5 Q’s platform investors would like to know?

You need to answer critical questions and document that your business model has a good liquidity to convince your investors. To make this article easier to apply in practice, we have two user groups; consumers and producers. In addition, we have one core transaction and no assessment of the value of an ecosystem with complementors and partners.

Q1: What stage is your platform company?

What investors look for depends on what stage your platform company is in. Before market fit, before or just after the launch, it is like looking at any other new company. Then the idea and the team are the essential focus areas for investors. 

After launching and approaching the market fit, the investors also look for proof of market size potential and that you have enough selection. Here current demand and liquidity are not that important yet. There should be possible to prove that the selection is good enough for the consumer to get on board, and there should also be likely to show that a producer (a service supplier) can get a good living wage.

Note: Many platforms don’t know what stage they are in, especially whether or not they have passed the important market fit stage!

Q2: Is your company a digital broker or an actual platform marketplace?

Companies that do a lot of the manual work (e.g., manual matching and tailored offerings) during the matchmaking process rather than naturally let the buyer and seller match on their platform are more like digital brokers than marketplaces. In a marketplace, buyers and sellers should naturally match on the platform without interference. (This is not necessarily the case with B2B market platforms.)

Marketplaces are an intermediary; they are a platform for matching buyers and sellers. So it’s okay if a company relies on short-term assets to kickstart its marketplace. Still, if long-term assets on the balance sheet and manual processes are their sustainable advantage, it is not an actual platform marketplace.

Q3: Can you show the numbers as a digital platform, not only a broker?

If you want to show proof of scale and that you are a true digital platform, there should be possible to prove that you can pivot to a low-to-zero marginal cost on a transaction due to Network effects. This includes onboarding producers, getting new consumers from search to fill, and recurring transactions (retention rates). It would be best to visualize new users and retention rates from both sides with foci on conversion, with a time and cost frame. I will recommend using cohort analysis to visualize these liquidity KPI’s.

Cohort analysis is a behavioral analytics subset that takes a data selection from a more extensive dataset within a specific period. Instead of looking at all users within the data as a single unit, cohort analysis splits them into smaller (related) groups based on various attribute types within a given timeframe.

Q4: Can you visualize good retention rates and usage rates?

One way of showing healthy liquidity and retention rates is to establish a time and cost perspective for both sides of the core transaction. For example, try to visualize “time to fill” on the consumer side and “time to utilize” on the producer side. In addition, it would be best to find a good way of showing retention rates on both sides within a timeframe and and cost. (cohort analysis).

With new producers, try to visualize time and cost to first and second transaction (cohort), and then secondly a new cohort curve with producer stock by volume tires, e.g., first transaction, Second, <5, <10, <25, <50 transactions and “full-timer”) To ensure this cohort analysis, you should have defined what a “full-timer” (full utilization of a producer) is. For example, for Uber, this could be that a driver has 40 rides a week. 

On the customer side, you should try to show conversion rates in a time and cost perspective (cohort) with “search to fill” and retention rates or usage. For example, this could be convention rates from search/download apps to completing a Uber trip. And then show retention with first, second, third trips with Uber.

Q5: Will your marginal cost go down due to network effects?

The aim is to show marginal cost on a transaction as volume increases.

With the producers try to show the cost related to a “producer lead” to the first transaction, and another curve with cost related to volume tires (1,2,5,10,25,50 transactions)

On the customers, try to show the cost on the first job and recurring transactions. Then, show the total marginal cost on the core transaction. (Fixed cost, marginal cost, marginal revenue (Cost (y) vs. quantity (x)) The important thing is to be able to aggregate total figures on marginal cost vs. volume.

Warning: The marginal cost argument will not stick with high fixed costs!

Experience also shows with platform companies that without enough time to replace, upgrade or sell fixed costs to react to an even larger volume, the economies of scale can eventually reverse, and the marginal cost goes up with increased production volume. We see this especially with platform companies that invested in assets and resources (e.g., sales and marketing) to grow and can’t defend this with increased volume. The key with platforms is to reduce marginal cost with quantity due to network effects. Sales and marketing costs should not grow with quantity since we have network effects. If we don’t learn to move the cogwheel with network effects, the marginal cost will increase with quantity, limiting scaling and profitability.