Today’s competitive market in the video game industry puts a lot of stress on companies to be ahead of competitors. The ability to predict the potential of a product gives companies an advantage over competitors on the market. Companies have therefore increased Competitive Intelligence (CI) departments in recent years and looked for ways to optimise forecasting capabilities. Researchers argue for the use of Machine Learning (ML) to forecast market potential of products, and have investigated varying methods of optimising the accuracy of models. Past studies have shown the existence of predictive value in online search traffic on Google. This study set out to investigate if Youtube search traffic holds similar predictive value. Results show that Youtube trends do have a degree of inherent predictive value, and the addition of the information enhances forecasting performance of ML models. However, the exact degree of the predictive value in Youtube trends is yet to be determined, as some evidence from testing implicated it to be strong while others weak.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-21540 |
| Date | January 2022 |
| Creators | Blomgren, Christoffer |
| Publisher | Högskolan i Skövde, Institutionen för informationsteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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