{"id":27351695,"url":"https://github.com/harshindcoder/anywhere_gaming_repair_advertisement_case_study","last_synced_at":"2026-01-21T06:22:44.693Z","repository":{"id":286282942,"uuid":"960952637","full_name":"harshindcoder/Anywhere_Gaming_Repair_Advertisement_Case_Study","owner":"harshindcoder","description":null,"archived":false,"fork":false,"pushed_at":"2025-04-05T12:36:12.000Z","size":4,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T13:36:59.249Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/harshindcoder.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-04-05T12:35:34.000Z","updated_at":"2025-04-05T12:36:15.000Z","dependencies_parsed_at":"2025-04-05T13:47:04.788Z","dependency_job_id":null,"html_url":"https://github.com/harshindcoder/Anywhere_Gaming_Repair_Advertisement_Case_Study","commit_stats":null,"previous_names":["harshindcoder/anywhere_gaming_repair_advertisement_case_study"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harshindcoder%2FAnywhere_Gaming_Repair_Advertisement_Case_Study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harshindcoder%2FAnywhere_Gaming_Repair_Advertisement_Case_Study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harshindcoder%2FAnywhere_Gaming_Repair_Advertisement_Case_Study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harshindcoder%2FAnywhere_Gaming_Repair_Advertisement_Case_Study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/harshindcoder","download_url":"https://codeload.github.com/harshindcoder/Anywhere_Gaming_Repair_Advertisement_Case_Study/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248630591,"owners_count":21136470,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-04-12T20:33:13.356Z","updated_at":"2026-01-21T06:22:44.658Z","avatar_url":"https://github.com/harshindcoder.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎮 Anywhere Gaming Repair - Advertising Effectiveness Case Study\n\nThis case study explores how **Anywhere Gaming Repair**, a gaming setup and repair company, used data-driven decision making to identify the most effective advertising channel for reaching its **target audience of customers aged 18–34**.\n\n---\n\n## ✅ Objective\n\nTo help company stakeholders determine:\n- Which advertising method is best suited to reach their target audience.\n- Which channel provides the **highest return on investment (ROI)** and **lowest cost per acquisition (CPA)**.\n- Whether to invest in **TV commercials** or **podcast ads** based on actual customer behavior and media consumption trends.\n\n---\n\n## 👥 Stakeholders\n\n- Owner of the company  \n- Vice President of Communications  \n- Director of Marketing  \n- Director of Finance  \n\nThey assigned the responsibility to **Anna, the Analyst**, to conduct a deep-dive study and recommend the most strategic advertising option.\n\n---\n\n## 🎯 Target Audience\n\nAnalysis of internal customer demographics revealed that **individuals aged 18 to 34** are most likely to purchase or repair gaming systems. The focus of this study is to evaluate how this group consumes media, and where the company should focus its advertising budget.\n\n---\n\n## 📡 Advertising Channels Considered\n\nThe company initially considered the following channels:\n- Radio\n- Print Media\n- Billboards\n- TV Commercials\n- Public Transportation Ads\n- Podcasts\n\nAfter audience analysis, **TV Commercials** and **Podcasts** were identified as the two most popular mediums among the target age group.\n\n---\n\n## 📊 Analytical Approach\n\nAnna followed a structured, statistical methodology to guide the decision:\n\n1. **Stakeholder Interviews**  \n   → Gathered objectives, constraints, and priorities.\n\n2. **Target Audience Analysis**  \n   → Used demographic data to identify dominant customer age groups.\n\n3. **Market Research**  \n   → Researched media consumption trends using public and internal data sources.\n\n4. **Cost-Effectiveness Modeling**  \n   → Compared the cost, estimated reach, and conversion rates of each channel.\n\n5. **Pilot Campaign Execution**  \n   → Ran a 5-week podcast ad with a local production agency.\n\n6. **Performance Evaluation**  \n   → Measured ROI, CPA, and customer acquisition numbers post-campaign.\n\n---\n\n## 📈 Results of Pilot Campaign\n\n- **Campaign Duration:** 5 Weeks  \n- **Advertising Channel:** Podcasts  \n- **Cost:** $4,250  \n- **New Customers Acquired:** 85  \n- **Cost Per Acquisition (CPA):** ~$50  \n- **Conversion Tracking:** Tracked using referral codes and booking links.\n\nCompared to projected TV commercial outcomes:\n- TV estimated CPA: ~$200  \n- Higher cost, lower targeting precision, and less trackable engagement.\n\n---\n\n## 💡 Final Recommendation\n\nBased on data analysis and campaign performance, **podcast advertising** was selected as the **most effective and budget-friendly** method to reach Anywhere Gaming Repair's ideal customers.\n\nAnna presented these insights to stakeholders in a concise, visual report, enabling the marketing team to confidently invest in future podcast-based campaigns.\n\n---\n\n## 🚀 Key Takeaways\n\n- Always align advertising with **target demographic media habits**.\n- Use **CPA and ROI models** to evaluate marketing performance.\n- Modern platforms like podcasts often offer **better targeting and measurability** compared to traditional media.\n- Data-driven marketing ensures **efficient spending and strategic growth**.\n\n---\n\n\u003e “Without data, you're just another person with an opinion.” – W. Edwards Deming\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshindcoder%2Fanywhere_gaming_repair_advertisement_case_study","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharshindcoder%2Fanywhere_gaming_repair_advertisement_case_study","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshindcoder%2Fanywhere_gaming_repair_advertisement_case_study/lists"}