<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
		>
<channel>
	<title>Comments on: Survey Data Cleansing: Five Steps for Cleaning Up Your Data</title>
	<atom:link href="http://blog.allegiance.com/2009/01/survey-data-cleansing-five-steps-for-cleaning-up-your-data/feed/" rel="self" type="application/rss+xml" />
	<link>http://blog.allegiance.com/2009/01/survey-data-cleansing-five-steps-for-cleaning-up-your-data/</link>
	<description>Increasing Customer and Employee Loyalty, Satisfaction and Engagement</description>
	<lastBuildDate>Thu, 11 Feb 2010 18:41:08 -0600</lastBuildDate>
	<generator>http://wordpress.org/?v=2.8.6</generator>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
		<item>
		<title>By: Alan Bainbridge</title>
		<link>http://blog.allegiance.com/2009/01/survey-data-cleansing-five-steps-for-cleaning-up-your-data/comment-page-1/#comment-695</link>
		<dc:creator>Alan Bainbridge</dc:creator>
		<pubDate>Thu, 08 Jan 2009 22:02:48 +0000</pubDate>
		<guid isPermaLink="false">http://blog.allegiance.com/?p=74#comment-695</guid>
		<description>Thanks for your comment,
This is equally important for small businesses.  I&#039;ve been reviewing data from another survey with a lot of speeders and flat-liners.  The very presence of a lot of speeders and flat-liners may reveal that respondents don&#039;t really know how to answer the questions.  Either the questions aren&#039;t clear or they lack relevant experience.  In my experience, tightening up the qualification process eliminates this to some degree.
For a small business with a smaller customer base, the presence of one outlier will throw the data off moreso than with a larger sample.  One respondent who answers everything 100% &#039;Strongly agree&#039; can really throw a wrench into your results.</description>
		<content:encoded><![CDATA[<p>Thanks for your comment,<br />
This is equally important for small businesses.  I&#8217;ve been reviewing data from another survey with a lot of speeders and flat-liners.  The very presence of a lot of speeders and flat-liners may reveal that respondents don&#8217;t really know how to answer the questions.  Either the questions aren&#8217;t clear or they lack relevant experience.  In my experience, tightening up the qualification process eliminates this to some degree.<br />
For a small business with a smaller customer base, the presence of one outlier will throw the data off moreso than with a larger sample.  One respondent who answers everything 100% &#8216;Strongly agree&#8217; can really throw a wrench into your results.</p>
]]></content:encoded>
	</item>
	<item>
		<title>By: cherryloyalty22</title>
		<link>http://blog.allegiance.com/2009/01/survey-data-cleansing-five-steps-for-cleaning-up-your-data/comment-page-1/#comment-694</link>
		<dc:creator>cherryloyalty22</dc:creator>
		<pubDate>Thu, 08 Jan 2009 21:31:46 +0000</pubDate>
		<guid isPermaLink="false">http://blog.allegiance.com/?p=74#comment-694</guid>
		<description>great post. i read these every week. regarding section #4, how important is it for small businesses</description>
		<content:encoded><![CDATA[<p>great post. i read these every week. regarding section #4, how important is it for small businesses</p>
]]></content:encoded>
	</item>
</channel>
</rss>
