{"id":2924,"date":"2016-06-23T05:30:53","date_gmt":"2016-06-23T09:30:53","guid":{"rendered":"http:\/\/www.sogolytics.com\/blog\/?p=2924"},"modified":"2019-09-25T07:46:34","modified_gmt":"2019-09-25T11:46:34","slug":"using-comparison-reports-to-delve-into-data","status":"publish","type":"post","link":"https:\/\/www.sogolytics.com\/blog\/using-comparison-reports-to-delve-into-data\/","title":{"rendered":"Using Comparison Reports to Delve Into Data"},"content":{"rendered":"

Quite often, we do research to get a snapshot of this moment in time: What do customers think of our new initiative? Which product features are most important?<\/p>\n

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However, in many situations, the current moment-in-time data is relevant only in terms of a comparison or an ongoing trend. On some random satisfaction scale, a score of 8 might be a good score. But that value is far more useful if we know that last year\u2019s score was 6, which means the situation is improving. If last year the score was 9.5, there\u2019s something for management to address.<\/p>\n

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\"?????????????????\"<\/a><\/p>\n

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There are several reasons to use Sogolytics\u2019s<\/strong> comparison reports. The most obvious is to evaluate trends by response period, such as year-over-year data analysis. It also lets you measure similar data sets against one another, such as comparing the U.S. versus EMEA market response, or judging employee satisfaction in both the Atlanta and Washington offices.<\/p>\n

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For instance, it is very common for businesses in the hospitality industry to send customer satisfaction surveys a few days after a hotel stay. That data all goes into one big bucket, and can comprise many thousands of responses. Looking at the standard reports shows an overall rating for each of the hotel chain\u2019s many attributes, such as \u201cvery satisfied\u201d for the check-in experience. But the generality has little value for executives making business decisions. Instead, the hotel chain can look at the data separated by time period (e.g. 2014, 2015, 2016 responses) and learn whether those expensive hotel renovations made any difference in customer perception.<\/p>\n

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\"Sogolytics-name-and-control-data-sets\"<\/a><\/p>\n

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Or management can use a comparison report to select and display customer satisfaction data by region, side by side. (This is not quite the same as doing a cross-tabulation; you should try both to see how the results differ.)<\/p>\n

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Sogolytics also makes it easy to grasp the similarities and differences once you are looking at the comparison report. The data is shown in tabular form by default, but you can turn this data into a chart or graph by choosing \u201cshow graphs\u201d under the report properties.<\/p>\n

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\"Sogolytics-Data-Comparison-Report\"<\/a><\/p>\n

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Happy exploring!<\/p>\n","protected":false},"excerpt":{"rendered":"

Quite often, we do research to get a snapshot of this moment in time: What do customers think of our new initiative? Which product features are most important? However, in many situations, the current moment-in-time data is relevant only in terms of a comparison or an ongoing trend. On some random satisfaction scale, a score of 8 might be a good score. But that value is far more useful if we know that last year\u2019s score was 6, which means the situation is improving. If last year the score was 9.5, there\u2019s something for management to address. There are several reasons to use Sogolytics\u2019s comparison reports. The most obvious is to evaluate trends by response period, such as year-over-year data analysis. It also lets you measure similar data sets against one another, such as comparing the U.S. versus EMEA market response, or judging employee satisfaction in both the Atlanta and Washington offices. For instance, it is very common for businesses in the hospitality industry to send customer satisfaction surveys a few days after a hotel stay. That data all goes into one big bucket, and can comprise many thousands of responses. Looking at the standard reports shows an overall rating for each of the hotel chain\u2019s many attributes, such as \u201cvery satisfied\u201d for the check-in experience. But the generality has little value for executives making business decisions. Instead, the hotel chain can look at the data separated by time period (e.g. 2014, 2015, 2016 responses) and learn whether those expensive […]<\/p>\n","protected":false},"author":1,"featured_media":5051,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[60,320,225,221],"yoast_head":"\nUsing Comparison Reports to Delve Into Data | Sogolytics Blog<\/title>\n<meta name=\"description\" content=\"Quite often, we do research to get a snapshot of this moment in time: What do customers think of our new initiative? 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