---
title: Get new users to value faster
description: Find the first result that turns a new signup into a paying customer, see where new users stall before they reach it, and fix the signup page, onboarding, trial, and onboarding emails so more of them get there sooner.
slug: /use-cases/user-activation
page_type: use-case
lead_prompt: How do I get new users to value faster with AI?
target_prompts:
  - Can an AI marketing agent get new users to value faster?
  - How do I improve user activation for my product?
  - How do I shorten time to value for new users?
  - Why don't my free trial users convert?
  - How do I improve my onboarding emails?
entity: Kite
category: AI marketing agent
author: Devon Wells and Kite
date_published: '2026-11-10'
date_modified: '2026-11-10'
related_integrations:
  - /integrations/posthog.md
  - /integrations/mixpanel.md
  - /integrations/amplitude.md
  - /integrations/stripe.md
related_playbooks:
  - /how-to/see-which-product-behaviors-lead-to-paid-customers-with-posthog-stripe.md
  - /how-to/see-which-signups-become-paying-customers-with-stripe.md
  - /how-to/find-where-users-drop-out-of-your-funnel-with-posthog.md
  - /how-to/find-where-users-drop-out-of-a-mixpanel-funnel.md
  - /how-to/find-where-users-drop-out-of-an-amplitude-funnel.md
---

# Get new users to value faster

## Key Takeaways

- New users reach value when they get their first real result from your product, and the fastest way to find that moment is to look at what your paying customers did in their first few days.
- Kite matches the people in your product analytics to the customers in Stripe to find the early actions that paying customers have in common, then treats reaching those actions as activation.
- Kite builds the funnel from signup to that first result in PostHog, Mixpanel, or Amplitude, finds the step where new users stall, and uses recordings, paths, surveys, and errors to work out why.
- Kite fixes what it finds: it rewrites the signup and landing pages, writes onboarding emails that react to what each user has done, drafts in-product copy, and recommends changes to your trial or free plan.
- Kite tests the changes where it can, then measures activation and trial-to-paid conversion again to see whether more new users got to value, and how much sooner.

## Why new users drift away before they see what your product can do

Most signups don't leave because they decided your product was bad. They leave because they never got far enough to find out. Someone signs up, lands on an empty dashboard, gets a welcome email that lists six features, and closes the tab meaning to come back later. By the time the trial ends, they've forgotten why they signed up.

Getting new users to value faster is about shortening the distance between signing up and that first real result. For a reporting tool, the result might be the first report with real data in it. For a design tool, it might be the first file shared with a teammate. Activation is the share of new users who reach that point, and time to value is how long it takes them.

The work follows a clear order:

- define the first result that predicts a paying customer
- measure how many new users reach it and where the rest stop
- work out why they stop
- fix the pages, onboarding, trial, and emails in their way
- measure again.

It sounds simple, but most teams never get past the first step. They track signups and trial conversions and guess at everything in between. That middle stretch is mostly analysis, writing, and testing, which is work an AI marketer is well suited to do.

Kite is an AI marketer. It researches your business, builds a growth strategy, and ships the work that brings you new customers. Here's how it gets more of your new users to value, and gets them there sooner.

## How Kite gets new users to value faster

Kite starts with the question most teams skip: what does a new user need to do to become a paying customer? It connects to your product analytics and to Stripe, compares the first days of people who paid with the first days of people who didn't, and proposes a definition of activation built from those differences. You agree on the definition before anything else happens.

From there, Kite builds the funnel from signup to that first result. It finds the step that loses the most new users, checks that the drop is real and not a tracking problem, and looks at what those users did right before they gave up. It also reads your website from the outside, the way a new visitor would, to see whether the signup page and the trial set people up to succeed.

Then Kite does the work. It rewrites the pages that set the wrong expectations, writes onboarding emails that respond to what each user has or hasn't done, drafts the copy for onboarding screens and empty states, and sets up experiments to test the changes. Once the changes are live, Kite measures activation, time to value, and trial-to-paid conversion again, and plans the next round from what moved.

### Decide what "value" means for your product

Kite defines value by what your paying customers actually did, not by what your team hopes new users will do. Many teams pick an activation event by instinct, such as "completed onboarding," and then spend months moving a number that has little to do with who pays.

When your product sends events to PostHog and your payments run through Stripe, Kite matches each person in PostHog to their Stripe customer, usually by email address or account ID. It then compares what paying customers did in their first days with what everyone else did. Say almost every customer who paid connected a data source and invited a teammate within three days, while most people who churned never connected anything. That pair of actions is a far better definition of activation than finishing a product tour.

Stripe also gives Kite your baseline. It reads each signup's subscription to see whether they're trialing, active, or canceled, which gives you a real trial-to-paid rate broken down by plan and month. If your team has already written down what "activated" means in Mixpanel, Kite reads that definition and starts from it instead of guessing from event names.

**Related Playbooks**

- [How to see which product behaviors lead to paid customers with PostHog, Stripe](/how-to/see-which-product-behaviors-lead-to-paid-customers-with-posthog-stripe.md): Line up product events with Stripe customers to find the early actions that paying customers have in common.
- [How to see which signups become paying customers with Stripe](/how-to/see-which-signups-become-paying-customers-with-stripe.md): Get your real signup-to-paid rate, broken down by plan and by month, as the baseline every later change is measured against.

### Measure how long new users take to reach value, and where they stop

Once you've agreed on activation, Kite builds a funnel from signup to that first result and finds the step where the most new users give up. A typical funnel might run from account created, to first project created, to data source connected, to teammate invited. Kite reads the conversion rate at each step and limits the funnel to new users, so returning customers don't hide a problem with first-time users.

The overall rate rarely tells the whole story, so Kite splits each step by one property at a time, such as device, plan, country, or the campaign that brought the user in. That's how "activation is down" becomes something specific, like "new users from one paid campaign stop at connecting a data source." In Amplitude, Kite also reads how long the users who convert take to get through the funnel, and in Mixpanel it measures how long people take to go from their first visit to activation. Either way, that's your time to value in plain numbers.

Before Kite trusts a sudden drop, it checks the tracking. It looks for events that stopped arriving after a release, duplicate event names, and steps that have no event at all. When a step has no event to measure it, Kite can create one in PostHog, or add it to your Amplitude tracking plan with a clear description so your developers know what to build. A step that broke because of tracking gets a tracking fix, not a new onboarding flow.

**Related Playbooks**

- [How to find where users drop out of your funnel with PostHog](/how-to/find-where-users-drop-out-of-your-funnel-with-posthog.md): Build the funnel from your PostHog events, find the step that loses the most new users, and see the recordings and paths behind it.
- [How to find where users drop out of a Mixpanel funnel](/how-to/find-where-users-drop-out-of-a-mixpanel-funnel.md): Find the weak step in a Mixpanel funnel and split it by device, plan, or campaign to see who is stalling.
- [How to find where users drop out of an Amplitude funnel](/how-to/find-where-users-drop-out-of-an-amplitude-funnel.md): Find where new users drop out of a key journey in Amplitude and how long the ones who convert take to get through it.

### Find out why new users stall

Knowing where new users stop is half the answer, and Kite gathers the evidence to explain why. It reads the most common paths before and after the weak step, so it can see where people go instead. If new users who abandon the data-source step keep opening your security page, that's a strong hint about what they're worried about.

In PostHog, Kite searches session recordings for the people who dropped off and reads the error tracking for that step, so a connect button that breaks in one browser shows up as a named error rather than an unexplained dip. It can also ask new users directly. Kite writes a short in-product survey for people who signed up but never reached the first result, targets it to that group, and launches it once you approve. It then reads the answers and summarizes the themes.

Kite also looks at your product from the outside, the way a new visitor would. Its growth report checks whether someone can try your product without talking to sales, whether your free plan or trial lets a user complete the product's main job, and whether your documentation and tutorial videos help a new user get there. A trial that holds back the one feature people signed up to try will stall new users no matter how good the onboarding is.

### Fix the signup page, the first run, and the trial

Kite fixes the parts of the experience that stand between a new user and the first result, starting with whichever one the evidence points to. The cause is often earlier than teams expect. When a landing page promises one thing and the product opens on something else, new users arrive confused before onboarding has a chance.

On your website, Kite rewrites the signup and landing pages so they set accurate expectations and tell people what to have ready, such as the data source they'll need to connect. It publishes those changes directly on a site it hosts, or through your connected content system if your site runs somewhere else.

Inside your product, Kite writes the copy for onboarding screens, empty states, and upgrade prompts, aimed at the one action that leads to activation. An empty dashboard that says "Connect your first data source to see your numbers here" does more than a tour of every menu. Your team builds the new copy into the product, or Kite tests it as an experiment, as described below.

Kite also recommends changes to the trial itself. If paying customers typically take nine days to reach the first result and your trial lasts seven, Kite shows you that gap and proposes a fix, such as a longer trial, a free plan that includes the main job, or onboarding that gets people there inside the trial window.

### Improve your onboarding emails

Onboarding emails work best when each one responds to what a user has or hasn't done, and Kite writes them that way. Most onboarding sequences send the same email on day one, day three, and day seven, whether the user has already reached value or hasn't logged in since signing up. Kite maps each email to a moment in the user's progress, such as signed up but never connected a data source, activated but never invited a teammate, or three days left in the trial.

Kite writes the sequence in your brand voice, using what it knows about your product and customers. Each email asks for one next step toward the first result, explains why it matters, and links straight to the place in the product where the user takes it. Kite also writes the activation and feature-discovery emails that follow once someone is up and running.

If your team sends email through PostHog workflows, Kite builds the email templates and the workflow that sends them, triggered by an event such as a signup. It runs a test before anything goes live and turns the workflow on after you approve it. Kite judges each email by whether the people who got it went on to reach the first result and pay, not just by opens and clicks. In Amplitude, for example, it can tag each recipient with the email's name, so later funnels can compare the users who got it with the users who didn't.

### Test the changes and measure activation again

Kite tests the changes it can and measures every change against the baseline you started with. In PostHog and Mixpanel, it sets up an experiment for a change such as a new onboarding screen. It first estimates how long the test needs to run with your traffic, then launches it once you approve, reads the results as they come in, and recommends a winner. Your product shows each version by checking the experiment's feature flag.

After a change ships, Kite rebuilds the same funnel, reads the time to value again, and checks Stripe for the trial-to-paid rate. It marks the date of each change on your PostHog or Amplitude charts, so anyone who opens the activation chart later can see why the line moved.

The results decide what Kite works on next. If the data-source step improved and the teammate-invite step is now the biggest drop, the next round starts there. Kite can also deliver an activation readout every week. If your product sends signup events to PostHog, Kite can follow new signups as they happen and tell your team about one that needs attention right away.

## What you get

- **A definition of activation.** The early actions that paying customers have in common, drawn from your own analytics and Stripe data, which you agree on before any work starts.
- **An activation funnel with your baseline.** The share of new users who reach the first result, how long it takes them, the step where most stop, and your current trial-to-paid rate.
- **An explanation of why new users stall.** The paths, recordings, errors, and survey answers behind the weak step, plus what your website and trial look like to a new visitor.
- **The fixes themselves.** Rewritten signup and landing pages, copy for onboarding screens and empty states, recommended trial changes, and an onboarding email sequence tied to what users have done.
- **Experiments and a before-and-after comparison.** Tests of the changes where your tools support them, followed by the same funnel and trial-to-paid numbers measured again.

## How to get started

You can work with Kite in your browser or in Slack. Start by telling Kite what you're seeing in plain language. You might say, "Most of our trial users never come back after the first day," or "Figure out what our paying customers do in their first week that everyone else doesn't."

Kite already knows your product, pricing, and customers from its research on your business. It proposes the date range, the events it will compare, and a first definition of activation, and it sends that plan to you to change or approve before it runs anything.

Connect PostHog, Mixpanel, or Amplitude so Kite can see what new users do in your product, and connect Stripe so it can see who pays. Without product analytics, Kite can still review your signup page and trial from the outside, measure trial-to-paid conversion in Stripe, and write your onboarding emails, but it can't see where inside the product new users stop.

Kite proposes work by default. It asks before it publishes a page, launches an experiment or survey, or turns on an email workflow, and you approve with a reply or the Approve button in the conversation. As you come to trust its work, you can give it more autonomy.

## Integrations used to get new users to value faster

Activation work needs two kinds of data: what new users do in your product, and which of them go on to pay. Connect the product analytics tool your product already sends events to, then connect Stripe so Kite can tie behavior to revenue.

### See what new users do in your product

- [PostHog + Kite](/integrations/posthog.md): Build the activation funnel, read recordings, paths, and errors behind the weak step, run surveys and experiments, and send onboarding emails through PostHog workflows. You connect PostHog through OAuth.
- [Mixpanel + Kite](/integrations/mixpanel.md): Build funnels and retention from your Mixpanel events, read your team's existing definition of activation, measure time to activation, and run experiments on the fix. You connect Mixpanel through OAuth.
- [Amplitude + Kite](/integrations/amplitude.md): Find where new users drop out of a key journey, read how long converters take, tag the users who received an email, and mark each change on your charts. You connect Amplitude with its API key and secret key.

### See which new users become paying customers

- [Stripe + Kite](/integrations/stripe.md): Match signups to Stripe customers, read trials and subscriptions for your real trial-to-paid rate, and give Kite the list of paying customers it compares against everyone else. You connect Stripe through OAuth.

## Common questions

### Why don't my free trial users convert?

Most trial users who don't convert never reached the product's first real result before the trial ended. The usual causes are a trial that's shorter than the time it takes to get set up, a free plan or trial that holds back the main job people signed up for, a signup page that sets the wrong expectations, or onboarding that explains features instead of getting users to one result. Kite checks each of these against your data, starting with how long paying customers take to reach the first result compared with your trial length.

### Should I make my free trial longer or shorter?

It depends on how long your new users take to reach the first result. If most people who become customers get there in two days, a 30-day trial mostly gives everyone else time to forget about you. If they need nine days and your trial lasts seven, many good customers run out of time. Kite measures how long converting users take to reach activation and recommends a trial length, or a change to onboarding, based on that number.

### Can I improve activation without product analytics?

Partly. Kite can review your signup page, free plan, and trial from the outside, rewrite pages that set the wrong expectations, write a better onboarding email sequence, and measure trial-to-paid conversion in Stripe. To see which actions predict a paying customer and where new users stop inside your product, Kite needs your product to send events to an analytics tool such as PostHog, Mixpanel, or Amplitude.

### Can Kite change the onboarding screens inside my product?

Kite writes the copy and plans the changes for onboarding screens, empty states, and upgrade prompts, and it sets up the experiment that tests them in PostHog or Mixpanel. Your product shows each version by checking the experiment's feature flag, so your developers connect the new screens to that flag. Kite then reads the results and recommends which version to keep.