Adobe Customer Journey Analytics - CJA

Location: Pan India • Experience: Mid Level • Openings: 5

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Job description

Job Details

Job Title - Adobe Customer Journey Analytics Specialist

Job Location - PAN India

Work Model - Work from Office

Candidate Expectations

Total Experience - 7+ years and Relevant Experience – 4+ years

Candidate Location – Anywhere

Skills – XDM schema design, data ingestion (batch & streaming), and Profile Store setup, Adobe Cloud, AEP

Candidate Industry – IT / ITES

Specific Remarks – Bachelor’s Degree regular mandatory

Detailed Job Description

4+ years of experience in digital analytics, with a focus on Adobe CJA, Adobe Analytics, and AEP.

Strong expertise in cross-channel data integration and analysis.

Experience with creating reports, dashboards, and visualizations in Adobe CJA Workspace.

Proficient in using Adobe Experience Platform to manage customer profiles and data connections.

Solid understanding of JavaScript, HTML, and tag management tools (e.g., Adobe Launch).

Analytical mindset with strong problem-solving skills and attention to detail.

Excellent communication skills, with the ability to translate data insights into business strategies.

Key Responsibilities:

Data Analysis & Insights:

Utilize Adobe CJA to analyze cross-channel customer data and provide actionable insights.

Create and optimize interactive dashboards and visualizations to communicate customer journey trends and KPIs.

Customer Journey Mapping:

Develop comprehensive customer journey maps to understand behavior across touchpoints.

Identify pain points, opportunities, and key moments in the customer lifecycle.

Adobe Experience Platform (AEP):

Integrate and manage data sources within AEP to ensure seamless data flow for CJA.

Configure schemas, datasets, and connections in AEP for effective customer data management.

Adobe Analytics Expertise:

Perform deep-dive analysis using Adobe Analytics for digital performance and user engagement metrics.

Collaborate with teams to implement tagging and tracking strategies for accurate data collection.

Stakeholder Collaboration:

Work closely with marketing, product, and data science teams to align analytics efforts with business goals.

Present findings and recommendations to both technical and non-technical stakeholders.

Optimization & Personalization:

Support personalization efforts by analysing audience segments and content performance.

Recommend strategies to improve campaign performance and customer engagement.