Marketplaces: Scaling with Operations vs Engineering?

There are many things that make building and scaling marketplace businesses hard: for example, there’s the quintessential chicken-and-egg problem of building and balancing supply and demand, and there’s the need to build two or more products in parallel to serve the needs of the different participants in your marketplace.

There is also the question of how you scale your marketplace once you’ve got product-market fit established and some unit economics that seem to work.

Electrons vs Atoms

Most marketplaces have to deal with the tangible, real world: unlike pure software/SaaS companies, marketplaces have to deal with whole atoms, rather than just electrons.

Those atoms might make up people, or cars, or meals, or apartments but they are physical resources that have to be managed. This is why marketplaces tend to need significant operational headcount.

However, most marketplace companies aspire to be, and actively position themselves as, technology platform companies.  This of course requires an ongoing investment in product/engineering.

Given finite resources, how do you choose between scaling a market place through operation headcount versus product/engineering investment?  How do you strike the right balance?

The Comparables

I did some quick research to look at what other marketplace businesses are doing.

I took a basket of marketplace companies at varying funding stages and looked at their employee counts on LinkedIn by role.

Firstly, let’s set the scene by looking at the absolute number of engineers that various marketplaces have and compare that to their funding stage:

Perhaps no surprises here: as marketplaces develop, they hire more engineers. I am struck, though, by the widely varying number of engineers that the earlier stages marketplaces seem to have.

Now let’s look at the ratio between operational headcount and engineering headcount in these same companies:

This is also what you might expect.  Although the data is noisy*, it seems that as marketplaces grow, they become less dependent on operational headcount. Presumably, their investments in product/engineering payoff in terms of automations and efficiencies.

Of course there’s also survivorship bias here – these are only the marketplaces that are still around. Perhaps the ones that didn’t make it had wildly different ratios.

What would be great is to get historical data on these ratios and see how that correlates with outcomes. Unfortunately, I don’t have that data (if you do, let me know!).

My bet would be that a higher ratio of operational to engineering headcount is hard for marketplaces to wean themselves off – i.e. it’s hard to change the ratio over time.  If you organization gets accustomed to scaling and solving problems by hiring ops people rather than hiring engineers to automate, that just gets amplified over time.

* my methodology here was simply to search on LinkedIn for people with “engineer” and people with “operations” in their job title. This is obviously error prone for a number of reasons.  For example, some “engineering” roles have “operations” in their job titles, and not all headcount are necessarily on LinkedIn, especially if a company outsources or off-shores some functions. However, given a sufficiently large sample set, one would hope that these effects blend out.

Brute Force Growth vs Long-term Value

Like any business, marketplaces have to continue to show top-line revenue growth in order to maintain the faith of investors and employees and be able to continue to raise money.  The first, second, and third rules of business are “don’t run out of money“.

However, while it’s possible to “brute force” growth of many marketplaces through reliance on operational headcount in the short to medium-term, I believe this strategy has large associated dangers in the longer term.

In a perfect world, you could scale both operational and product/engineering headcount as needed but, in reality, you will be forced to choose between spending each $1 on one or the other. Here’s my quick take on the pros and cons:

In summary, the biggest danger with scaling by adding operational headcount is that it works…in the short-term.  It’s also cheaper.  But, the danger is that you win the battle but not the war.

Agree or disagree, please leave a comment.

Are you confusing Optimization with Growth?

Are you confusing Optimization with Growth?

In a startup, there are always many things that aren’t working as efficiently as they could be – acquisition funnel conversion, manual processes, customer acquisition costs, etc.  This may be incredibly frustrating, especially for the team members who have to deal with it on a day-to-day basis.

It’s very tempting to direct precious money, time, and energy to resolving these frustrations, especially as its your team’s tired faces that you have to look at every day.  It’s always tempting to give the squeaky wheel some oil.

However, it’s vital that you remain focused on growth and don’t confuse growth with optimization. Burning lots of time optimizing at the expense of growing is not a recipe for success for early- to mid-stage, venture-backed startups.

Of course, there is some nuance here: if things are so broken that your team starts to leave, you have to address that – no team; no company.

Also, the smart investors (i.e. the ones you want) realize that, if your unit economics fundamentally don’t work, you will simply lose more money as you grow.

However, conversely, it’s unlikely that a Tier 1 investor will invest in the also-ran, #3 player in any category in terms of growth rate and/or absolute revenue, however optimized and healthy the acquisition funnels, gross margins, etc. Investors are in the business of selecting for the biggest return on their capital, not the best run or most efficient business.  The biggest return comes from the biggest exit and the biggest exit goes to the category winners.

As a venture-backed startup, the most important thing is to stay as one of the leaders in your category – this is what allows you to maintain team confidence and morale, attract the best talent and investors, and continue to raise money when you need it.  Note: there are usually only 1 or 2 “leaders” in any category.

Let’s take two startups:  to start with, Company A and Company B are neck-and-neck.  Both have a $5M in gross revenue, with a average revenue of $5,000 per customer per year and a customer acquisition cost (CAC) of $2,000.  Both have revenue that is doubling each year.  Both are mid-stage startups – they’re not yet profitable and don’t expect to be any time soon.

Both companies also know that their CAC is too high and, by some optimizations, the CAC can be reduced significantly.  The high CAC drives some members of the team crazy – so many opportunities lost, so many wasted marketing dollars.

So, the CEO of Company A directs the team to work on CAC.  Over 6 months, they manage to effect a series of changes process and product changes in their customer-acquisition funnel, through A/B testing, cost reduction, etc.  These compound and end up halving the CAC to $1,000 – that’s a huge improvement.  Company A’s gross margin has significantly improved.

Meanwhile, the CEO of Company B ignores the CAC for now and instead directs the team to focus on increasing the size of the sales and marketing teams significantly and filling the top of the sales funnel with as many leads as possible.

One year later, Company A’s revenue has doubled again and they’re netting an average of $4,000 per customer per year – 33% more.  Not bad.

However, by focusing on growth, one year later, Company B’s revenue has tripled rather than just doubling.  They still net an average of $3,000 per customer per year but there are 3 times more customers.

Both Company A and Company B need to raise more money.  So does a 3rd player in the category; Company C.  Company C is going gang-busters, beating both Company A and Company B on growth rate and total revenue.

You know how this story ends:  Company B and Company C are able to raise giant C-rounds from Tier 1 investors at great valuations.  Meanwhile, Company A has fallen behind – its unit economics are better than Company B’s but it’s now an also-ran and struggles to raise money.  Without that money, it cannot continue to grow and falls further and further behind Company B and Company C.  Perhaps it’s acquired by Company C at a fire-sale valuation or perhaps it’s a giant smoking crater.

Of course, this is a contrived story.  In reality, you can probably achieve growth and some optimization in parallel.  But, the key is not to confuse one with the other.

So, grow and optimize as you go, as long as that optimization doesn’t slow your growth.  Don’t optimize hoping that it will deliver meaningful growth.

tl;dr – in a startup, you can’t optimize your way to success – you must out-grow your competitors.