Senior Data Analyst - CRM PME

Role Summary

Investigative curiosity, critical sense and consultative stance.

Proactivity to identify opportunities, risks, inconsistencies and paths for evolution.

Ability to influence decisions based on evidence, tests and results.

Organization, autonomy and responsibility for highly relevant deliveries for the business.

Collaboration to work in multifunctional environments with CRM, Marketing, Commercial, Product, Data Science, Analytics and Technology.

Result orientation, focusing on impact, continuous learning and performance improvement.

Differences

Previous experience with B2B CRM, SMEs, financial services, credit, collections, data, marketing services or digital products.

Experience with Next Best Offer, Next Best Action, offer recommendation, advanced personalization or lifecycle marketing strategies.

Experience in activating analytical models in campaigns, journeys, digital channels or commercial actions.

Experience with Salesforce, CDPs, automation tools, data platforms or integration between analytical models and activation channels.

Knowledge in portfolio analysis, product penetration, portfolio expansion, cross-sell, upsell and base profitability.

Experience in environments driven by revenue, conversion, retention, commercial efficiency and campaign performance goals.

Main Responsibilities Strategy, CRM and Business

Support the evolution of the SME CRM strategy based on data, customer behavior, life cycle, campaign performance and business opportunities.

Connect customer analytics to acquisition, activation, engagement, retention, reactivation, cross-sell, upsell, shielding and churn reduction strategies.

Identify opportunities to personalize communications, offers and journeys based on profile, segment, channel, contracted product, behavior, customer maturity and relationship moment.

Translate complex analyzes into practical recommendations for CRM, Marketing, Commercial, Product and other stakeholders.

Support the definition of audiences, journeys, hypotheses, messages, channels and moments of approach based on evidence and data.

Contribute to the evolution of CRM indicators, such as engagement, conversion, revenue, retention, churn, reactivation, product penetration, LTV, customer value and campaign efficiency.

Act as an analytical reference for SME CRM decisions, helping to increase the quality of hypotheses, reading of results and the team's data-driven culture.

Connection with NBO/NBA and Intelligence Applied to CRM

Act as a bridge between the CRM SME team and the Data Science front responsible for the NBO/NBA models.

Interpret the outputs of NBO/NBA models and translate them into actionable opportunities for campaigns, journeys, rulers, digital channels and commercial actions.

Support the definition of hypotheses for using models in communications, considering audience, offer, recommended action, channel, message, frequency and moment of approach.

Propose A/B tests, incrementality tests, pilots and controlled experiments to evaluate the effectiveness of using NBO/NBA in CRM actions.

Build analyzes that facilitate the adoption of the use of intelligence in communications, demonstrating gains, learning, limitations and opportunities for evolution.

Monitor the performance of actions that use NBO/NBA, evaluating engagement, conversion, revenue, offer acceptance, product use, retention, cross-sell, upsell and incremental impact.

Identify response patterns by segment, product, channel, moment in the journey and type of recommendation, generating learning for continuous optimization.

Support the prioritization of audiences and recommendations, connecting the analytical rationale of the model to the real needs of CRM and the SME business.

Work with Data Science to feed the models with CRM learnings, campaign results, response behavior and opportunities observed in the operation.

Ensure that the use of NBO/NBA is applied in a practical, measurable way and adheres to the relationship strategy with SME customers.

Analytical Operation, Data and Processes

Lead base analyses, cohorts, funnels, journeys, channels, products, clusters, behavior, propensity and campaign performance.

Build and evolve dashboards, executive reports and recurring analytical views for SME CRM monitoring.

Support the structuring of analytical bases, segmentations, eligibility rules, prioritization criteria and opportunity studies.

Ensure clarity, reliability and actionability of indicators used in CRM decisions.

Work with different data sources to build a more integrated view of the customer, considering relationships, consumption, engagement, commercial history, interactions by channel and contracted products.

Identify inconsistencies, data gaps, automation opportunities and improvements in CRM analytical processes.

Contribute to reducing communications overlap, improving contact pressure and increasing the relevance of interactions.

Support the evolution of automated journeys, dynamic and responsive to customer behavior.

Contribute to greater operational efficiency of campaigns, segmentations and performance analysis.

Measurement, Experimentation and Learning

Define and conduct performance analyzes to evaluate the impact of campaigns, journeys, rules, offers, commercial actions and intelligence-driven communications.

Structure A/B tests, multivariate tests, control groups and incrementality analyses, whenever applicable.

Evaluate business hypotheses with analytical rigor, connecting results to clear learnings and optimization recommendations.

Measure the impact of CRM actions on indicators such as conversion, revenue, engagement, product use, retention, churn, cross-sell, upsell and LTV.

Create analytical narratives that facilitate decision-making for different audiences, from technical teams to business leaders.

Transform complex data into diagnoses, recommendations and action plans.

Document learnings about what works, for which audiences, on which channels, at which points in the journey and with what types of recommendations.

Support the creation of a continuous learning routine, connecting hypotheses, tests, results and next steps.

Benefits

Experian is a global data and technology company that drives opportunities for people and businesses around the world. We operate in several markets, such as financial services, health, automotive, agribusiness, insurance, among others. Experian invests in people and advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees in 32 countries.

Our uniqueness is to value yours. Experian’s people-centered, inclusive and purpose-driven culture is recognized by numerous awards — including World’s Best Workplaces™ 2025 (Fortune’s Global Top 25) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to see why. Experian is also proud to be an equal opportunity and affirmative action employer.

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