The Business Case for a PLG Tech Stack
Adopting a Product Led Growth motion is now table stakes for software companies and it’s likely that your executive team is already sold on it. Enterprises that don’t adopt PLG and are hard-bound to a sales-only approach where one has to sit through multiple Zoom meetings just to find out the pricing, are bound to get disrupted by upstarts.
Moreover, it’s already hard to attract and retain good talent and if enterprise software companies adopt Product Led Growth only in name and are not willing to adapt to the new way of doing things, talented individuals who wish to move their career forwards are sure to move on.
The logical next step is to figure out the PLG tech stack — a set of purpose-built tools to enable your GTM teams to drive the PLG motion.
Why a PLG stack, you ask?
Because product, growth, and sales teams who don’t have access to the right tools with the right data are like musicians without instruments on a stage — they’re unable to do what they do best.
It’s more important to invest in purpose-built tools that solve one or two problems really well rather than an all-in-one solution that claims to do it all. Then, once you have the right tools implemented properly and integrated tightly, there ought to be harmony — amongst the tools as well as the teams that rely on them.
However, the PLG tooling landscape is ever-expanding and a growing overlap between tools is making the evaluation process more cumbersome — I hope to fix that via this guide.
Product Instrumentation and Warehousing
Instrumentation refers to the process of tracking customer data from your website and apps followed by syncing the data to tools and systems where data is consumed. It’s important to sync data to a data warehouse so that you own your data and amongst other things, can build data models to power reports in a business intelligence (BI) tool.
Instrumentation or Data Collection
Segment has been the go-to solution for companies large and small to start collecting data since it’s easy to implement and you can get started without a “conversation with sales”.
While Segment offers multiple products, you only need their core product — Connections to start collecting and syncing data.
RudderStack is an open source alternative to Segment Connections and offers similar capabilities to collect and send data to a host of cloud destinations including data warehouses.
Once you begin collecting customer data, it is essential to store it in a data warehouse such as Snowflake, Google BigQuery, or AWS Redshift — the three frontrunners of cloud data warehousing.
Having access to raw data in a warehouse is a no-brainer because you can do all kinds of things with this data — from analyzing, transforming and combining customer data with data from other sources to syncing enriched data to sales and marketing tools using a tool like Correlated.
And when you’re ready to build a data team and hire data scientists to extract the juice from years worth of data and build predictive models to reduce churn or build a recommendation engine, you will be glad that your data is housed in your warehouse rather than being locked inside a third-party vendor’s warehouse.
Storing raw data in a data warehouse should be non-negotiable, especially when data warehouses have become so affordable and can be spun up in a matter of hours without deep technical know-how.
Once product instrumentation is taken care of, you can begin to derive insights from data and drive action based on those insights — the two key pillars of PLG whose foundation is accurate customer data.
A product analytics tool enables you to understand how users interact with your product by visualizing their actions as funnel reports. These reports are dead easy to create once data begins to flow into your product analytics tool, allowing you to start deriving insights from product data without relying on an analyst.
You are able to analyze user behavior by slicing the data based on user personas or any other data point that you collect at the time of onboarding such as industry or role.
Doing so allows you to understand how different cohorts of users interact with your product differently, enabling you to identify the most valuable user cohorts — the ones that are the most engaged and are using the maximum number of product features.
This further enables product teams to prioritize the most-used features while growth teams are able to identify points of friction in the user journey and improve product adoption.
Amplitude, Mixpanel, and Heap are the most well-known in the product analytics category. They’re all best-in-class tools that have been around for long and are really good at what they do.
Amplitude and Mixpanel are similar in their approach to data collection — they only support explicit tracking of events where you need to specify each event and its related properties before instrumentation.
This is typically done via a tracking plan that acts as the source of truth for all the events that are collected and also contains additional details about each event. Once the tracking plan is ready, an engineer needs to implement the tracking via data collection tools like Segment or RudderStack, or in some cases, directly using the SDKs offered by product analytics tools.
Heap, on the other hand, offers autocapture, which is a codeless event tracking capability that is able to automatically track events as they take place on the website or apps where Heap’s tracking library is implemented.
Codeless tracking is also known as implicit tracking as one doesn’t need to explicitly define which events to track and what data to gather with each event. That said, you can still explicitly track events alongside those that are tracked automatically using Heap’s integration with Segment or RudderStack or via Heap’s APIs.
Product Led Engagement
To embrace a PLG motion, you need to let your product usage data inform your engagement campaigns — that’s the idea behind product led engagement.
Product led engagement typically takes place via in-app experiences and emails, both of which require tools that are purpose-built to cater to the needs of PLG companies.
To build product led engagement campaigns, you need an easy way to sync your customer data with your engagement tools. Therefore, when evaluating engagement tools, it is really important to gain a clear understanding of their data ingestion capabilities by looking at the integrations and APIs they offer.
Customer.io and Intercom are battle-tested tools for onboarding and lifecycle email campaigns, allowing growth and marketing teams to send contextual emails to users based on the events they perform or don’t perform inside your app. While Intercom can also be used for in-app experiences, Userflow and Appcues are purpose-built tools for this.
All the tools mentioned above offer APIs to ingest customer data as well as integrate with Segment and RudderStack.
Outreach is an engagement tool that is popular amongst sales teams and allows sales reps to build email campaigns targeting the right users in a particular account based on the in-app activity of those users.
The key difference between a sales engagement tool like Outreach and a marketing automation tool like Customer.io is that the former is purpose-built to cater to the needs of SDRs and offers the capability for reps to engage with prospective accounts on a 1:1 basis while leveraging the power of automation.
Sales engagement tools also offer integrations with CRMs and scheduling tools, providing reps with the context and the tools to book more meetings with prospects who are likely to convert.
It helps to keep in mind that marketing automation tools can be more complex and are usually used by fewer people while sales engagement tools are easier to use and are used by every sales rep on a team.
Tools like Outreach can be paired with Product Led Revenue tools like Correlated to enable powerful email automation workflows based on product usage.
Product Led Revenue
As PLG continues to bend the buying journey towards a low-touch sales funnel, revenue and sales teams at PLG companies are having to recalibrate how they identify and engage with prospects and customers.
Product Led Revenue is an emerging practice where the concept of leads is being replaced by trial or free users and accounts are qualified based on the in-app activity of users rather than traditional signals like company size and number of employees.
Traditional CRMs like Salesforce are not suited to cater to the needs of sales teams at PLG companies who need a complete view of an account alongside product usage data of the users in each account.
Tools like Correlated fulfill this need by enabling sales and revenue teams to use product signals to:
- Find free trials or self-service customers who are ready to engage with sales
- Identify existing customers who are ready to expand their product usage
- Automate outreach by triggering campaigns inside sales tools
Common product signals include trying new features, inviting users to an account, and hitting usage caps. Correlated makes these data points actionable for sales teams in tools like Slack and Outreach.
Correlated integrates with Segment and with data warehouses like Snowflake, allowing you bring customer data into Correlated using your preferred method.
The PLG stack that you ultimately adopt might include alternatives of the tools mentioned here. The goal of this article, however, was to offer an overview of the main categories of tools that every PLG stack must comprise, and I hope it helps a little in your evaluation process.
If you’re a PLG company and are looking to empower your revenue teams with accurate customer data, you should schedule a Correlated demo.