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Specialized, goal‑oriented AI experts embedded in Amplitude that can surface insights, investigate issues, generate hypotheses, recommend actions, and carry out actions you approve (e.g., run an experiment or send targeted guidance).

Automatically analyzes an Amplitude dashboard to produce prioritized insights and recommendations, including patterns/anomalies and root-cause deep dives, with optional scheduled notifications to Slack/email.

Amplitude Model Context Protocol (MCP) server that lets you query and create Amplitude content (charts, dashboards, experiments, cohorts) from MCP-compatible AI tools using natural language.

Conversational interface that lets you create/edit charts from natural language, search org content (charts/dashboards), navigate Amplitude, and get help using the product.

Automatically captures a predefined set of website/app interactions with minimal setup (e.g., sessions, page views, clicks, form interactions, file downloads, and marketing attribution).

Create and edit labeled events with no new code by clicking elements on your site; labeled events can work retroactively against historical Autocapture data.

Codeless data governance for planning events/properties with automated event-schema QA, sensitive-data ingestion rules, and instant schema fixes (e.g., naming conventions/duplicates) without changing underlying data.

Keeps Amplitude aligned with your warehouse by supporting INSERT/UPDATE/DELETE operations on event data via Mirror Sync strategies (e.g., Snowflake/Databricks/S3).

Run analyses directly on data in your own data warehouse (Warehouse-native Amplitude), including building custom analyses from data models that live in the warehouse.

Join customer profile data from your warehouse as “standalone” (eventless) user profile properties that stay synced with the latest warehouse values.

Role-based Access Controls (RBAC) to centrally manage roles/permissions/actions so administrators can scale access management across products and projects.

Restrict access to sensitive data categories (e.g., PII/revenue data) so unauthorized users can’t view or build analyses that include restricted properties, and restricted values appear as "[DAC Restricted]".

Catalog of data & marketing integrations covering sources/destinations and multiple connection types (e.g., raw events, cohorts, event streaming, SDKs, and APIs).

Unify customer data across your ecosystem as part of Amplitude Activation (connect product + marketing + warehouse data to power activation).

Resolve customer identities across touchpoints to build unified customer profiles for analysis and targeting.

Visualize trends and compositions in event/cohort/profile data with multiple chart types; includes advanced capabilities like formulas, comparisons, and generating custom events/properties.

Analyze multi-step conversion journeys, measure conversion rate/time-to-convert, and pinpoint where users drop off in key flows.

Measure how users return after an entry action to quantify retention and loyalty across cohorts over time.

Explore how users move through your product by analyzing paths/behavior sequences to understand common journeys.

Quantifies correlation between a “goal event” and other events to identify behaviors associated with higher retention/conversion.

Measures the effects of product/marketing launches on KPIs by comparing adopters vs non-adopters and tracking adoption over time.

Watch playbacks to understand the “why” behind drop-offs, filter replays using Mixpanel events/properties/cohorts, and use replays across web + mobile apps (and even tied to backend/warehouse events).

Visualize hot spots, dead zones, and missed opportunities on web pages, connected to analytics and replays in the same workflow.

Privacy-first Session Replay with client-side masking/blocking (so raw sensitive data isn’t collected) plus configurable controls for what to unmask/unblock.

Web autocapture to collect common frontend interactions with minimal setup (page views, clicks, form interactions, scrolls) plus attribution and frustration signals like dead clicks and rage clicks.

Codeless syncing of warehouse data (e.g., Snowflake, BigQuery, Databricks, Redshift, Postgres) into Mixpanel so teams can analyze product + business data together.

Keeps Mixpanel in sync with warehouse changes, including reflecting updates to historical records when events are modified or deleted in the warehouse.

Hybrid data capability to apply clickstream context (like UTMs) onto warehouse events (like confirmed signups) without engineering lift.

Continuously export Mixpanel data (events, user profiles, identity mappings) to cloud storage buckets or data warehouses for SQL analysis in your environment.

Visually define cohorts from behavior sequences and/or profile properties, compare them in analysis, and manage cohorts alongside other saved definitions.

Automatically captures user interactions from install onward (e.g., clicks/taps/swipes/pageviews/form fills) so teams don’t need to pre-plan tracking or rely on engineers for instrumentation.

Because Heap captures from day one, teams can answer new questions on historical data without waiting for new instrumentation/data to collect.

Smart Capture for mobile apps (no tagging) with broad framework support (native + cross-platform) to collect mobile behavioral data quickly with less code and maintenance.

Supports combining Smart Capture/Autocapture with manual tracking and server-side events to match different teams’ workflows and data needs.

Server-side API to send custom events (e.g., purchases, backend milestones) with support for idempotency keys to prevent duplicate events.

Guidance and support for capturing additional user activities as custom events via client-side and server-side track APIs, including tradeoffs (e.g., ad blockers vs precision).

Point-and-click interface to find, name, and manage events without touching the codebase (including applying labels to raw events).

Event definitions apply across the entire dataset so newly defined events can be analyzed immediately across historical data.

Inject metadata into Autocaptured events without code (e.g., capture form-fill fields, grab text from elements, attach custom JavaScript-derived values as event properties).

Use APIs to enrich user/account/event properties, create unique identities across sessions, and incorporate server-side details (e.g., purchase processing and what was bought).

Built-in governance lifecycle for events: Define (taxonomy), Validate (verification), Monitor (alerts/repair), and Evolve (update/retire/combine).

Provides a Data Dictionary/definitions hub plus categories and version history to keep large datasets consistent and understandable.

Governance tooling surfaces items needing attention (e.g., notifies admins when new events need verification and flags definitions that stop collecting data).

Data science layer that analyzes behavioral data to automatically surface insights—even on behaviors you haven’t been following.

Generates a “Top Events” table to show key events between two moments in a funnel and what most influences conversion.

Instantly tracks engagement and success drivers for product analytics with “no manual event tagging needed.”

Lets teams “start yesterday” by learning from the past with retroactive product analytics.

Surfaces AI-powered recommendations (recommended next steps) so teams can act on insights faster.

Tracks and compares how users navigate your app to spot drop-off and improve conversion.

Unifies web and product analytics to understand which campaigns bring highly engaged users.

Deploy in-app guidance quickly using a no-engineering approach (“no engineering required”) with Pendo’s guide creation experience.

Uses embedded guides that blend into your UI for contextual help without disrupting the experience.

Supports walkthroughs and tooltips that surface when needed to accelerate onboarding and feature adoption.

Builds dynamic in-app experiences with conditional logic (“Guide Branching”) that adapts to each user’s choices.

Creates guides instantly using simple prompts via the AI guide builder (open beta).

Automatically matches your app’s dark mode so guides stay seamless and on-brand.

Provides video playbacks of user sessions for web and mobile apps to see experiences firsthand.

Includes unlimited replays, plus filtering and “Suggested Replays” to focus on the most relevant sessions.

Offers no-code privacy settings; sensitive content can be masked/blocked on the client so it never leaves the visitor’s device.

Debug faster with console and network logs in Session Replay, and report bugs with AI.

Automatically captures every user interaction without manual tagging, so teams can explore fresh insights retroactively and avoid missed data points.

Uses a “one global script” approach with server-side data processing to minimize client-side load and avoid performance hiccups.

Fullcapture adjusts to changes in your site or app automatically, reducing the need to retag or update events over time.

Recreates user sessions so teams can see the “why” behind metrics, including support for behaviors like tabbed browsing.

Generates AI-powered session summaries (including multi-session summaries) to condense lengthy replays into actionable takeaways.

An AI-powered analyst built into Fullstory that answers questions and analyzes sessions, segments, and dashboards to surface context-rich insights.

Proactively identifies and prioritizes issues such as “Opportunities - Funnel Drops” and “Opportunities - Spiking Issues,” based on impact.

AI assistance that trims selectors down to the most stable option for elements (to make analysis and definition work more resilient).

AI suggests pages that match behavioral patterns and recommends elements/object names to speed up configuration and analysis.

Visualize engagement with Click Maps and Scroll Maps to understand interaction and scroll depth on pages; jump to deeper diagnostics as needed.

Analyze conversion paths to spot where users get off track, measure completion and speed-to-finish, and save high-priority funnels to dashboards.

Automatically surfaces key frustration signals such as Rage Clicks, Dead Clicks, Error Clicks, and Thrashed Cursor to pinpoint UX breakdowns.

Provides automated alerts for frustration/sentiment signals and prioritizes issues by business impact, with validation via Session Replay.

Visualize step-by-step navigation paths through your site to understand common routes and deviations by segment, using Pages, Events, and Elements.

Create segments from hundreds of user and event criteria (and enriched attributes) to compare successful vs. struggling cohorts across analyses.

Visualize aggregated behavior to see where users click (or tap), scroll, and move on each page—so you can identify what’s working (and what’s not).

Heatmaps include “Attention Maps” to help you understand what grabs users’ attention.

Compare behaviors “side by side across journeys” to spot differences and patterns faster.

Watch real user journeys to quickly spot bugs, confusion, and drop-offs.

Get AI-powered summaries (including a “one-click summary”) that highlight key moments so you can find issues faster.

Session Replay includes frustration detection to help surface sessions worth investigating.

Session Replay is described as enhanced with error detection to help teams find and fix bugs faster.

Hotjar highlights a “privacy-first script built for site speed,” and its recording pipeline includes anonymization/suppression controls you manage.

Connect replays with heatmaps and survey responses to get the “full picture” of what users experience.

Visualize each step of a journey to see where users drop off and connect the numbers to behavior.

Build funnels with up to 10 steps based on sessions that viewed a page, clicked an element, or triggered an event—and jump into connected recordings for conversions/drop-offs.

Compare funnels across devices/segments with up to 5 comparisons, plus views like “Conversion over time” and “average time to convert.”

Use “Sense Chat” to ask questions (e.g., where users are dropping off) and get practical recommendations instantly.

Create and compare custom metrics, visualize them in charts, track over time, click through to related recordings/heatmaps, and add them to Dashboards.

Dashboards provide a high-level view of key metrics; you can filter and compare aggregates and reuse saved “Segments” across Recordings and Dashboards.

Matomo is built around “100% data ownership”, so you stay in full control of your analytics data.

Matomo is free and open-source software (GPL v3 or later), designed for transparency, extensibility, and long-term “future-proof” analytics.

Matomo emphasizes “No Data Sampling” so reporting is based on complete, unsampled data rather than estimates.

Matomo highlights “No data limitations” (e.g., no limits on websites/users/segments and no limitation on how much data you store).

Matomo Cloud is a fully managed option with access to all Matomo features plus automatic software updates and support.

Matomo On-Premise lets you self-host Matomo Analytics on your own servers to control where your data is stored (data sovereignty).

Matomo supports migrating between Cloud-hosted and On-Premise (and vice versa).

The Data Warehouse Connector is a Matomo Cloud add-on for hosted, automated exports of Matomo analytics data to supported data warehouse platforms (e.g., BigQuery workflows are documented).

Matomo provides a Google Analytics import to bring historical GA reports/data into Matomo.

Matomo Log Analytics lets you generate reports by importing web server logs as an alternative to JavaScript tracking (for more security/privacy-sensitive environments).

Matomo positions “GDPR Manager” alongside GDPR features like data anonymization, opt-out, and visitor data deletion capabilities.

Matomo lists privacy controls such as IP anonymisation, DoNotTrack support, an opt-out mechanism, configurable retention, and the ability to run in consent-exempt configurations (when properly configured).

Matomo supports tracking/cookie consent modes (e.g., requireConsent vs requireCookieConsent) and can also be configured for cookieless tracking (disable cookies).

Matomo provides guidance and integrations for Consent Management Platforms (CMPs) so analytics collection can be aligned to user consent.

Matomo includes built-in opt-out mechanisms, including an embeddable opt-out form you can publish (often on a privacy policy page).