Sina Fak – Translating Data Into Business Intelligence

There’s untapped revenue hidden in your analytics. I’ll help you find it.

Businesses are capturing more data than ever before. But they’re also struggling to translate this data into actionable insights that drive real business value.

That’s where we come in.

In particular, we are going to demonstrate how, using our process and IIEA Framework, you can use experiments to:

• Translate your data into business intelligence.

As the volume and complexity of data your company captures increases, we help you make sense of the information you’re capturing, by giving you action-focused insights you need to make better, faster, more accurate decisions.

• Increase revenues and reduce costs.

Using data-driven experimentation as a tool to increase business performance, we use an agile process to solve problems and find hidden revenue opportunities for your business — leading to more efficient use of advertising budget, greater scale, and higher profit margins.

• Drive continuous growth and innovation.

As customer expectations change, acquisitions costs are increasing, and a growing number of competitors are disrupting your industry, we ensure that your business stays ahead of the curve by continuously improving your sales and marketing assets

What You’ll Learn In Translating Data Into Business Intelligence

Foundation

• 1.1 Intro (3:05)
• 1.2 Data Analytics vs. Business Intelligence (6:36)
• 1.3 7 Ways Combining Business Intelligence Insights And Experiments Will Exponentially Grow Your Business (15:15)
• 1.4 The Evolution of Business Intelligence Systems (10:12)

Insights

• 2.1 Extract Transform Load – The Data Infrastructure Required For Business Intelligence (5:55)
• 2.2 Evaluating what data you need to capture and how (9:00)
• 2.3 Mapping your customer buying journey (13:12)
• 2.4 Mapping your business ecosystem (13:26)
• 2.5 Data segmentation analysis (9:44)
• 2.6 Example of Insights from real customers (11:11)
• 2.7 Evaluating the quality of insights generated (4:23)

Ideation

• 3.1 The Scientific Method (3:05)
• 3.2 Setting objectives fo ideation (6:07)
• 3.3 Formulating your hypothesis (9:16)
• 3.4 Setting KPIs and learning objectives (7:09)
• 3.5 Prioritizing ideas (3:59)
• 3.6 Evaluating the quality of ideas generated (3:25)

Experimentation

• 4.1 Using experiments as a tool to translate data into intelligence (6:57)
• 4.2 Managing an experiment plan (PIE KPIs Hypothesis) (10:41)
• 4.3 Establishing an ongoing experiment process and culture (10:31)
• 4.4 Evaluating quality of experiments generated (2:55)

Analysis

• 5.1 Post test analysis (5:29)
• 5.2 Experiment Segmentation (7:09)
• 5.3 Reporting visualizing modeling data (12:24)
• 5.4 Communicating results across your team (3:50)
• 5.5 Conclusions (6:23)
• 5.6 Special Offer for INSIGHTS by ConversionAdvocates (0:44)
• BI Live Class – Free Resource (50:24)

About Sina Fak

As a Conversion Optimization and Business Intelligence consultant with over 10 years of experience, Sina helps decision-makers translate complex data, gathered from human-interfacing technologies, into actionable business intelligence insights that drive business growth.

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