C2-M1 - Take Action With Data

Introduction

• The video presents a data analytics case study focused on problem-solving in the context of a real-world scenario.

• The business featured is Anywhere Gaming Repair, specializing in fixing video game systems and accessories.

Case Background

• The owner aimed to expand the business through advertising but was uncertain about the optimal strategy.

• Various advertising methods were discussed: print, billboards, TV commercials, public transportation ads, podcasts, and radio.

• Key Considerations for Advertising:

  • Target Audience: Understanding who to reach (e.g., a medical equipment manufacturer targeting doctors).

  • Budget Constraints: Evaluating the costs associated with different advertising methods (e.g., TV ads vs. radio ads).

The Data Analysis Process

Step 1: Ask

• Defining the Core Problem: Ensure clarity by discussing with stakeholders: owner, VP of communications, director of marketing and finance.

• Key insight: Not knowing the target audience's preferred advertising type.

Step 2: Prepare

• Understanding the Target Audience:

  • Focus on individuals who own video game systems, particularly the demographic likely to be interested.

• Data Collection:

  • Research various advertising methods to identify which one resonates with the target audience.

Step 3: Process

• Data Cleaning:

  • Removing errors and inconsistencies to ensure accurate findings for the analysis.

  • Techniques include using spreadsheet functions to correct data entries, checking for biases, and eliminating duplicates.

Step 4: Analyze

• Findings From Analysis:

  • Most likely demographic owning video game systems: Ages 18 to 34.

  • Top advertisement mediums for this demographic: TV commercials and podcasts.

• Budget Constraints:

  • Given high costs of TV ads, podcasts emerged as a more cost-effective solution.

Step 5: Share

• Communicating Results:

  • Created clear and engaging visuals to present findings to stakeholders effectively.

  • Ensured clarity in how the data informs the recommended advertising strategy.

Step 6: Act

• Implementation of Findings:

  • Collaborated with a local podcast production agency to create a 30-second ad for airing.

  • Results: Increased customer traffic noted within the first week; ultimately gained 85 new customers after a month.

Conclusion

• The presentation effectively demonstrates the application of the six phases of the data analysis process in solving real business problems:

  • The Six Phases: Ask, Prepare, Process, Analyze, Share, and Act.

• These phases differ from the data life cycle, which outlines how data changes over time.

Structured Problem-Solving Process

Structured Thinking Activities:

1. Recognizing the current problem

2. Organizing available information

3. Revealing gaps and opportunities

4. Identifying options

Personal Insight from Nikki

• Nikki's Experience at Google:

  • Involved in evaluating the effectiveness of the Noogler onboarding program.

    The team engaged in defining onboarding metrics and preparing, processing, analyzing, and ultimately acting on the data received.

  • The conclusion supported the successful transition to a project-based approach in onboarding, showing rapid productivity among new hires.