Analysing Docs Data for Developer Led Sales
How to use your amazing developer docs to find high intent accounts
A matured GTM motion has always started with intent. GTM leaders want to target accounts that are already interested in them to improve the efficiency of GTM efforts. Interestingly, intent sources in B2B marketing have not changed in the last 15 years.
Source: Gartner
The majority of these intent signals is around content and topics, where marketers track accounts from where they are getting website traffic (using IP reveal mechanisms) or accounts where employees are reading about topics core to the marketer on third party sites (using third party intent data)
But for Developer focused companies, the most important intent signals are in developer activities around their product. These signals are completely different from the intent signals marketers have been tracking in the past. These signals include activities where developers trying out the product, reading developer docs, trying example code, installing package managers, doing activities in sandboxes, participating in communities and more.
Deriving intent from Developer Docs
In this post want to focus on a very obvious but perhaps the most ignored intent signal of developer interest, and that is the traffic and activities on the developer documentation (docs) of a developer focused company.
At Reo.Dev we mine developer intent for many developer focused company and have been amazed by the intent signals on the documentation. Our analysis across all our users show that amongst all channels developers engage with a product, docs get highest amount of traffic.
We also see that docs traffic is much more relevant for developer focused companies than website traffic. Our analysis on the traffic on docs vs website data shows that the accounts / organizations who visited the docs had more developers and hence were a better fit for the developer focused companies than accounts who visited the websites, where the traffic was more generic.
In retrospect this sounds very logical too as docs are very specific to the problem the product solves. They are not created to attract traffic, generally not built after analysing keyword search trends; but with the idea of helping someone get educated about the product or the problem it solves.
How to analyse docs data
Analysing website traffic is nothing new. There are bunch of tools such as clearbit, leadfeeder, that help you in IP revealing (so you understand people in a certain organization are visiting you webpage) and more such as Google Analytics, Mixpanel that give you webpage analytics.
However analysis of docs data is different from the website data because the way content is consumed by a business user is very different from a technical user who will go very deep into the content if interested.
Hence once you have planted an IP reveal tool in your docs, here are a few ways to get the most intelligent intent signals from your docs.
Understand the usage patterns from an account over a period of time
Developer marketers want to know what is the right time to get in an account. They provide a free tool (via developer/ trial version, sandbox or open source) to the developers and want to use it to get into an account with a sales opportunity, the challenge being it is very difficult to know the right time to get into an account where the developer activity is maturing.
Analysing your technical docs traffic is a great proxy for understanding the maturity of developer intent. Generally the dev adoption journey start with a single developer playing around with your product and in that journey the developer spends time on the docs to understand the product better; and then if the tool gets internal adoption, more developers start spending time on your docs.
Thus tracking this spike in your docs usage will help ensure you hit the right time to outreach the buyers when the developer evaluation has matured.
Understand developers interactions with your docs
Developers who are serious about a product won’t just read the documentation but interact with it on a code level. They will install package managers or execute docker commands and code examples. They will search for stuff, copy code block and text / content to share with other developers.
Such interactions are unique to developers and tracking them can help you find the account where developers are really active on your code, thus helping you get stronger intent signals
Prioritise accounts based on key sections/ pages of the docs.
Since developers are going through your docs to educate themselves about your product and guide their usage, the sections of the docs they are spending more time is a great signal to know where the developers in that account are in their trial journeys. By analysing whether they are spending time on references, guide and tutorials, getting started or any other similar sections of your docs can be a great intel for interpreting intent.
Triangulate developer intent from docs with your product signups
For Developer tools with a PLG strategy finding the right lead from product signups, with desired intent from a company that is worth going after can be like finding a needle in the haystack. Marketers look as a signup as a purchase intent and bombard developers with marketing mailers and sales messaging.
But product usage data married with the docs usage data can help you create a more relevant playbook where you can form a comprehensive picture of an account and purchase stage. Thus it become much easier to understand if the developer leads from product signups are in their research stage, POC stage or at a stage where they have qualified the product internally and could become great champions to getting warm account intros.
If you are looking for a tool to do all of the above, try Reo.Dev. We believe there is tremendous wealth in developer activities data around your product and are building a GTM OS for mining such data for Developer Led GTM.