc.), teams by function/ type (eg. engg., product, design, sales, marketing, offshore contractors, agencies etc.) & other buckets that are relevant for your business.
Arrange all the relevant buckets & their constituent elements on a single page. This is your “Focus Canvas“.
On the top-left corner, list the most updated business goals for this year that all stakeholders in the company have aligned on. These could be things like “hit $1Mn ARR”, “show x% retention”, “start fundraising in Q4” etc.
On the top-right corner, list all the business constraints you expect to face this year. These could be things like “12 months runway left”, “only 2 backend engineers”, “sales cycle taking 6+ months to close” etc.
Now, as you are looking at this Focus Canvas, try and answer the question “what is working well right now?”*. You need to define “working well” for each bucket as per your specific context, also taking into account the above goals & constraints. It could be driven by one or more of revenue growth, most profitable, highest ROI, generating the most valuable feedback, creating the most differentiation, highest team productivity etc. *Note: this step is well-suited for a team workshop/ brainstorming session.
The most important step – for each bucket, put a â in front of the element(s) you believe is your best bet to achieve this year’s business goals while navigating expected constraints. Then, â out all other elements in the bucket. This is where ruthless focus is extremely important for the Canvas to do its job well – ideally, force yourself to â only your #1 focus element. In the case of most startups, that’s probably all you can afford to execute anyway.
Finally, take the â element from each bucket & weave them into a simple, 1-2 paragraph Focus Narrative. An example to illustrate this – “In 2023, we will focus on the Enterprise customer segment & offer them the standard product suite with a billable custom deployment services wrapper. The product roadmap will focus on the desktop app. We will double down on the internal sales model for distribution, with founders pitching in for strategic logos. To increase our team’s efficiency, we will significantly reduce contractor headcount & re-allocate them to full-time hires in engineering & internal sales.”
This Focus Canvas now provides a clear & strategic view of opportunities to both cut burn & re-allocate resources, while staying on track to achieve business goals & making progress toward PMF. The Focus Narrative can be used to socialize the going-forward strategy across teams in an easy-to-remember way. If used well (read: with ruthless focus), this approach can help startups in playing offense even in a tough economic environment.
PS: sharing a Focus Canvas template that you can use as a starting point. Feel free to download a copy & modify it as per your requirements.
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2022 definitely felt like the end of an era. A decade-long party for US tech, fueled by low-interest rates -> increased availability of risk capital -> price inflation across asset classes.
The last chapter of this post-GFC era was perhaps the craziest – an unprecedented pandemic -> widespread lockdowns -> more fiscal stimulus -> injecting more air into already inflated asset bubbles.
With inflation crossing 7%, the Fed finally started increasing interest rates last year and is expected to continue quantitative tightening over the next few quarters. Public market valuations expectedly turned south (valuations are based on DCF, so as discount rates go up, valuations go down), with tech growth stocks correcting by as much as 80-90%.
The following dynamics are currently at play:
Large tech: shrinking macro-demand + adverse public markets -> pressure on companies to reduce costs to bring them in line with lower growth projections -> drastic cost-cutting measures, including major layoffs.
VentureInvestors: public market corrections -> LPs cut back on venture allocations + downward revision of expected returns on exit -> venture activity slows down + any deals that happen, happen at much lower valuations given new public market comps.
Startups: less capital available + higher bar in private markets -> startups need to cut costs to survive -> layoffs in high-cost/ non-core functions + pause hiring unless absolutely essential.
2023 appears to be the “year of transition”, as both the overall macroeconomic cycle, as well as the technology sector within it, move into a new paradigm. I see the following ten big ideas for 2023:
Leaner-and-meaner big tech
For anyone working in tech over the last decade, we have witnessed first-hand the level of entitlement & cultural complacency that has grown within large tech companies like Google & Meta. With more challenging times ahead, I expect large tech companies to take drastic steps towards re-wiring their cultures & operating models. Layoffs are just one piece of the puzzle – expect significant changes to compensation policies, KPI/ OKR philosophies, org. structures, functional locations, work-from-home policies, contractor hiring, operating routines etc., all with the aim to make execution more efficient.
Founder-led companies (eg. Meta, Salesforce, Shopify, Coinbase etc.) will take quicker & braver calls to re-invent themselves, compared to those run by professional management teams (eg. Google). In the latter case, I expect shareholders to put considerable pressure on these professional CEOs to take corrective measures. In fact, I won’t be surprised if some of the big tech CEOs get unexpectedly replaced as many of them come across as peacetime CEOs who will struggle in wartime.
2. Capital efficiency over growth for startups
The last decade in tech startups was all about growth. This year, expect investing thesis & operating models to decisively shift towards capital efficiency. Mirroring the demands for margin improvement by public markets, I expect private market investors to significantly raise their expectations on operating efficiency.
Founders will have to react fast and in several cases, give a 1800 turn to their culture & business models. A silver lining – founders who were heads-down amidst the craziness of 2020-21, building their companies in a capital-efficient way, will have an enviable opportunity (& deservedly so!) to play offense both with customers & investors.
3. Bay Area bounces back
Remote work boomed during the pandemic, as tech companies grew at unprecedented rates. However, we saw signs of a comeback-to-office across both big companies & startups last year. With current headwinds, I expect factors like teams getting together to drive execution & in-person networking to become increasingly important.
With rampant layoffs, tech professionals will also feel more insecure & would need more access & optionality to get their careers back on track. All this bodes well for the Bay Area – I expect significant migration to the region, especially for people in their 20s to mid-30s. In terms of the sheer depth of the tech ecosystem, the Bay Area remains unparalleled. As emerging areas like AI, health-tech & EVs gain strength, they will provide even more reasons for talent to be physically here.
4. “De-angelification” of the startup ecosystem
Amidst the post-pandemic investing frenzy, liquidity-rich, over-optimistic, FOMO-driven tech professionals started dabbling in angel investing. Becoming an angel in a “hot deal” became a status symbol, & rapid paper-markups made everyone feel like a winner.
A majority of newbie angels from this vintage neither understand the nuances of this asset class nor have the depth of resources to play the game effectively over the long term.
As more startups start shutting down this year, combined with layoffs & decreasing compensations courtesy dwindling value of RSUs, I expect a massive churn in 2020-21 vintage angels. In my experience, tourist angels typically drop out of the game around the 4-6 deals/ 24 months mark, as they see portfolio companies starting to shut down & their hard-earned money vaporizing into thin air.
5. More pain in Crypto
If you thought 2022 was brutal for Crypto, brace yourself! FTX implosion is only the beginning of a much-needed cleanup in the space. I expect many more tokens to go to zero, projects to shut down & low-conviction talent to move out. Given the scale of the FTX fraud, am expecting even more regulatory oversight & ramifications for the overall sector this year.
Personally, I do believe there is a kernel of truth in the Web3 opportunity. The faster this cleanup happens, the sooner the next chapter can begin & we can make tangible progress towards discovering its real-world use cases.
On BTC and ETH, I expect both to remain flat at best, & significantly down from current levels in the bear case.
6. The FOMO shifts to AI
Whenever there is too much consensus around a trend or an asset class, I get worried! It was clean-tech pre-GFC, then Blockchain & Crypto pre-pandemic, moving to Web3 & future-of-work post-pandemic. Based on my Twitter feed, I can safely say that with the rise of OpenAI & launch of ChatGPT, the FOMO has now shifted from Web3 to AI. I am expecting the space to see a lot of hype, investor interest & startups being launched in 2023.
Studying how the previous FOMO waves evolved gives a fair understanding of what to expect – those without first-principles conviction & a long-term strategy are more likely to get their hands burned. Those who were anyway committed to the space & were quietly building behind the scenes over the last few years stand to disproportionately benefit from the increased availability of risk capital & talent.
7. The return of “moats” (& rise of deeptech)
As the perpetual-growth era of software ends, I expect the question around “moats” to re-appear in the diligence checklist of investors. The lifecycle of companies like Netflix & Robinhood has clearly shown how hard it is to have a sustainable competitive advantage in tech (one reason why Warren Buffet stays away from investing in it!).
As the likelihood of purely growth-driven exits goes down, I expect venture investors to start looking at deeptech verticals with inherent moats much more seriously. These include space-tech, health-tech (including lifesciences), energy, climate etc.
Each of the above markets seems to be getting unlocked in its own unique way & while these companies can be more capital-intensive & have higher technical risk compared to say SaaS or Social, the resulting market leaders have much more defensible competitive positions & hence command healthy valuation multiples.
8. EVs taking over the transportation stack
EVs are seeing major progress on both the supply & demand side. On the supply side, most major auto companies have an EV product in the market, with use cases evolving from urban sedans to SUVs, pickup trucks & now, even semi-trucks.
On the demand side, record-high gasoline prices have acted as a key unlock. This is visible in the rising hybridization of the latest gasoline car models. With non-Tesla EV products rapidly expanding, consumers have more choices across use cases & price points. I wrote a post a few months back on how I warmed up to EVs & Tesla, in particular. I expect EV penetration to have significant growth momentum this year.
9. Digitization of mainstream healthcare
A positive side-effect of the pandemic has been consumers getting increasingly comfortable with digitally-delivered healthcare services. In my case, interacting with healthcare providers over Zoom and accessing services such as Carbon Health & One Medical via their apps (including getting advice via chat) has really opened my eyes to its value. Even beyond that, I work-out with my trainer via video & our family nutritionist is in India with all interactions happening via Whatsapp.
I expect the overall healthcare stack, including mainstream services, to digitize at an even faster rate in the coming year. These tech platforms will also open up opportunities for niche services to exist eg. virtual monitoring & consultations for chronic patients, pre & post-natal advice, nutrition guidance etc.
10. India as a global greenshoot
Amidst an unstable China, weakening EU, war-torn Russia, one-dimensional Middle East, fiscally-unstable LatAm & fragmented Africa, India appears to be a solid greenshoot both geo-politically & economically. A stable & reformist govt. has worked hard to put together core growth pillars over the last 8 years – from building physical infrastructure & a national digital payments network to ensuring economic development at the grassroots & supporting tech startup activity in the country. India is poised to now reap the dividends of all this hard work, and similar to China, grow its per-capita income from ~$2k at present to ~$10k over the next 20 years, all in a democratic environment.
India’s tech ecosystem has also come of age in the last 5 years. The mega question of “can exits of venture-backed companies happen in India?” has been progressively answered, beginning with the acquisition of Flipkart by Walmart, followed by IPOs of consumer companies like Paytm, Nykaa & Zomato in domestic public markets, & the IPO of Freshworks in the from-India SaaS space on Nasdaq. There is a growing pool of startup talent, courtesy of a decade-long Mobile & software wave, which will fuel the country’s tech ecosystem over the next decade.
The above ideas are making me super-excited for 2023, both as an angel investor & operator. After a 2.5-year hiatus, I returned to angel investing in 2022, doing 3 deals in Q4. With the turning cycle & above ideas as a backdrop, my goal is to make 2023 my most active year yet as an angel, while also keeping a high bar on quality. Excited to collaborate with all founders, angels, VCs & operators out there đđ˝
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1) In SaaS/ Cloud, having a free product is really important to drive product-led-growth [note: strongly echoes what I heard from Dheeraj Pandey at the SaaSBOOMi Summit a few weeks back. Post Nutanix, he is building DevRev to be PLG-first].
2) Focusing on getting into enterprise deals much faster in his current startups compared to AppDynamics, as “that’s where the $$ are”. Eg. started doing $1Mn deals ~1.5 yrs into Harness vs taking a few years for the same at AppDynamics.
3) When doing a 0-to-1 in Enterprise, important to first build a “top 3 product” in the segment. Once that’s achieved, various layers of monetization can be built around it.
4) Really important to qualify beta customers in Enterprise, so the product can be built efficiently. Once they start using the MVP, ask them the question “what’s the business case of this product for you?”. Will help filter out potential non-customers from the beta group.
5) While in the early stages of building an Enterprise product, avoid going down a feature-building rabbit hole for specific customers. The risk here is building features that not everyone will use.
6) Content marketing is key to early customer discovery. Put great content out there and let customers find you.
7) To identify which customer segment to focus on, run multiple experiments & track metrics. Eg. do cold emails on LinkedIn to multiple personas in parallel & measure response rates to see where you are getting the most interest.
8) To build a $100Mn ARR Enterprise business, founders need to have a view early on of how that destination math will eventually look in terms of no. of customers & ACV.
9) Interestingly, the current macro climate is seeing a slowdown only from an investor perspective. Enterprise customers are still growing rapidly & also spending more on software.
10) Important to operate lean in times like these where access to capital is getting constrained. Eg. at Harness, we are asking the question “can we achieve the same growth targets but with 20% less burn?”. Looking grounds-up at each function’s op-structure & optimizing.
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Recently, I was in a shareholder’s meeting of a portfolio company. It has been a gut-wrenching last 3 years for the leadership. Unfortunately, the company’s market pretty much shut down during Covid. Significant liabilities built up & the team saw significant churn. To survive, the company had to raise a bridge at a major haircut.
During the meeting, the management team walked us through their journey of turning the business around from this dire situation. After the lockdown was over, customer demand got re-ignited. The company drastically cut costs, improved operating metrics to get revenue back on track, re-negotiated long-term vendor contracts, and cleared-off short-term liabilities, all while retaining the core manpower, many of whom had to take salary cuts.
As a result, the company is now PBT-profitable & growing through internal accruals. Btw this turnaround was achieved on a ~$13Mn revenue base. As an operator & ex-founder, I was blown away by this execution story & the team’s grit.
But then, I put my investor’s hat on – despite all this progress, early investors are deeply out-of-money & are likely to remain so for a while. During 2017-19, the company raised equity at aggressive valuations that were misaligned with both the maturity of the business as well as the underlying multiples the sector trades at. In boom times, startups get valued at hyper-growth tech multiples. However, as soon as the cycle resets, follow-on investors revert to valuing them on realistic sectoral comps.
The good news is, courtesy of the awesome restructuring efforts, the business is on a profitable growth path. But given the extent of divergence between our entry valuations & current market comps, it’s going to be a long road toward generating healthy returns for early investors. And even if we get there, the sheer time taken will negatively impact IRRs.
As an angel, this is the part I really struggle to get my head around – how important is the entry price? Bill Gurley says in this 20VC podcast with Harry Stebbings – “the market sets the price on a deal-by-deal basis but as an investor, you have to keep an eye out for the price you are paying at a portfolio level”. This becomes especially hard for angels, who typically have to adhere to the price set either by the founder (SAFEs) or an institutional lead. In this era of fragmented checks via syndicates, SPVs & RUVs, I frequently see valuations that aren’t correlated to the underlying risk in the business & smaller check investors unable to push back. Ultimately, everyone ends up toeing the line.
As an investor, I always have the option of not participating in a highly-priced round. But then enters the other side of the coin – power law ensures very few companies drive a majority of venture returns. Therefore, angel investing is the game of accessing the “best” companies, which often requires paying up to get in. An argument frequently made is “if the company ends up as an outlier, it doesn’t matter what price you got in at”. I get this line of thinking but an “outlier return” is very contextual. Eg. a 10x return potential over a 5-7 year period is very solid for an angel, though might not meet the deal hurdle for a large fund. There are cases in my own portfolio wherein early angels are sitting on a 5-10x unrealized return because we entered at sub-$10Mn valuations and frankly, the likelihood of a startup hitting a $50-100Mn valuation is significantly higher than becoming a unicorn.
Over a 20+ angel portfolio built over 8+ years, I still struggle with thinking about entry valuations the right way. Presently, am taking it deal-by-deal with the guiding North Star of discovering & backing the best founders I can find, while also accepting the reality that angels will usually be price-takers that are prone to macro sentiments & the whims of lead investors. As Bill Gurley advises, maintaining perspective & discipline around portfolio-wide avg. entry price seems to be a smart way to play a balanced game.
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Was talking to a really early stage startup recently. The founders have been building the product as a side-hustle, have a few initial users but are now facing a decision fork. They need to raise capital to be able to leave their full-time jobs and focus on the startup BUT investors typically want founders who are already full-time before they commit capital. How does one resolve this?
I have personally faced several such forks, especially since starting-up 2 years back. I call them “but” decisions – they are irritatingly hard because both sides of outcomes have similar chances of actually happening.
Despite many iterations, the product isn’t hitting the expected metrics. On one hand, you had decided that if the desired metrics aren’t achieved, you will seriously evaluate the company’s future. BUT, you also hear stories of perseverance where an extra 12 months ended up changing the growth trajectory of many startups.
You are close to hiring someone for a super-critical role but aren’t fully convinced yet on the candidate. On one hand, it could be just the person you were looking for, who ends up contributing really well. BUT, it could also blow up in your face, end up eating valuable runway and adversely impact the rest of the team.
You are feeling stressed about various challenges facing the company, and are contemplating discussing it with an investor in the company. On one hand, the investor’s interests are perfectly aligned with yours and advising founders is one of their core roles. BUT, you have seen/ heard of several cases where these interactions have blown up in the founder’s face in more ways than one.
“But” decisions also have other added complexities like not having prior experience to turn to & existential impact in case of an unfavorable outcome. A common advice would be to talk to people who have dealt with similar situations. Again, what I have seen is that you get very divided opinions wherein people in the past have ended up on either side of the equation.
I haven’t yet been able to figure out a perfect framework to make these “but” decisions. Typically, I try and go by first-principles, following a method very similar to what Annie Duke frequently talks about:
Map out various outcome scenarios
Do a macro-filtering based on a) values and b) goals I have set for the particular context
Figure out the upside & downside quantums for each scenario (qualitative and/ or quantitative)
In my head, assign some kind of (even qualitative) “probability” to each scenario, based on what I know at that time
See what the expected payoff is looking like for each scenario
While speaking to relevant experts/ mentors, rather than accepting any binary advice on face value, I adjust the above variables based on their inputs. Also, I try and adjust for few specific biases I know I have been prone to in the past (eg. optimism bias in my case). My better half plays an awesome role in calling my biases out :).
I know these decisions can’t be taken mathematically but the above process at least makes sure I am thinking 3600 about the problem. But even with all this prep & analysis, frequent screw-ups happen đ It’s part of the game – I believe the idea is to get a little bit better at these “but” decisions each time…and avoid risk of total ruin to be able to keep playing the game.
Recently, David Sacks shared about having a product-first approach to building companies, drawing on how Square & PayPal used similar strategies to identify market gaps & solve for them. Here are the key takeaways:
#1 Make a simple product with a clear âhookâ to grab users. Typically, this hook is a high-frequency task that users can do in the product to engage with it and subsequently, can then be enticed to engage with other features in the stack. Square -> Swipe, PayPal ->Email Money.
#2 Couple the product hook with a distribution trick that can create viral adoption of the product. Square ->distinctive hardware design & branding. PayPal -> email virality via sending money.
#3 Hook+Distribution trick together hopefully drive enough early users to start learning from. Unique market insight doesnât appear via a brain wave from founders. Itâs identified via observing who is using the product & why. Eg. Square -> merchants not having a credit history.
#4 Build the operating capabilities necessary to execute on this insight. For instance, both Square and PayPal had to build new types of fraud detection systems to solve the lack of credit history & processes. These operating capabilities & IP, turn, become long term moats.
#5 Finally, in this process of operationalizing the market insight, an overarching business theme will emerge. Eg. for Square, it became âaccessâ. Start building out your product roadmap around this theme, and keep adding more offerings but all centered around this âNorth Starâ.
To summarize, getting a unique market insight to build a startup on, first requires launching a simple product that gets user-adoption, observing who they are and why they are using it, and then extrapolating that to re-frame the true pain point of the user.
Building a product to solve for this âreframedâ user problem will automatically result in a truly differentiated product that is filling a key gap in the market that few others are seeing in the way you are seeing.
You can read the complete article on Davidâs substack here.
Note: this post first appeared on the Workomo blog here.
Team Workomo had an excellent working session on engineering last week with Prashanth Susarla, ex-CTO of PayU. He shared several frameworks and heuristics with us for taking smarter tech decisions as a really early-stage startup. Sharing key insights below đŻ
#1 Less is more: proactively look for platform elements where you can avoid coding and offload to off-the-shelf services. Look for opportunities where you can cut down your own code. Avoid unnecessarily complex approaches for low-value tasks đ¤ş
#2 Invest in automated testing: it will yield valuable dividends compared to manual testing. In fact, engineering teams should invest in automated testing ASAP else it becomes part of a broken culture thatâs tough to change later âď¸
#3 Testing is strategic to the product: often teams tend to view testing as low-value ops. Being able to design great test cases is a high-value skill. Break down the most critical user journeys and start automating them. Donât sweat over perfecting the testing frameworks yet đ
#4 Aim for architecture reliability, not perfection: at really early stages, with rapid product iterations and pivots, engineering teams need to build for progress and not perfection. Having said that, keep periodically stress testing your backend for expected traction loads đđźââď¸
#5 Define engineering SLAs via highly-specific user stories: eg. a user story could be â95th percentile of my users should not see more than a 5 min delay between updating their Gsuite calendar vs those changes reflecting in the Workomo panelâ đĽ
#6 Apply ML to project future loads & requirements: while engineering is building for high-velocity weekly/ biweekly releases, certain core elements require thinking through requirements say after 1â1.5 yrs. However, you canât build for it right now. So use ML to break down the problem and optimize đŹ
#7 Account for engineering activities in product sprints: core engineering tasks that arenât always directly related to a specific feature release, still need to be baked into sprint planning & timelines. Helps balance prioritization between feature releases and tech debt optimization âšđ˝ââď¸
#8 Build a strong engineering culture: that happens as a result of adopting strong habits. A bad habit will often give you speed but destroy value in the long run. Even if you are moving in bi-weekly sprints, always have a 3-month view and a 1-year strategy in place âł
#9 Security is important even for a really early product: your platform coming under attack is not a question of âifâ, itâs a question of âwhenâ. Think about security as soon as you launch, even in private beta. Imagine a doomsday scenario once a month and prepare for it đš
#10 Finally, the best engineering teams are driven by humility: while looking to build any feature or platform, teams need to be incredibly honest to themselves about their present capabilities, what risks can they take, what plans can they pull off & take decisions accordingly đ§đ˝ââď¸
What are some engineering best practices that have worked for you in an early startup environment? Would love to hear your thoughts.
Note: this post first appeared on the Workomo blog here.
