Interview results from surveying Product Managers at API-first San Francisco companies who have revenue in excess of $100M. let's dive into API-First Product Managers’ Popular API Tools and API Metrics
We interviewed the product managers at a number of the larger API-first companies that are based in San Francisco. The companies are all publicly traded, have TTM revenue of more than $100M and are in the fields of billing, security, communications and workflow automation.
The PMs were asked what were their favorite tools and what API metrics they cared most about. Where possible we identified tools and metrics that were common across all market segments, excluding the (many) edge cases that you’d expect when your customer base numbered in the 1,000s.
Not surprisingly, our answers nicely segmented down into three classic areas: adoption, engagement and retention. Before we dive into those areas, we need to get the data into our analytics ecosystem.
One of the most consistent take-aways is that the storage and data processing required to analyze billions of APIs calls is huge. Data lakes often grow so large that retroactive analyses have to be limited to just a few days, or even the last few hours.
In many cases, the first step companies take is to dump the unstructured API data, or the entire raw dump of their syslog, into a data lake in Amazon Redshift or Splunk. From there, the data infrastructure team pulls out the syslog events the PM is interested in and passes them to the data warehouse, often in Snowflake, where it’s more easily queryable. Here, the actual processing and aggregating of metrics takes place, often under the auspices of the Business Intelligence team, the PMs and perhaps even engineers.
For the majority of api-first companies we talked to, one of the first, and arguably most important metrics that PMs track, is developer activation. In general, the steps in product adoption are straightforward:
Our cohort of established API-first companies use a Tableau or Looker dashboard that displays how many people are signing up, of those sign ups how many are logging in, of those logins how many are creating an app, and of those apps how many mint API tokens.
Predominantly PMs’ OKRs are devoted towards increasing the developer activation rate and making sure the time to activation is decreased. Since devs could stay in a single funnel stage for days or longer, it’s important to track both the conversion rate for each step, and also the time it takes to reach the next step.
If the normal sales cycle is 90 days, the PMs like to look at the quartiles: what’s the fiftieth quartile doing, what’s the seventy-fifth quartile doing, and then they use that as a proxy to determine how useful are their SDKs and documentation.
Once the API is adopted, PMs want to see usage increase leading to a paid plan, a highlighting of popular endpoints and an ability to identify missing features. At this stage the buying motion of the customer bifurcates depending on their company size: large enterprises or SMBs/startups.
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