Certification in Marketing Analytics

Learn data collection methods and sources for marketing analytics. Explore web analytics, CRM data, social media, email marketing, and e-commerce data, with essential ethical considerations and tools.

Explore platform analytics and social listening for engagement, reach, and audience insights. Track email campaigns with open rates, click-through rates, bounce rates, and unsubscribe rates to optimize targeting.

Explore how CRM platforms store customer data, enabling personalized marketing, segmentation, and better targeting. Learn how sales pipeline and marketing automation capture campaign data to improve leads, conversion, and engagement.

explore data collection sources for marketing analytics, including ad platform metrics and third-party data. leverage pos and online survey insights to enrich customer profiles, enable personalized marketing, and improve segmentation.

Explore how marketers leverage diverse data sources to understand customer behavior and campaign performance, enabling data driven decision making while upholding GDPR, CcpA, and ethical privacy practices.

Analyze descriptive analytics for marketing insights by examining historical marketing performance, website traffic, conversion rate, and demographics, and visualize trends to guide data-driven decisions.

Explore demographic analysis and behavioral analysis to segment customers by age, gender, income, and location, and apply RFM, attribution models, and A/B testing to optimize marketing campaigns and channel ROI.

Explore descriptive analytics for marketing insights by mapping the conversation funnel, analyzing paths and drop-off points, and using product, market, and customer feedback data to optimize strategies.

Visualize customer distribution, market penetration, and sales performance on maps to uncover high potential geographic regions. Apply CLV segmentation and retention strategies with tailored messaging and analytics to optimize marketing.

Create interactive dashboards to visualize marketing KPIs and real-time metrics, enabling informed decisions and clear stakeholder communication. Use descriptive analytics to derive marketing insights.

Segment customers by demographic, psychographic, and behavioral attributes; analyze segments for targeted, personalized marketing using marketing analytics and a centralized customer data platform (CDP).

Explore demographic, psychographic, behavioral, and firmographic segmentation, and apply cluster, factor, and decision-tree analyses (including k-means) for precise marketing targeting.

Explore how personalization and customization craft segment-specific messages, tailored product offerings, and dynamic content across channels, using ab testing and iterative optimization to boost engagement and conversions.

Define and measure customer segments with KPIs like conversion rate, retention, average order value, and customer lifetime value to optimize targeting and ROI through marketing analytics.

Explore predictive analytics for forecasting customer behavior using logistic regression, trees, forests, neural networks, and Arima to predict churn, lifetime value, and future sales for acquisition and retention strategies.

Develop data collection, cleaning, and integration across purchases, website behavior, demographics, and social engagement, then perform feature selection and engineering for predictive customer behavior.

Explore how to select and train predictive analytics models for customer behavior, using regression, classification, or time series techniques, with historical data, feature engineering, and robust evaluation.

Forecast future customer behavior with predictive models across short, medium, and long horizons; perform scenario analyses, interpret results, and deploy real-time insights to personalize marketing and optimize campaigns.

Leverage predictive analytics to forecast customer behavior and personalize interactions while monitoring model performance, updating with new data, and upholding GDPR and CCPA privacy and ethics.

Explore how campaigning analytics and ROI measurement assess marketing performance through data collection, integration, and metrics like click-through rate, conversion rate, and ROI, guiding data-driven resource allocation and optimization.

Apply attribution models, including first click, last click, linear, and time decay, to attribute conversions to campaigns, using UTM parameters, tracking pixels, and conversation tags for ROI insights.

Analyze campaign metrics and KPIs across channels to identify top performing campaigns, channels, and creatives, allocate budget efficiently, and maximize ROI via marketing mix modeling, regression analysis, and data-driven segmentation.

Design and run A/B tests to compare ad copy, visuals, targeting, and landing pages, and apply lift and incremental analysis to measure ROI and optimize campaigns.

Optimize attribution models across multiple touchpoints to measure ROI, visualize campaigns with dashboards, and deliver data-driven insights for marketing decisions.

Explore how social media analytics measure engagement and brand sentiment. Identify influencers, key metrics, and use data from Facebook, Twitter, Instagram, LinkedIn, YouTube, and TikTok to inform content strategy.

Track key metrics and KPIs such as reach, impressions, engagement rate, growth rate, click through rate, and share of voice to measure social media engagement and guide content optimization.

Learn to map social media audiences with demographic and behavior insights, tailor content and targeting, monitor competitor performance, and apply sentiment analysis to track brand perception and engagement trends.

Identify influencers and key opinion leaders, analyze collaboration impact on brand awareness and engagement, and measure campaigning performance through reach, engagement, conversion, and return on investment with social listening.

Create dashboard and report to visualize social media analytics data, train and insight, and share report with stakeholders, decision makers and marketing teams to inform strategy, decision making and optimization.

Explore customer journey mapping across touchpoints and channels and apply attribution modeling to allocate credit, optimize the marketing mix, and improve ROI.

Collect data from analytics, CRM, sales records, and feedback to map touchpoints across awareness to post-purchase. Create personas and analyze behavior to enable data-driven decisions and improve the journey.

Define conversation events and identify marketing touchpoints across channels such as organic search, paid ads, social, email, and referrals. Compare attribution models—first touch, last touch, linear, time decay, and position-based.

Analyze the customer journey and attribution modeling to identify influential touchpoints, optimize channel mix, and allocate budget for maximum roi through experimentation, including a/b testing, and data-driven strategy.

Design and conduct A/B tests to optimize marketing campaigns, form hypotheses, set up control vs. variant tests, and use metrics like conversion and click-through rate to drive data-driven decisions.

Identify testable variables such as headlines, CTAs, images, and layouts; create mutually exclusive variations, randomize audience assignment, and segment by demographics to measure impact on engagement and conversions.

Deploy and monitor A/B test variations across email, website, landing pages, and ads, analyze real time metrics like click through rates, conversion rate, engagement, revenue, and apply hypothesis testing.

Learn to run A/B tests across marketing assets and channels, implement winning variations, document insights, and continuously optimize strategies to boost engagement and return on investment.