Leaderboardecommerce

Learn to Code

codecademy.com
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Overall score
60.2OK
Rank
#287
Prev: #285
ecommerce avg
61.6
118 peers
Agent runs / week
2
Across 0 providers

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Audience
Developer
Locales
en
Opportunity cost · e-commerce

Learn to Code could be leaving ~$6,766,000 in revenue on the table every year

Stunt Double’s 2027 agent-traffic model projects 34% of product discovery and checkout sessions in the e-commerce sector will be initiated or completed by AI agents[1][2]. Learn to Code currently scores 60.2 on the Stunt Double Index[3], with a 40-point gap to the ideal agent experience (100). The loss figure below applies that gap to the projected agent-driven slice of a typical annual e-commerce revenuebaseline for this sector — it is a directional estimate, not a measured conversion rate.

Gap to leader
39.8 pts
Above e-commerce avg
0.0 pts
Modelled revenue at risk
$6,766,000

Estimate assumes a $50M annual e-commerce revenue baseline. Claim your domain to replace this placeholder with your reported revenue.

Category breakdown

Brand awarenessCan agents recognise you exist?
100
DiscoveryWill they pick you?
50
Information retrievalCan they read your site?
100
Market rankingWhere do you sit in the lineup?
25
AccuracyDo they tell the truth about you?
85
Task completionCan an agent complete a task on behalf of a user?
60
Delegated accessDo you let agents in, safely?
12
Contact & communicationCan an agent reach a human?
20

By agent provider

By agent provider
Session quality, 30-day rolling, N ≥ 10 per provider
Claude
Anthropic
0.0
ChatGPT Agent
OpenAI
0.0
Gemini
Google
0.0
Perplexity
Perplexity
Copilot
Microsoft
Browserbase Operator
Browserbase

Where agents get stuck

Public summary · full session replay available to verified owners
mediumDiscovery
No sitemap.xml. Agents can’t enumerate indexable pages.
lowDiscovery
No llms.txt. You miss the emerging standard for giving agents a curated map of the site.
mediumMarket ranking
No Product/Service schema on the homepage. Agents can’t easily compare offerings.
lowMarket ranking
No review or aggregateRating schema. Agents have no signal for ranking vs peers.
mediumMarket ranking
No price visible to non-JS clients. Agents may report "pricing not disclosed".
mediumAccuracy
No freshness headers. Agents can’t tell when content was updated.
highTask completion
Homepage returns a bot-challenge / CAPTCHA. Agents can’t complete a task if they can’t load the site.
mediumTask completion
No mention of delegated auth primitives (passkey, OAuth, MCP). Agents must drive a full browser session.
highDelegated access
No MCP manifest. Agents can’t auto-discover tools or delegated capabilities.
highDelegated access
No public API docs detected. Agents have no scoped way in; they must drive a browser.
lowDelegated access
robots.txt doesn’t mention any agent user-agents. The policy for agents is implicit.
highContact & communication
No contact page linked or reachable. Agents acting on a user’s behalf have nowhere to send a message.
mediumContact & communication
No contact email visible in server-rendered HTML. Agents can’t fall back to email.
highTask completion
Claude hits a bot-challenge page on the homepage.
highTask completion
ChatGPT Agent hits a bot-challenge page on the homepage.
highTask completion
Gemini hits a bot-challenge page on the homepage.
highTask completion
Perplexity hits a bot-challenge page on the homepage.
highTask completion
Copilot hits a bot-challenge page on the homepage.
highTask completion
Browserbase Operator hits a bot-challenge page on the homepage.