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Big data is the source of a myriad of opportunities for businesses looking to develop their markets, build customer loyalty, take an innovative lead and explore niches to attract new customers.
This course features new practices in data and big data analytics to accelerate your marketing results and optimize your customers’ experience.
Explore opportunities stemming from big data and analytics to understand how data behaves, develop appealing proposals and use digital networks to get customers to buy in to new products faster.
Review marketing concepts from a big data analytics perspective.
Get to know the main tools used in marketing analytics.
Adopt an analytical framework and practical tools to roll out new initiatives.
Share best practices in big data and AI use.
Give participants the opportunity to contemplate solutions for improving their strategies and accelerating their results.
Clarify the numerous abbreviations used in digital marketing and big data.
Is this for you?
Leaders and managers working in the marketing ecosystem who:
Want to use big data to boost their profits and sales quickly by making better decisions using big data and AI.
Are looking to gain a clearer understanding of their options in terms of marketing technologies to better orient their strategies and tactics.
Are determined to step up their skills and knowledge in a fast-changing market.
Have their sights set on getting a leg up on their competitors with hard-to-replicate advantages.
Interact with high-level executives working in the marketing ecosystem.
Take advantage of big data analytics to acquire new customers, improve product and service quality, increase retention and loyalty, boost average revenue per client, maximize response rates to marketing campaigns and outgrow the competition.
Role of the marketing leader and partners in gleaning invaluable customer insight and making decisions.
Market trends and added value of analytical models and AI in your marketing mix in terms of boosting sales, reducing costs and maximizing working capital.
Definitions and types of marketing models (descriptive, diagnostic, predictive, prescriptive). Discussion of various types of data used.
Real-life industry examples from companies of all sizes to explore key tools in determining and optimizing prices and products, segmentation, optimization of B2B sales using CRM, demand forecasting, and profitability and life cycle models.
Review of the main methodologies used in digital marketing, such as search engine optimization (SEO), customer value analytics (CVA), attribution models and micro-moments, to enhance marketing campaigns and improve the customer experience and engagement levels.
Discussion of the importance of data integrity, metrics and tools.
Review and discussion of best practices and resources to help assess the maturity of big data–driven digital marketing strategies and implement various efforts to take them to the next level and improve your outcomes.