Marketplace Take Rates and Econ 101

supply_demand

In college I studied both Finance and Economics and I really enjoyed the combination that both degrees offered me.  Finance gave me a great sense of numbers and analyzing companies and Economics offered me more on organizational theory and incentive behavior.  When combined, these studies offered me a holistic viewpoint into why businesses make decisions and how to analyze those decisions and this has been instrumental in my career working with hundreds of startups in the venture ecosystem.

One thing that has stuck with me since college is the idea of price elasticity and in my career I have been fortunate to work with a lot of marketplace companies where I see the theory of price elasticity being proven out daily.

As I alluded to in my last post, I have been wanting to write a more comprehensive post on this topic and with long term rental/corporate housing startup, 2nd Address’ announcement of its $10M Series C from GV, I figured now a better time than ever.

For a quick econ 101 lesson, Price elasticity is the degree of responsiveness (change in quantity) for supply or demand based on a change in price.  There are 2 extremes of price elasticity of demand, highly inelastic demand and highly elastic demand.  

Image result for inelastic vs elastic price curve

Highly Inelastic Demand is that there is no or minimal change in demand for a given change in price. The example that my professor always used was Insulin but for a more 2019 version we can use the excessive drug prices that big pharma can charge (looking at you Shkreli!).  In this example, a company can raise prices as much as they want because of the nature of the good (life saving drugs) that the demand will remain the same and users are forced to pay the high prices in order to live.  This gives businesses extreme pricing power over consumers.   

Highly Elastic Demand is the opposite where any change in price will drastically change the demand for the good. An example of this would be the price difference between Uber and Lyft. If Uber and Lyft prices differ greatly the user would choose the lower cost ride (all other things equal and switching costs being de minimis). This gives users a large degree of indirect control over the pricing dynamics of the marketplaces as businesses must be hypersensitive to changing price in fear of losing customers.

With marketplaces such as Uber, Lyft, Airbnb, Gametime Getaround, 2nd Address, and many others, one of the main ways they are compensated is on their take rate (called many things by many companies) and that rate is the fees they charge to manage the marketplace and facilitate transactions. The supplier (Drivers in Uber/Lyft example) then get to keep the remainder of the fare minus the take rate.

Uber and Lyft charge these to pay engineer salaries to keep the app updated and to fund their marketing spend to attract both drivers and riders (#expensive!).  Getaround charges their rate to keep their ecosystem online and work with their various support teams to get new cars on the road and keep consumers happy.

This take rate varies by company and marketplace model and a lot of other factors as you can see by the examples below.

Company Industry Take Rate
Airbnb Home sharing/Travel 0 – 20%
2nd Address Home sharing/Travel 7 – 26%
Uber Rideshare/Mobility ~25%
Lyft Rideshare/Mobility ~25%
Getaround Rideshare/Mobility 40%

So why do Airbnb and 2nd Address and Uber and Lyft have similar take rates? Why is Getaround far and away the highest percentage?  Many reasons but one partial explanation is price elasticity.

In our Econ 101 example above, Uber and Lyft are near identical services and as a result are competing mostly on price and are fairly elastic goods so it makes sense that their take rates are similar.

Getaround on the other hand is a fairly inelastic good due primarily to the nature of the service it facilitates.  Getaround offers consumers the use of someone’s car when that car is not being used by the owner.  This is about as inelastic as one can get in consumer.  The use of the car, which otherwise remains unused/parked in its parking spot, is right up there with insulin as an inelastic good because the opportunity cost is next to nothing to have someone rent it.  This differs from Uber/Lyft where the car owner actually needs to drive the car and provide a service and is one of the main reasons why Getaround can charge so much.  Some may say Getaround is letting the suppliers or car owners (disclaimer: I am one) off easy by only charging 40%!

While take rates vary for numerous reasons and are only one piece of the puzzle, I find it fascinating their role in the interplay between incentives, consumer behavior, and business growth.  This will be ever interesting to watch as Uber, Lyft, and Airbnb march towards IPO and focus on a path to (or maintaining) profitability while other competitors raise larger rounds and try to scale their own businesses in the behemoths shadows.  It can be appealing to use the lever of take rate to impact business performance and the financial model but if we’ve learned anything from this post is that the take rate may impact a lot more than the top line growth due to its price elasticity!

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Unit Economics, Network Effects, Loss Leaders, and Vertical SaaS: Some thoughts on scaling marketplaces

 

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#MOOD? (Credit HackerNoon)

Unit Economics are of utmost importance when starting and scaling a business, especially a marketplace.  I came across a great article by Toby Clarence-Smith, a Toptal finance expert, entrepreneur, and investor, about what Unit Economics are and why they matter.  I want to provide some context given my experience working with hundreds of VC-backed companies and numerous consumer and marketplace startups.

In his post, Toby brings up some great points on scaling a business and how to think in-depth about fixed and variable costs and contribution margin. He also highlights Food as a key industry that has attempted to become an on-demand haven but struggled mightily.  All points are well made and it is a great primer for any transactional or marketplace-based founder to read.

When you factor what needs to go right for even positive unit economics businesses, it is no surprise that purely transactional marketplaces in industries like Food are extremely hard to scale on their own successfully. They require massive investments in both supply-side and demand-side user acquisition and support all for take rates that can be as low as 5-10% based on the price elasticity of a product/service (more on this in another post).  While network effects and winner take all moats can be extremely lucrative, the difficulty in executing and actually succeeding is extremely high.

So what can be done and why are these companies still getting funded at such valuations? Sure some of this may be market froth and a bit of FOMTN (Fear of Missing the Next) but there are some key actions a Company can take to better position themselves for success.

In his article, Toby makes some great points on how companies can get by with negative/minimal unit economics temporarily to generate economies of scale, increase customer loyalty, and drive ROI on an LTV/CAC basis.

I want to highlight his last point on driving ROI around LTV/CAC or the ability to generate minimal margin on first orders to drive profitable longer term customer value.  This business strategy when used effectively can be extremely lucrative but is fraught with danger and bubble-isms of the dotcom era when done wrong.

In my opinion, one of the best at this strategy was Microsoft who used this strategy when driving its Xbox and Xbox live platform to use the gaming console as a loss leader sold at cost or below cost to enable the sale of higher margin games and online subscriptions. Amazon prime has also been a great example of this more recently to drive not only a subscription component but higher GMV.

Image result for xbox 2005

One of the OG Xboxes of my youth

This use of a transactional marketplace as the “loss leading product” can be effective when combined with other revenue streams atop the marketplace. We have seen this of recent in the VC community with Vertical-Specific marketplaces adopting SaaS models in addition to the transactional piece.  This is not specific to loss-leading as many companies can straddle profitable marketplaces and vertical-specific software but I think it is important to illustrate the potential.

Roadster, an online car buying platform, has done this with their express storefront for consumers and selling the backend software to dealerships to not only drive SaaS margins but greatly improve the online buying experience for consumers.

Squire, an online barbershop marketplace with corresponding barbershop software provider is another example.

By allowing for marketplace transactions to be at minimal margin or at cost, it enables the company to not only drive the demand side of the equation to attract consumers with fair pricing but it also enables them to implement software (at much higher margins) on the supply side to allow business owners to better reach this audience within the marketplace.  This SaaS revenue at best drives major growth for the business and at minimum can offset some of the costs for supply and demand-side acquisition and support that is so critical (and expensive) to really get the network effects and marketplace flywheel going.

There are other ways to augment the purely transactional marketplace via premium offerings, promoted posts, and other subscription types and it really depends on what the best use case is for each company and market the founders are going after.

There are lots of ways to build a great business and I am always amazed to see just what the startup community can do around business model innovation to drive change across industries!

Thoughts on Walmart’s purchase of Eloquii

Image result for eloquii logo

Last week Walmart bought Eloquii in a bid to expand their online offerings for the $21BN plus-size women’s apparel market.

Deal Overview:

According to the recode article, Eloquii raised $42M and the rumored purchase price was $100M at about 2.5x – 3x sales.  While, this not the Billion dollar outcome VCs strive for, if this price is accurate, it appears to be a less than ideal money-back type outcome for the investors but it commands a solid multiple on sales relative to most ecommerce/brand comps out there, and an even better strategic fit for Walmart long term.

Eloquii CEO Mariah Chase was quoted as saying “When you’re a business that had raised venture capital, selling the business is not necessarily an existential question, especially as you mature, “The question really comes down to timing and partner. And for us, that all kind of gelled with Walmart.”

This “timing and partnership” was further highlighted by Walmart head of eCommerce/Digital, and creator of the OG DNVB Bonobos, Andy Dunn, as he mentioned Walmart’s desire to be able to better serve the plus-size market as well as make Walmart and their family of brands more than just a shopping portal that sells brands but a place that “builds brands and develops customer relationships”.

Walmart’s approach to strategic purchases the past few years has proven out this commitment to brand building and customer relationships within Walmart (see deals: Bonobos, Modcloth, Moosejaw, Store8, Allswell, etc.).

Brand Building is harder than it looks:

Given the influx of social media influencers and Shopify’s ease of setup it has never been easier to start a brand. But starting a brand and building a brand are very different things.

Building a brand is hard, building an authentic brand that is able to reach scale or “escape velocity” as a stand-alone company to generate the true “VC-level” returns is extremely difficult in today’s day and age of rising Customer Acquisition Cost (CAC) and increasing competition for wallet share so I think deals like this one will become more frequent.

Large Enterprise Software and Cybersecurity firms are notorious for small tuck -in acquisitions and other point solution purchases they can then attach to their broader suite of products (shout out 2014 Valuation World Cup Runner-Up Attach Rate!) and I view this deal the brand equivalent of just that.

Eloquii is a strong individual brand in a market they know extremely well that can be even better utilized in a bigger portfolio of brands with access to much greater resources while still maintaining the ability to keep its unique brand identity and ethos intact.

I have mentioned to anyone that will listen, or at least feign interest as I theorize, that I think Walmart is well on its way to becoming the Phillips Van Heusen or V.F. Corporation for the next wave of Consumer Brands.

Image result for pvh brands

A Sample of PVH’s brands

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V.F. Corps family of brands (a bit outdated since they just sold Reef to Rockport)

They have the buying power, the leadership team, the data-first mentality that comes with DNVBs, the supply chain expertise, and the need to differentiate from Amazon to drive them to become the next great brand aggregator.

This deal is another step in that direction as it gives Walmart entry into a market they have so desperately wanted access to but it also gives Eloquii the ability to grow and reach scale with much greater resources at their disposal.

Can AI/ML continue to make waves in HR Tech? A dive into Headstart.io

Another day, another diligence memo! Today I focused on a company in the HR/Talent Acquisition space.  For this one, it wasn’t done around a specific deal, simply about the company overall.

Company: Headstart

Website: https://headstart.io/

headstart

Key Takeaway

  • An AI/ML focused startup that has the potential to disrupt the HR/Talent Acquisition landscape through focused execution and a diligent leadership team.  Initial traction between users and corporate accounts demonstrates execution and upside potential but tempered by intense competition and fears of this being a feature and not a full-fledged company.

headst

Company Description

  • Headstart is a developer of a job matching platform designed to help employers identify the best-suited candidates in the shortest amount of time. The company’s platform utilizes machine learning technology and combines psychometric testing and algorithmic analysis to offer effective, engaging and unbiased applicant review, enabling job-seekers to connect directly with businesses and companies and save time and money by accurately finding candidates who meet their exact job recruitment. The Company’s ability to combine traditional objective job traits with context and cultural fit of the target company is their key differentiator. They recently participated in Y Combinator’s Summer 2017 batch. (source: PItchbook, company website)

What could make Headstart a success? What could make it struggle to succeed?

  • Headstart could be a success if it can continue to provide positive outcomes for its large corporate clients while not losing sight of the job seeker experience.  This balance between serving two-sided marketplaces is fraught with peril so appropriate consideration must be given to not only the job seeking user experience but also the corporate user and their KPIs around time to hire and using the algorithms to find strong cultural fit.
  • Headstart could struggle to succeed if the Company’s algorithms do not improve candidate selection metrics for its corporate customers. It could also struggle to succeed in acquiring job-seekers amidst hundreds of other competitors and have low conversion rates for the target companies and high customer acquisition costs.

Market Potential

Talent Acquisition Segments 2016   ($M) 2021 ($M) CAGR, %
Applicant Tracking 732 889 4.0%
Contingent Labor Management 445 578 5.4%
Marketing 410 514 4.6%
Onboarding 447 545 4.0%
Recruiting 1,219 1,450 3.5%
Sourcing 728 782 1.4%
Total 3,981 4,757 3.6%
  • Source: Apps Run The World, January 2018

The talent acquisition market within HR tech is expected to reach $4.7BN by 2021.  This is a massive opportunity for Headstart to continue to break into this market. That said, the majority of the market is currently made up of by the big names in the space (LinkedIn, IBM, SAP, etc.) but there is continued interest in new/emerging technologies which could drive greater adoption for Headstart.
talent acq

Management Team

    • The team is led by two co-founders with backgrounds in edtech and a Thiel fellow as well as neuroscience/ML/AI. The two co-founders combined with their extended management team have all the makings of a strong team poised to execute well and their ability to attract large corporates as well as YC backing, especially the AI Vertical group, is a testament to this ability.

 

  • Nicholas Shekerdemian – Co-founder (CEO)

 

      • NIcholas is a Forbes 30 under 30, a Thiel Fellow, and also started an online tutoring/consulting edTech company focused on China and the UK prior to founding Headstart.  Just age 23, he seems dedicated, driven, and passionate about enacting real change in the talent acquisition market

 

  • Jeremy Hindle – Co-founder (CTO)

 

    • Jeremy is a Forbes 30 under 30 with a strong background in neuroscience, AI/ML and programming

Investors/Financing

  • Headstart was recently accepted into Plug and Play’s enterprise 2.0 batch for 2018.  Prior to that, the Company was in YC’s summer 2017 batch and before that the company bootstrapped itself. According to Pitchbook, total financing is at $120k but a few other sources have the total raised at $600k.  
  • Regardless of true total raised, the Company has shown strong capital efficiency in that it grew its team from bootstrapped 2 co-founders to 17 employees all on a minimal amount of investor capital which combined with their customer adoption, leads me to believe they are generating decent initial revenues.  
  • Headstart’s ability to drive solid adoption and close corporate customers while bootstrapping and on minimal capital is a very positive development and demonstrates their ability to effectively manage capital yet still execute on the business.

Competition

  • The competition in Talent Acquisition and the broader HR tech landscape is immense.  Competitors range from multibillion dollar companies to well-funded growth stage startups to a handful of other early stage businesses.  This provides market validation of the need for new approaches to recruiting but also makes the potential for success that much more difficult.  
  • LinkedIn, Glassdoor, ZIpRecruiter, Lever, Indeed, Smartly, and many others are just a few of the companies vying for a similar budget that Headstart is going after.
  • A lot of the competition is looking to differentiate in certain ways via metric tracking (Lever), mass market adoption/1st mover advantage (Linkedin), education/value add services (Smartly) and Headstart is no different. Their focus on AI/ML to drive comprehensive hiring is a strong differentiator if they can execute on it.
  • Koru appears to be the closest direct competitor I could find to Headstart in that it is also aiming to get predictive on hiring based on more than objective criteria for those early in their careers.  According to Pitchbook, they have raised $15m to date but it looks like they did a Series A2 in Sep 2017 at a down round from their Series A in 2015. They did have a solid investor syndicate in their Series A (Battery, First Round) so I would want to dig further on Koru and look to connect with their investors or the company itself to get a better sense of what caused the down round and if it was company execution or more macro issues and use that for guidance with Headstart.

Financials/Growth/KPIs/Business Model

  • The Company has had solid success in its first year of founding, they have over 100 corporations signed up and over 20k students signed up.  The business model is corporations pay for posting and using the service whereas job seekers and small start-ups can use the platform for free.  
  • Similar to the Company’s capital efficiency, their ability to attract sizeable numbers of students and corporations all while growing the team substantially is a positive indicator about future upside.  I would want to learn more about the Company’s customer acquisition channels and how they plan to fulfill both sides of the market while maintaining growth and managing cash burn.
  • One of the biggest questions i have regarding Headstart as a potential investment opportunity is their focus on expansion.  Do they plan to really build out a true double sided market and become the next LinkedIn/ZipRecruiter? Or are they comfortable using their algorithms and matching software as more of a traditional enterprise sale or feature to then be built into a larger platform such as LinkedIn’s offering.  I find it would become fairly cost prohibitive to go after the double sided market given the large incumbents but I could see more viability in focusing on the corporate clients it just may become more difficult to effectively train their algorithms with less job seeker data.
  • For KPIs, I would want to learn about their CAC, their Sales cycle for corporations, their average sales price, their revenue concentration by client, their churn, their conversion rates from candidate to being hired, and their ability to truly tailor candidates to more than just a job description and really source for culture.

Key Strengths

  • The team’s ability to execute on minimal capital and drive substantial initial results is by far the most impressive thing to me so far.
  • The AI/ML angle is the second most impressive potential strength. If the company can continue to prove their offering and their algorithm can match better candidates for fit/culture then they will truly be an outsized venture-level success in market.
  • The HR tech market is also a strength as there is a lot of appetite for new products and an ability to prove ROI on recruiting via time or cost savings.
  • The user experience on the consumer user side can also be seen as a strength as they appear to be able to have a single application/profile for each user which drives ease of use and easier adoption.

Key Risks

  • Can the company achieve scale? They have gotten initial validation and some key customers but can they really achieve growth on both sides of the market to feed their algorithms and continue to amass the dataset needed to truly change the market around talent acquisition?
  • It appears they have lost their head of Psychology/Psychometrics based on his updated LinkedIn profile.  Can the company continue to achieve scale with the right management team while dealing with turnover/hiring their own candidates?
  • With any AI/ML or algorithm approach, there is always risk that someone else can make a similar algorithm and/or a “better mouse trap”. How do you view your IP/Algorithms as defensible to the major incumbents (LinkedIn, Google, etc) and what is stopping them from using their vast user base and data sets from creating a similar offering?

Key Questions for Management

  • What information is needed to best feed the algorithm? Job seeker data or corporation data?
  • Is acquiring Job seekers vital to the algorithm and if so, how do you plan to profitably acquire users at scale? How has using school groups and ambassadors worked so far?
  • Koru the company – are you aware of them and their history? If so, did they have any issues in market or just company specific issues?
  • What are your expansion plans? WIll you look to raise traditional venture growth funding or plan to run the business via sales/profitability using corporate customers?
  • What has been the feedback from current customers? Has there been any churn? If so, what was the reason for the churn?

Final Thoughts

  • I think Headstart has a lot of upside and has shown their ability to execute on minimal outside capital. I think they have a strong team and are hitting the timing right with their focus on AI/ML in market and the appetite for corporations to utilize new technologies to recruit the best candidates. This combined with their recent acceptance into Plug and Play’s 2018 Enterprise 2.0 batch makes Headstart a company I will continue to follow and recommend for further diligence.

Series A Teardown – Front

This is my first run at a teardown of a Series A Company.

I am going to try to make this a recurring theme where I dive into a publicly available Company pitch deck and derive an investment and due diligence memo from it.

Why? Because as a VC-nerd I find this fun but I aware I probably need more hobbies 🙂 In reality, I hope this can provide a framework into how I look at certain types of companies in various sectors.

Company: Front

front

Website: https://frontapp.com/

Front Original Slide Deck  – Series A, 2016

Key Takeaway

  • A promising company with solid initial traction and potential to warrant a continued look.

Company Description

  • Front is a collaboration tool for enterprises. It is a multi-channel email system that provides a unified view and allows teams to collaborate across the enterprise.  

What could make Front a success? What could make it struggle to succeed?

  • Front has good initial traction and has been very capital efficient since inception. This financial rigor combined with an ability to scale and generate consistent growth could allow them to achieve a sizeable outcome.  
  • Front could struggle if they cannot transition from organic growth to paid growth to effectively reach scale and if other major players in the communication space decide to build a competing product.

Market Potential

  • If executed properly, Front has the potential to take share from the external communications, support, and customer service industries, a billion dollar business is feasible.

Management Team

  • The Head of Sales is the former 1st salesperson at Box and the Head of Customer success was head of upsells at Dropbox. This seems to be a quality team for entering the market.

Investors/Financing

  • Front participated in Y combinator and then raised a $3M Seed round in 2014 from notable angels including Elad Gil, Dave Morin, Alexis Ohanian, and Paul Buchheit.

Competition

  • Combination of established players and growth stage/VC backed companies

competition front

Customers

  • Front has signed up a few major brands and other lighthouse customers but the extent of their revenue concentration from these customers is unknown.  I would want to understand more about how much MRR these select customers were responsible for before passing judgement on whether these are true customers or just marketing ploys.

Financials/Growth/KPIs/Business Model

Pricing

pricing

  • For the sake of this exercise, I am assuming that pricing hasn’t changed since 2016 from what is on the current website.
  • This is clearly a high volume, low price per user business.  The company employs a land and expand strategy where they sign up individuals and small teams and then look to upsell and cross-sell to the rest of the organization.  
  • Bonus points for the 14 day free trial as well as the annual pricing with the 17% savings highlighted as each plan is billed annually upon sign up resulting in cash inflow from day 1 as opposed to monthly. This sales incentive to generate cash flow is part of the Company’s financial rigor that I am impressed with.

MRR and Customer Count

  • The company has shown consistent and impressive MRR growth and increased customer adoption.  This is excellent to see this consistent early traction with no marketing spend
  • That said, doing an estimated MRR per customer shows a different story. As seen below, the average MRR per customer shows a continued decline.  While it is great they are growing both MRR and customers, it appears that the average MRR per customer is decreasing each month meaning that less and less seats are signing up per new customer.  
Estimated MRR, Customer Count
Date MRR Company Count Avg. MRR per Customer
9/1/14 $15,000 62 $242
12/1/14 $26,000 125 $208
3/1/15 $41,000 200 $205
6/1/15 $59,000 330 $179
9/1/15 $82,000 500 $164
12/1/15 $97,500 670 $146
3/1/16 $113,000 880 $128
*my estimated calculations by reading the graph in more detail
  • I would continue to monitor this trend as it could be a sign of trouble should the average keep getting lower and lower.  I understand that this is a freemium/self-service type SaaS model with low barriers to adoption but this is something that worries me especially for when they have to move to paid advertising to attract customers and the resulting LTV/CAC ratio could be based on drastically lower LTV expectations.

User Churn

churn.png

  • Front advertises low churn and negative net MRR churn. While the negative dollar churn appears to be true, the 3% monthly user churn seems a bit high to me as that annualizes out to about 31% user churn which at 1000 customers would be 310 lost customers a year! I understand that this is a high volume business but that is a dangerous amount of customers to lose even at this early stage.  
  • I would want to learn more from management as to the main causes of churn

Dollar Churn

dollar churn.png

  • On the flip side, I am impressed with their successful expansion strategy and the resulting negative net MRR dollar churn.  The ability for the company to replace not only the dollars lost from the churned users through greatly expanding MRR from retained customers has been very impressive.  Especially impressive has been the ability to continually increase the MRR on an annual cohort basis of 150% of starting MRR. This helps prove their product is not only viable for its initial customers but that Front can successfully upsell consistently over time.
  • Conversely, if my calculations on average MRR per customer are correct, the absolute dollar value of MRR expansion may not be as impressive on the more recent cohorts. Seeing that Average MRR per customer has decreased from ~$240 to ~$130 since the cohort measurements started, getting to 150% annual expansion of $130 MRR would only generate $195 in MRR so the expansion of a lower starting MRR customer is less impressive on a percentage basis. While it is nice to see that they can land and expand, if the starting point continues to get smaller it may be a cause for concern.
  • I would want to ask management more about their customer dynamics around free trial conversions, customer revenue concentration within each cohort, and expansion strategy playbook.

Capital Efficiency

cap effic

  • To me, this is where Front shines.  The fact that they have only spent $1.3M to arrive at $1.4M in ARR is extremely impressive especially given how much companies are spending on customer acquisition, engineering talent, and perks these days.  
  • The other impressive piece is they still have over half of their Seed round left. That and their $90k monthly burn rate gives them about 20 months of runway so even without this $10M they are still on solid financial footing.

Projections

projections.png

  • Front expects to triple ARR in 2017 and while this would be impressive, it is unclear where that sales efficiency would come from based on this financial plan.  I would want to ask management a lot more questions around how they plan to build up this ARR and what the “Other” expense entailed as it is unclear if this is salary for sales, rent for a building, etc.
  • The non-engineering spend seems to taper off starting in February 2017 so it appears they expect to hire aggressively through the end of 2016 but less so in 2017. I would be curious to know their hiring plans as well as their sales and marketing plans.  

Valuation

  • According to Pitchbook, the Company raised their $10M at $30M pre for a post-money valuation of $40M.   While I am unsure the validity of these terms, this could be an appropriate valuation for the round given the Company traction.  While you can’t really use public company multiples as a comparison given the differences in company profile, a few other methods could give us comfort.

VC Ownership Method

  • From a venture ownership, this follows the more traditional model of investors owning ~25% of a company in the series A so that isn’t out of the ordinary and what i believe had an outsized influence on this valuation and pricing of the round.

VC Rate of Return Method:

  • If Front raised $10M, Series A investors would expect a $100M return (10x) which would be $400M in exit value which in the realm of B2B SaaS deals is more than reasonable.  With major corporations spending hundreds of millions and even billions in M&A each year combined with the ability for companies to IPO at the $100M revenue threshold on a path to profitability, the options for an exit of this caliber are fathomable if Front can execute on their vision long term.

Conclusion:

  • Front’s value proposition, its capital efficient growth, and capable management team have demonstrated enough value to warrant a sizeable uptick in valuation from their seed round.  I recommend we continue further diligence with management.

Disclosure: My employer (SVB) may do business or seek to do business with companies mentioned or their competitors. Views expressed above are solely the views of me.

Back at it

Shadysback

Greetings C:V. fam!

After a 3 year hiatus from C:V., I have decided to pick this back up again.  Excited to write again but the format will be a lot different than the #UnicornHunter days.  It will be a lot less structured but I plan to write periodically about key news items, fundings and/or other Venture related things that pique my interest.

Stay tuned!