PostHog Handbook Library / Growth

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Cross sell motions

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At a Glance

This long page covers these main areas. The list is generated from the article headings, so it updates with every handbook rebuild.

  1. Problem statement
  2. Goals
  3. Results
  4. Measuring success
  5. Accounts that are a good fit
  6. Optimal timing for discussions
  7. Hypothetical approach
  8. The why evolve framework for cross selling

Problem statement

We haven't had a specific playbook/motion/plan on how to do cross sell, until now!

CS & TAM managed accounts historically have only been slightly better than average when it comes to product adoption. We can change this. We have the technology. We have the power.

Described here are some of the current goals and tactics to improve effective cross-selling measures when working with customers accompanied with specific how-to guidance.

Goals

The main objective is to get existing PostHog customers to adopt more of the platform. We firmly believe that adopting more products leads to a better experience and higher satisfaction with PostHog.

For a TAM today, a quantitative goal is to move from an average 4.8 products adopted currently to 6 products adopted for AM managed accounts over the next two quarters. Accounts may be promoted to CSM coverage and continue with the adoption plan.

AEs and CSMs goals might be polar opposites. Where AEs may want wide exposure, it's also important to establish the right time for product adoption, rather than overselling something that may not apply to the initial implementation.

CSMs are not here to push new products and features; CSMs are here to ensure customers successfully use PostHog and get the most value for their business. Remember, we want to help our champions look like heroes at their companies!

Results

Cross-selling has clear expected outcomes:

  1. Increase Revenue / product usage
  2. Increase stickiness
  3. Offer real value of the "platform" to users

Measuring success

Successful expansion strengthens customer relationships and increases account stickiness. Each additional product that delivers value makes PostHog more integral to the customer's operations. There are a number of things we can look at that deliver these results.

Since we have different folks at different stages of ramp and onboarding, instead of making these metrics flat or percentage based, we are looking for an increase quarter over quarter.

Accounts that are a good fit

As a part of this process you are determining whether they are a good opportunity for cross-sell motions and if they are representative of an ideal candidate for growth. Here are some key qualities we've found to date:

Optimal timing for discussions

Why Now? All good opportunities have this and are timeline driven.

Ideal moments:

Times to avoid or pause cross-selling:

Optimal timeline if a customer is on an annual contract:

Hypothetical approach

One way of approaching this that we have seen work is a research -> QBR -> recommended cross-sell

  1. Account research and understanding the business
  2. Some sort of engagement (QBRs?) to understand business priorities and tie them to PostHog
  3. Make specific recommendations around what to adopt and how it will help with business priorities

For example, customer B2C SaaS has a business model selling subscription plans. Digging in to understand the differentiators of the plans and reviewing their custom events to ensure they are collecting the appropriate data. Come to the QBR ready to discuss the particulars of their situation. You may or may not have the info you need to make a recommendation on the call, but at the very least, you should have a direction to suggest. You could recommend customer/revenue analytics, experiments for plan adoption, and surveys for user feedback given what you know about their business model.

This doesn't always need to be a formal QBR process. Some form of research -> discovery/interaction/recommendation is the basic flow here.

The why evolve framework for cross-selling

  1. Document Results
  1. Highlight Evolving Pressures
  1. Share Hard Truths
  1. Emphasize Risk of No Change
  1. Describe Upside Opportunity

The new cross-sell motions playbook

You've been here awhile and just want the script. Wet get it. The following sections describe the actual approaches that fit well within PostHog for a cross-sell motion, and can be pitched in grouping by feature or by user needs.

Remember that where possible, we're providing solutions and outcomes rather than features. Today we have clear examples with the Error tracking product where customers have found success, with more direct playbooks in the works.

Common cross-sell and expansion paths: Adoption paths are good to frame products as point in time or natural progression to their implementation. For example:

Here are some other known examples that aren't necessarily 0 to 1 linear adoption, or working backwards from what a customer is using outside of PostHog:

Bundle "Features"

Bundling is another good way to position products by customer type and stage. The following product stacks match certain types of user needs with value.

The "early stage growth" stack

Products: Analytics + Session Replay + Surveys Value story: "You know what users do, see how they struggle, and can ask them why" Ideal for: B2C companies with conversion optimization focus

The "ship fast without breaking" stack

Products: Feature Flags + Error Tracking + Experiments Value story: "Roll out safely, catch issues instantly, measure impact scientifically" Ideal for: High-velocity teams with continuous deployment

The "revenue optimization" stack

Products: Analytics + Experiments + Revenue Analytics (via Data Warehouse) Value story: "Track user behavior, test pricing changes, measure revenue impact" Ideal for: B2B businesses focused on LTV/CAC

The "vibey AI startup" stack

Products: Analytics + Flags + LLM Analytics + Error tracking Value story: "Tie user behavior to run cost, launching features that are both user requested and revenue generating" Ideal for: AI-focused startups optimizing for cost efficiency and user engagement

What to look for when cross selling

We've already seen general indicators that are worth paying attention to when it comes to success cross-selling and here is an expanded list with what to do next.

  1. New PostHog product launch - did we launch a product that is a good fit for their use case? Did we add a new data pipeline source or destination?
  2. Reach with details on the new product
  3. Offer to credit them back their first month of usage so they can try it out risk free
  4. Raising funding - did the customer just raise money?
  5. Congratulate the founder on the raise
  6. Lead with product that can capitalize on their opportunity to bring in more revenue / usage
  7. i.e. if they are B2C, pitching experiments to maximize conversion
  8. PostHog price change - did we change pricing to make adoption more palatable?
  9. Let your main point of contact know how much they will save with the new pricing if they currently use the product
  10. If they don't suggest adoption based on the new rate and offer credits to offset learning curve
  11. Revenue increase - is the customer seeing an increase in revenue?
  12. Depending on how you know about it, either congratulate them (or don't)
  13. Recommend a product that would capitalize on that revenue
  14. Error tracking to clean up issues
  15. Feature flags to launch new user features
  16. New customer product launch - is the customer launching a new product that could benefit from additional PostHog goodness?
  17. Check out the product yourself (if applicable)
  18. Congratulate them on the new launch
  19. Suggest products that would help with the success of the new launch
  20. i.e. surveys for feedback, feature flags for new features
  21. Competitor drops (or lacks) SDK support - does a competitor lack critical support or have they dropped support?
  22. Reach out proactively to main technical contact if there is overlap
  23. Mention our support (and lack of competitor support)
  24. Send any pertinent docs
  25. Follow up regularly with status updates and additional resources
  26. Eng/marketing hiring - is the customer hiring more technical roles? Could we do this through LinkedIn?
  27. Prep PostHog onboarding for new user
  28. Offer call / support for getting them up to speed
  29. Suggest products that make that new hire's life easier
  30. i.e. error tracking to figure out where the gremlins are
  31. New users from other business units - are we aware of / seeing people from other parts of the business asking about (or even using) PostHog?
  32. Make note of who the new users / units are
  33. Ask for a warm intro from current main point of contact
  34. Reach out 1:1 to new users to get feedback / offer help
  35. Customer expanding into new geography / territory - is the customer moving into a market they weren't previously in?
  36. Ensure they are capturing the correct custom events / properties
  37. Pitch products that help with differentiating location experience
  38. i.e. feature flags for unique features based on GeoIP
  39. When an owner leaves PostHog or a new owner is added - is the new owner open to other products that can help solve the problems they care about?
  40. Reach out to new owner to understand their priorities
  41. Hit any products that were previously suggested to the other owner
  42. Offer credits for adoption of the new product
  43. Shift in customer business model - is the customer introducing a new type of subscription, going from on-prem to cloud, changing their fundamental offering?
  44. Dig in to understand the changes
  45. Suggest flags / experiments as a good way to get feedback / modify the experience for the new model

Alerts

What alerts would be helpful to have that would indicate good cross sell opportunities. Continue to question what would be useful to follow in order to positively influence timing.

  1. Could we use our PostHog to flag when an account's revenue is increasing on their end? (not spend with PostHog, but their actual revenue)
  2. Could we use signals in Vitally / PostHog to notify about new power users?
  3. Could we get an alert when an account tries a new product for the first time?

Discovery through conversation

Effective discovery focuses on understanding customer challenges rather than pushing products.

Example questions to ask

The questions below are designed to spark thoughtful conversations with customers. They help uncover how teams are currently solving problems and whether there might be simpler or more effective ways to do so using PostHog.

Use these questions in preparing for calls and use them as examples for developing your own questions. Each includes the question, the pain revealed, and the PostHog advantage.

High-value discovery questions for upsell/cross-sell:

These questions will naturally surface use cases for session replay, feature flags, experiments, and other products. We should also identify opportunities programmatically through the other data sources we have to supplement the conversation approach. It's not a recommendation to ask each and every one of these questions on a call. These are simply a guide and an example of the types of questions that will help surface opportunities.

Error tracking

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | When an error occurs, how easy is it for you to see exactly which user actions led up to it and how it affected the experience? | Debugging relies often relies on reproducing error | Error Tracking tied directly to replays makes root cause and impact obvious. | | If you’ve built your own error tracking, how much effort goes into maintaining and correlating it with analytics? | Time wasted maintaining infra, blind spots in analysis. | Lightweight SDK that's tightly integrated with other products. | | How do you decide which errors to fix first? | Prioritizing by gut feeling or frequency, not business impact. | Error Tracking + Product & Revenue Analytics can show which errors have the greatest impact. |

For more recommendations, look at the Error tracking motions

Session replay

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | When debugging, how often do you rely on logs or secondhand reports to reconstruct what happened? | Time lost piecing together events. | Session Replay shows exact user journey, reducing guesswork. | | How do you confirm if a bug is isolated or widespread across users? | Hard to prioritize fixes without scope clarity. | Replays + analytics show impact | | How do you identify user friction today? | Lacks visibility into real interactions without PM background. | Session Replay gives direct user perspective for product calls. |

Feature flags

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | When launching a new feature, how do you manage risk of rollouts failing? | “Big bang” releases increase risk + stress. | Feature Flags enable safe, gradual rollouts & rollbacks. | | How do you measure whether users actually engage with a feature once it’s enabled? | No feedback loop between rollout and usage metrics. | PostHog connects flags directly to analytics & experiments. | | What’s your process for debugging an experiment if users drop off unexpectedly? | Experiments may fail without clarity on root cause. | Session Replay + Error Tracking pinpoint where the experience broke down. | | How do you currently measure the business impact (e.g., revenue, retention) of an experiment? | Results limited to engagement metrics, missing real business outcomes. | Revenue Analytics + Product Analytics + Data Warehous show both engagement and business impact. |

Customer/Revenue analytics

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | How do you measure the direct revenue impact of your features? | Work disconnected from business outcomes. | Revenue Analytics ties feature usage to revenue & LTV. | | How do you weigh roadmap decisions against revenue impact today? | Guesswork in prioritization. | Revenue Analytics reveals which features drive business outcomes. |

LLM analytics

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | When your LLM-driven features underperform, how do you pinpoint why? | No clear visibility into model errors or user friction. | LLM Analytics shows usage, performance, and cost data together. | | How do you know which LLM features are helping vs hurting users? | No clear way to measure LLM impact on user behavior or business outcomes. | LLM Analytics + Session Replay shows which interactions drive value vs cause drop-offs. | | How do you evaluate your LLM analytics in the context of broader product goals? | Standalone tools miss product context. | Integration ties LLM performance to actual product outcomes. |

Surveys

| Question | Pain Revealed | PostHog Advantage | | --- | --- | --- | | When analyzing survey responses, how easy is it to connect them to specific user behaviors or outcomes? | Responses are siloed, making it hard to correlate feedback with analytics or events. | Surveys integrate natively with Product Analytics and Session Replay, linking responses to user journeys and metrics. | | How do you target surveys to the right users without manual segmentation or guesswork? | Less targeted surveys lead to low relevance and response rates. Custom targeting requires dev time. | Display conditions use cohorts, feature flags, and events to show surveys only to specifics users, with built-in response limits. |

Expansion within existing product usage - and up-selling

It's worth calling out a question again: are we selling more of the thing, a more expensive thing, or a new thing? Cross-sell and expansion opportunities can have significant overlap in product plays.

If we're planning expansion, the best way to do this is to replicate usage of existing product with _new_ teams at the same company. This is a bit more straightforward conceptually, and may be harder to execute because you're likely to be starting with a new team from scratch.

You may want to consider expanding usage of the same product within the same team if there is obvious scope to do so here. This can also be difficult as it depends on the individual success and growth of their product, which you can't control.

Trial/Evaluation incentives

If we want customers to use more products, we should incentivize new product adoption. This could be in the form of credits for a specific timeframe to cover adoption and usage of the specific product. For example, if a customer wants to try out data warehouse, we offer 2-3 months of credit for any data warehouse usage as they figure out how they would use it and where it provides additional insight.

We have opportunities to get creative with how we incentivize new product adoption with users. A few ideas are:

Canonical URL: https://posthog.com/handbook/growth/cross-selling/cross-sell-motions

GitHub source: contents/handbook/growth/cross-selling/cross-sell-motions.md

Content hash: 7a6c4c58dd86637c