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MARKETING ANALYTICS DATA-DRIVEN TECHNIQUES WITH MICROSOFT EXCEL PDF

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ronaldweinland.info - download Marketing Analytics: Data-Driven Techniques with Microsoft Excel book online at best prices in India on ronaldweinland.info Read Marketing Analytics . Marketing Analytics: Data-Driven Techniques with Microsoft Excel eBook: Wayne L. Winston: ronaldweinland.info: Kindle Store. Marketing Analytics: Data-Driven Techniques with Microsoft Excel shows business managers and data analysts how to use a relatively simple tool--Excel-- -to.


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Marketing Analytics: Data-Driven Techniques with Microsoft® Excel®. Published by Microsoft and Excel are registered trademarks of Microsoft Corporation. Helping tech-savvy marketers and data analysts solve real-world business problems with Excel. Using data-driven business analytics to understand customers. Marketing Analytics: Data-Driven Techniques with Microsoft Excel [Wayne L. Winston] on ronaldweinland.info *FREE* shipping on qualifying offers. Helping tech- savvy.

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Winston W.L. Marketing Analytics: Data-Driven Techniques with Microsoft Excel

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No notes for slide. Download Marketing Analytics: Book Details Author: Paperback Brand: Description Marketing Analytics Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data.

Calculating the Percentage of Sales at Each Store The first step in creating a PivotTable is ensuring you have headings in the first row of your data. Notice that Row 7 of the example data in the data worksheet has the headings Product, Month, Store, and Price.

Because these are in place, you can begin creating your PivotTable. To do so, perform the following steps: 1. Place your cursor anywhere in the data cells on the data worksheet, and then click PivotTable in the Tables group on the Insert tab. Excel opens the Create PivotTable dialog box, as shown in Figure 1. In Exercise 14 at the end of the chapter you can practice creating PivotTables from data in different worksheets or even different workbooks.

Figure PivotTable Field List 3. You can choose from the following four zones: Row Labels: Fields dragged here are listed on the left side of the table in the order in which they are added to the box. In the current example, the Store field should be dragged to the Row Labels box so that data can be summarized by store. Column Labels: Fields dragged here have their values listed across the top row of the PivotTable.

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In the current example no fields exist in the Column Labels zone. Values: Fields dragged here are summarized mathematically in the PivotTable. The Price field should be dragged to this zone. Excel tries to guess the type of calculation you want to perform on a field.

Download Marketing Analytics Data-Driven Techniques with Microsoft Ex…

In this example Excel guesses that you want all Prices to be summed. Because you want to compute total revenue, this is correct.

If you want to change the method of calculation for a data field to an average, a count, or something else, simply double-click the data field or choose Value Field Settings.

You learn how to use the Value Fields Setting command later in this section. For fields dragged to the Report Filter zone, you can easily pick any subset of the field values so that the PivotTable shows calculations based only on that subset. In Excel or Excel you can use the exciting Slicers to select the subset of fields used in PivotTable calculations.

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If you do not see the field list, right-click any cell in the PivotTable, and select Show Field List. Figure Completed PivotTable Figure 1.

If you want a percentage breakdown of the sales by store, you need to change the way Excel displays data in the Values zone.

Wayne L. Winston

To do this, perform these steps: 1. Select Show Values As and click the drop-down arrow on the right side of the dialog box. Figure Obtaining percentage breakdown by Store Figure 1.