The Definitive Guide to making Intercom work for PLG
Nov 15, 2023

The Definitive Guide to making Intercom work for PLG


An effective growth strategy demands precise triggers to inspire registered users to maximize value from the product, reducing abandonment. To build an automated and efficient system requires a combination of user activity tracking and payment information along with simple multi-channel nudging tools for growth and marketing teams.

To successfully implement a product-led growth (PLG) strategy, companies need strong inbound marketing through platforms such as Google and Facebook. However, many struggle with low sign-up rates, as over 90% of website visitors do not convert to users ( Therefore, it is crucial to strengthen the user flow pipeline from acquisition through product usage to activate, upgrade, and retain your customers. Understanding where to allocate investments is key to determining success or failure within this space.


Intercom, founded in 2011, is a natural tool of choice of because of the richness and robustness of the solution for PLG companies. While analytics tools such as Amplitude and MixPanel allow the creation of segments and tracking behavior over time, integrating payment or other data can be challenging. Segment also enables profiles  creation, but the starting price may be prohibitive along with its long installation & instrumentation time, and profiles are not easily available in other tools like Intercom. Moreover, ingesting payment data into Segment is not straightforward.

Series in Intercom

Series were introduced by Intercom (September 2020), prior to that Intercom had “Smart Campaigns” that was around 2016. Series were introduced in Intercom with a focus of engaging with the customer based on their behavioral data.

To put it simply, Series in Intercom is the campaign builder. Which allows its customers to create campaigns and engage with their users through a series of cohesive messages across tons of channels. A series is made up of 4 blocks:

  1. Rule Block: This block defines the entry and exit rules of the user. There are mainly 2 sections of the rule block - “When” I.e when someone will enter that series, it is based on a trigger event. Secondly there is the “Who” I.e. the segment of users that will enter the series based on their current status, for instance - all users who are on the premium plan.
  2. Content Block: This is the block is where you create the content that your customers should receive.
  3. Wait Block: This block lets you define a specific time period, or date that must pass before customers will proceed any further through a series. Wait is added to content blocks, this way the right message is sent to the right user at the right time. There are two types of wait methods - first is “Wait for X number of days” and secondly “Wait for X times”. The prior is useful in situations when you have sent an email to the user and waiting for them to take an action on it, so you can say “wait for 5 days” and then send another fallback email. The later is useful in situations when a user you’re waiting for a user to upgrade their plan, so if their plan status changes to “paid” then that’s enough for the rule to move them in the series.
  4. Tag Block: This block lets you automatically apply / remove tags to customers as they complete their journey through a series. You can tag customers when they match the filters for a rule block, or based on interactions with series content. Tags can then be used to enter or exit customers from other series, filter your reports, define segments or build custom Help Desk view.
  • Multiple tags are allowed in the tag block.
  • You won’t be able to create a new tag in the tag block, but can use any existing tag from the workspace.

Note: By default Intercom checks every 30 minutes for each internal rule, message, wait or tag block if a user matches.

Goals in Intercom

Apart from the open and click rates that show the performance of a message and a series as a whole, each message can have their individual goals. The performance of a goal is measured by tracking the change in any set property within a specified time period of receiving that message. For instance, the goal can be set “Web sessions increased” within 3 days of receiving the message.

Similar to message goals, you can also have goals for each series, that can be set from “Show more settings” in the series.


Scheduling and Frequency: In Intercom you can schedule a message to send at exactly the right time. There are three ways you can do this in Intercom:

  • Schedule messages to send during or outside your office hours.
  • Set a specific delivery times during which your message will send.
  • Schedule a particular date and time for your message to start and stop sending.

Message Testing

To test how a message is performing in a series, Intercom offers two options - A/B Testing and Control Group.

  • A/B Testing: It is general method of testing two messages to a set of users to gauge which message is performing the best.
  • Control Group: This testing method is for higher plans and can be used to test out how a single message is performing on a particular segment of your users. For instance, if a content block has 400 users who will receive particular message, then you can use this feature to test out that message on about 20% of your audience first to gauge their reaction before sending out to everyone else on that list.

Exit Rules: Exit rules for a series can be set from the “Show more settings” option in the series. For instance, you can set a rule to exit users once their subscription changes to paid.

Company Priority

Within a series, there could be users who are part of multiple companies (Intercom does notify you about the number of such users in a series), so you prioritise the messages to be sent to these users based on the two criteria:

  • Send a copy of each message for every matching company. This means that a user will get all the different messages you’ve created for every matching company. For instance, a user is associated with two companies. One with 50 employees and other with 200 employees. You have created rules to send different messages for companies with less than 100 employees and for over 100 employees. The user will match in both the rules and will receive both the messages.
  • Send each message only to the highest priority matching company. This means that a user will get a message for only that company for which you’ve set the highest priority. Let’s try to understand this with an example. You have set a priority to send a message to companies who have their web sessions “descending”. So following the previous example, if any of the companies will have their web sessions in “descending” then they’ll receive a message accordingly.

Can we make it better? 

Overtime, the sheer amount of segmented data from precise event filtering can quickly spiral out of control.  (as seen in the picture on the right).

  1. Ease of Creation: Currently, creating lists (of contacts) and connecting them to workflows is a manual process in Intercom. Creating useful filters that move your north start metrics requires significant cognitive load. Creating filters is necessary but not great at allowing you to visualize if the filters you created are the right ones to drive revenue goals.
  2. Trends: Once a persona is created it's important to be able to track it over time and see how it's behaving, to quickly test & validate your growth experiments.
  3. Organization: Its important to be able to easily organize the persona's into Stages such as Trial, Active, Churned and Never Converted to build your PLG User Journey, exactly where you organize the personas that are taking the journey.
  4. Dark Pipeline: In the persona creation exercise its also important to know how many users are not in any persona, to create additional campaigns to interact with this untapped, unengaged group of future users.
  5. Persona Transition: Its also important to know the change over time across persona's and change per stage
  6. Synchronization: Once created in a tool these personas should be easily available in any other marketing tool automatically in a single click

Filters are a measurement of where a user might have been in time, versus personas that show the efficacy of your outreach over time as a user progresses from newbie to power user.

Data-drive personas that show user journey & product adoption, allow for stronger marketing & revenue campaigns, increase conversion rate, drive profitability, and create better feedback loops through sales, customer success, growth, marketing, and product.To effectively manage this complexity, an ideal solution requires several features listed below.

Finally, Revenue teams need the ability to connect personas to an outcome that they want to drive. So for example if you want to drive 1% increase in engagement which persona(s) should you be targeting, which tool should be used, when should that outreach occur, and who should do that? This is complex undertaking for a team without several dedicated Machine-Learning personnel & resources waiting to do that complex work.