Marketa analytics wants to optimize their promotions campaign. They have weekly historical data and have built a model that shows sales a function of temperature, tv ad spending, radio spending and adstock effects.
• CodeLab Link for Assignment: https://codelabs-preview.appspot.com/?file_id=1PSsKcbe53Y1PKxCQOKHN5wUrM666ZdMuP4gBZ7oyng0#7
• To analyze the data and understand the influence of ad spending on sales including the adstock effects.
- Einstetin Analytics - Salesforce
- Google Colaboratory
- Pandas for Data Analysis
- Validating Adstock Model to understand how Adstock Value is generated.
- Manipulating the Adstock Model 1 and 2 to understand the decay effects of TV and Radio Spend.
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Data Wrangling CSV - Change the Sr.no format to "Text" and create the schema (final.jason) for the CSV file.
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Upload the file with Schema mentioned in Step 1, setting "Week" as Dimension and other attributes as "Measures"
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Create the App and Lenses with associated logic as:
• Sales Evaluation • Effect of TV Spend On Sales • Quantify_TVspend_v1 • AdStock Effects on TV Spending • AdStock Effects on Radio Spending • Effect of Radio Spend On Sales • Quantify_RadioVspend_v1
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Derive the insights from the above lenses.