Crazy Egg
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FullStory
Crazy Egg vs FullStory: Which Is Right for You?
Crazy Egg and FullStory sit at very different ends of the behavioral analytics spectrum. Crazy Egg is built for teams that want approachable visual insights without deep technical infrastructure.
FullStory targets enterprise organizations with dedicated data teams and significant implementation budgets.
Comparing them usually reveals a mismatch in scope — the question is whether you need accessibility or enterprise depth.
About
Crazy Egg
Crazy Egg is a popular page-level optimization tool positioned as page-level optimization tool built for marketers, combining heatmaps with lightweight A/B testing. It's primarily used by small business owners, marketing managers, and growth teams focused on landing page optimization.
Teams choose Crazy Egg for its built-in A/B and multivariate testing, confetti click reports show traffic-source segmentation, and simple enough for non-technical marketers. Compared to Hotjar, Crazy Egg is generally your primary goal is testing individual pages quickly with a simple, affordable tool — though it can feel limiting when weak multi-step funnel or journey analysis or A/B testing is rudimentary vs. dedicated tools.
About
FullStory
FullStory is an enterprise-grade session replay and behavioral data platform positioned as enterprise digital experience intelligence platform built on autocapture and DX Data for data-driven product and engineering teams. It's primarily used by enterprise product, engineering, and data teams at companies with 200+ employees and existing data infrastructure.
Teams choose FullStory for its pixel-perfect session replay — industry benchmark quality, autocapture enables retroactive analysis without pre-tagging, and DX Data pipes behavioral data into Snowflake, BigQuery, and Redshift. Compared to Hotjar, FullStory is generally you need enterprise-grade replay quality and want behavioral data flowing into your existing data warehouse — though it can feel limiting when among the most expensive tools in the category or requires significant engineering involvement.
Feature | Crazy Egg | FullStory | Lucky Orange |
|---|---|---|---|
Heatmaps | Yes | Limited | Yes |
Session Recordings | Limited | Yes | Yes |
A/B Testing | Yes | No | No |
Funnel Analysis | No | Yes | Yes |
Surveys & Feedback | Yes | No | Yes |
Mobile Analytics | No | Yes | Yes |
AI-Powered Insights | No | Limited | Yes |
Data Warehouse Export | Limited | Yes | Limited |
Free Plan | No | Yes | Yes |
Manual Review Required | Medium | Medium | Low |
Choose Crazy Egg if your primary goal is testing individual pages quickly with a simple, affordable tool. It's a strong fit for small business owners, marketing managers, and growth teams focused on landing page optimization and offers confetti click reports show traffic-source segmentation. Avoid it if you need session recording depth or multi-page journey analysis.
Choose FullStory if you need enterprise-grade replay quality and want behavioral data flowing into your existing data warehouse. It's a strong fit for enterprise product, engineering, and data teams at companies with 200+ employees and existing data infrastructure and offers autocapture enables retroactive analysis without pre-tagging.
Avoid it if you're a small or mid-market team without data infrastructure to consume DX Data.
Do you need more data, or do you need fewer questions?
Crazy Egg and FullStory both generate behavioral data — heatmaps, session recordings, event streams, and funnel reports. But both tools still require your team to decide what to investigate, manually review what they find, and form conclusions without automated support.
Lucky Orange Discovery AI is different. It's an AI-powered analytics assistant that automatically analyzes session data and answers natural-language questions about user behavior. Instead of reviewing recordings or scanning charts, your team can ask direct questions and receive structured explanations, supporting evidence from real sessions, and recommended next steps — without needing to know what to look for first.
Ask questions like:
Why are users abandoning checkout after selecting shipping?
Which traffic sources produce the most confused sessions?
What changed in user behavior after our last product update?
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