Emotional intelligence scoring as a service
Self-awareness, self-regulation, motivation, empathy, social skills — server-side scored and returned as per-dimension values via three REST calls. X-API-Key auth, 2-minute completion, results attributed to your org.
JobCannon's EQ API exposes Goleman-model emotional intelligence scoring as a live REST service. The instrument covers five EQ domains — self-awareness, self-regulation, motivation, empathy, and social skills — in a 10-question format designed for 2-minute completion inside coaching intake flows, leadership programmes, and workplace-readiness modules. Integration follows the same three-call lifecycle: POST /api/v1/assessments with { test: "eq" } starts a session and returns the question set; POST /api/v1/assessments/{session_id}/complete submits answers and returns { result_id, top_result, scores } with per-dimension values across all five Goleman domains; GET /api/v1/assessments/{session_id}/questions re-serves questions if needed (scope assessments:read). Authentication is a single X-API-Key header (jck_live_…, SHA-256 hashed at rest) — no OAuth exchange. Scoring is deterministic and server-side. Results persist to the partner organisation via api_org_id, enabling re-administration against the same external_user_id to track EQ development over time. Live on the Scale tier ($199/mo) with a monthly allotment then $2/assessment overage; white-label resale partners can move to revenue-share.
Emotional intelligence scoring built for leadership and workplace-readiness products.
Deploy EQ alongside personality or career instruments for a complete leadership or coaching profile.
For L&D, coaching, and leadership-development platforms
The EQ API is an instrument-specific entry point into the broader psychometric API, which covers the full instrument library and scientific framing. For the three-call lifecycle and auth reference, see the Assessment API page. All institutional features are described on the JobCannon for Business hub.
Teams deploying EQ alongside personality scoring should see the Big Five API and the personality test API overview. For career-interest data in workforce-readiness contexts, see the RIASEC API. Embedding the full assessment experience under your own brand? Review white-label theming.
Live on the Scale tier ($199/mo) with a monthly assessment allotment; additional assessments are $2 each. Coaching and L&D platforms operating at scale should ask about partnership pricing. White-label partners who embed and resell EQ results can move to a revenue-share.
Always free for micro-teams
For solo coaches and small HR
For startups, teams and HR
For agencies, L&D and scale-ups
For 200+ person companies
Self-serve checkout via Stripe — major cards, Apple Pay, Google Pay, Link. Cancel anytime; 14-day money-back on Starter, Team, and Scale. Enterprise via the contact form below.
Tell us your use case — L&D, coaching, leadership development, workplace readiness — and your expected monthly volume. We respond with a key, the endpoint reference, and a technical onboarding plan.
The instrument is grounded in Goleman's model of emotional intelligence, which defines EQ across five domains: self-awareness (recognising one's own emotions and their effects), self-regulation (managing disruptive emotions and impulses), motivation (internal drive beyond external rewards), empathy (understanding others' emotional states), and social skills (managing relationships and building networks). These are the dimensions most widely adopted in L&D, leadership-development, and coaching contexts — the framework behind the Emotional Competency Inventory and widely cited in organisational-behaviour research.
POST /api/v1/assessments/{session_id}/complete returns { result_id, test, top_result, scores, question_pool }. For the EQ instrument, scores contains per-dimension values across the Goleman domains. top_result is the dominant dimension label — the area of highest emotional intelligence for the respondent — useful for a one-line coaching headline. Your L&D or coaching product renders the dimension breakdown (strengths, development areas) however the workflow demands.
POST /api/v1/assessments with { test: "eq", locale?, external_user_id? } starts a session and returns the question set. The EQ instrument is 10 questions — completion takes approximately 2 minutes, well inside the attention budget of a leadership-development module or coaching intake flow. GET /api/v1/assessments/{session_id}/questions re-serves the questions if your UI needs them again (scope assessments:read). POST /api/v1/assessments/{session_id}/complete with { answers: number[] } submits the answer vector, scores it server-side, and returns the result.
EQ is consistently the most-requested instrument in leadership-development contexts because EQ dimensions predict leadership effectiveness, team cohesion, and coaching responsiveness better than IQ alone does. An EQ baseline at hire or cohort-entry lets coaching platforms track development over time, L&D platforms personalise module sequences (high self-awareness but low self-regulation → impulse-management modules), and leadership programmes identify development priorities before a 360 review.
Yes. Each administration is a new session and returns a new result_id, all attributed to your organisation via api_org_id. You pass the same external_user_id across administrations to track an individual. The result_id and scores are yours to store, diff, and surface as development progress inside your coaching or L&D platform.
One X-API-Key header per request. Keys are issued per organisation (format jck_live_…), scoped to assessments:send and assessments:read, and SHA-256 hashed at rest. No OAuth exchange. Sessions are short-lived signed tokens returned by the start call, so your side holds no session state.
The API is live on the Scale tier ($199/mo), which includes a monthly assessment allotment. Assessments over the cap are $2 each. Coaching and L&D platforms operating at scale should ask about partnership pricing. White-label partners who resell EQ results inside their programmes can move to a revenue-share model.