<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	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/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Marketing Productivity Blog</title>
	<atom:link href="https://blog.jimnovo.com/feed/" rel="self" type="application/rss+xml" />
	<link>https://blog.jimnovo.com</link>
	<description>Moving from a Low Accountability to a High Accountability Business Model</description>
	<lastBuildDate>Wed, 29 Jan 2025 13:05:48 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.0</generator>
	<item>
		<title>Marketing Model or Financial Model?</title>
		<link>https://blog.jimnovo.com/2025/01/29/marketing-model-or-financial-model/</link>
					<comments>https://blog.jimnovo.com/2025/01/29/marketing-model-or-financial-model/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 29 Jan 2025 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6096</guid>

					<description><![CDATA[Where does all this kind of thinking on customer retention and value over time eventually lead you? Well, often right to Finance. Because you see, the more you can do to convince Finance the activities you are in engaging in are increasing profits for the company &#8211; and Finance truly believes this because they participated &#8230; <a href="https://blog.jimnovo.com/2025/01/29/marketing-model-or-financial-model/" class="more-link">Continue reading <span class="screen-reader-text">Marketing Model or Financial Model?</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2025/01/29/marketing-model-or-financial-model/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Intra-Company Promotional Risks</title>
		<link>https://blog.jimnovo.com/2025/01/15/intra-company-promotional-risks/</link>
					<comments>https://blog.jimnovo.com/2025/01/15/intra-company-promotional-risks/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 15 Jan 2025 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6007</guid>

					<description><![CDATA[Eating Your Own is not a great idea. Yet in many large companies, different divisions literally try to steal customers / sales from each other using the common customer database. Sure, everyone gets real excited over the plans to merge databases across the company and get the &#8220;full view&#8221; of the customer, and it makes &#8230; <a href="https://blog.jimnovo.com/2025/01/15/intra-company-promotional-risks/" class="more-link">Continue reading <span class="screen-reader-text">Intra-Company Promotional Risks</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2025/01/15/intra-company-promotional-risks/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Discovering Customer LifeCycles</title>
		<link>https://blog.jimnovo.com/2024/12/18/discovering-customer-lifecycles/</link>
					<comments>https://blog.jimnovo.com/2024/12/18/discovering-customer-lifecycles/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 18 Dec 2024 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6151</guid>

					<description><![CDATA[Today, we&#8217;re asked for a simple definition of retention. Problem is, the data / biz model really creates the definition. Meaning, you gotta match the creation of metrics with the actual actions.&#160; So I call for segmentation first so we can put some &#8220;actionable&#8221; stuff in the mix. Make sense? Let&#8217;s do the &#8220;simple&#8221; (easy? &#8230; <a href="https://blog.jimnovo.com/2024/12/18/discovering-customer-lifecycles/" class="more-link">Continue reading <span class="screen-reader-text">Discovering Customer LifeCycles</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/12/18/discovering-customer-lifecycles/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Modeling Customer Behavior with Small Databases</title>
		<link>https://blog.jimnovo.com/2024/12/04/modeling-small-scale-databases/</link>
					<comments>https://blog.jimnovo.com/2024/12/04/modeling-small-scale-databases/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 04 Dec 2024 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6145</guid>

					<description><![CDATA[We&#8217;re about to take a trip into the world of small scale databases. In particular, how does a not-for-profit with a small database of donors go about using predictive models? Answer: Keep it simple. Try to avoid using a lot of variables; look for the most powerful and stick with those until you are able &#8230; <a href="https://blog.jimnovo.com/2024/12/04/modeling-small-scale-databases/" class="more-link">Continue reading <span class="screen-reader-text">Modeling Customer Behavior with Small Databases</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/12/04/modeling-small-scale-databases/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>How Much is Promotional Proneness Costing You?</title>
		<link>https://blog.jimnovo.com/2024/11/20/cost-of-promotional-proneness/</link>
					<comments>https://blog.jimnovo.com/2024/11/20/cost-of-promotional-proneness/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 20 Nov 2024 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6134</guid>

					<description><![CDATA[Is your mission to increase Sales or Net Margin dollars? Worth getting some clarity on if you&#8217;re not sure, and if it&#8217;s Margin dollars you are after, watch out for Promotional Proneness. What&#8217;s that? The tendency of customers to learn promotional patterns and &#8220;wait for a discount&#8221;, which can significantly impact campaign profitability. Got Proneness? &#8230; <a href="https://blog.jimnovo.com/2024/11/20/cost-of-promotional-proneness/" class="more-link">Continue reading <span class="screen-reader-text">How Much is Promotional Proneness Costing You?</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/11/20/cost-of-promotional-proneness/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Difference between RF(M)  Scores &#038; LifeCycle Grids?</title>
		<link>https://blog.jimnovo.com/2024/11/06/difference-rfm-scores-lifecycle-grids/</link>
					<comments>https://blog.jimnovo.com/2024/11/06/difference-rfm-scores-lifecycle-grids/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 06 Nov 2024 20:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6118</guid>

					<description><![CDATA[Both RF(M) scoring and Lifecycle Grids use the same key predictive metrics &#8211; Recency and Frequency. So what&#8217;s the difference? RFM is a predictive &#8220;snapshot&#8221; at a specific point in time; LifeCycle Grids are more like a &#8220;movie&#8221; designed to be predictive over different periods of time. Another way to think of this: RFM is &#8230; <a href="https://blog.jimnovo.com/2024/11/06/difference-rfm-scores-lifecycle-grids/" class="more-link">Continue reading <span class="screen-reader-text">Difference between RF(M)  Scores &#38; LifeCycle Grids?</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/11/06/difference-rfm-scores-lifecycle-grids/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Problems Calculating Retention Rate</title>
		<link>https://blog.jimnovo.com/2024/10/23/problems-calculating-retention-rate/</link>
					<comments>https://blog.jimnovo.com/2024/10/23/problems-calculating-retention-rate/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 23 Oct 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6090</guid>

					<description><![CDATA[What is your customer retention rate? Well, that kinda depends on how you define the customer. Have you had an internal discussion, and more importantly, solidified agreement across divisions / functions on the definition of an (active?) customer? Please do. For example, is someone who hasn&#8217;t interacted with your company in any way for over &#8230; <a href="https://blog.jimnovo.com/2024/10/23/problems-calculating-retention-rate/" class="more-link">Continue reading <span class="screen-reader-text">Problems Calculating Retention Rate</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/10/23/problems-calculating-retention-rate/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Behavioral versus Demographic Data</title>
		<link>https://blog.jimnovo.com/2024/10/08/behavioral-versus-demographic-data/</link>
					<comments>https://blog.jimnovo.com/2024/10/08/behavioral-versus-demographic-data/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Tue, 08 Oct 2024 19:02:21 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6081</guid>

					<description><![CDATA[Most businesses want their visitors or customers to &#8220;do something&#8221; &#8211; to take an action of some kind. Trying to drive action, businesses engage in marketing / advertising to reach &#8220;audiences&#8221; with their message. These audiences can be quantified in a number of ways using Demographics, Sociographics, and Psychographics for the purpose of &#8220;targeting&#8221; the &#8230; <a href="https://blog.jimnovo.com/2024/10/08/behavioral-versus-demographic-data/" class="more-link">Continue reading <span class="screen-reader-text">Behavioral versus Demographic Data</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/10/08/behavioral-versus-demographic-data/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>LTV Not Just About Sales &#038; Marketing Data: Check Service Problem Outcomes</title>
		<link>https://blog.jimnovo.com/2024/09/25/impact-of-service-problems-on-ltv/</link>
					<comments>https://blog.jimnovo.com/2024/09/25/impact-of-service-problems-on-ltv/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 25 Sep 2024 20:04:50 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6085</guid>

					<description><![CDATA[Often we spend a lot of time talking about analyzing &#8220;customer data&#8221;, and the implication is we are looking at marketing or sales related information. That may be true for companies just beginning to use customer data; this data often is the easiest to understand and access. But true data-driven organizations have analysts who reach &#8230; <a href="https://blog.jimnovo.com/2024/09/25/impact-of-service-problems-on-ltv/" class="more-link">Continue reading <span class="screen-reader-text">LTV Not Just About Sales &#38; Marketing Data: Check Service Problem Outcomes</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/09/25/impact-of-service-problems-on-ltv/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Creating Effective Retention Campaigns</title>
		<link>https://blog.jimnovo.com/2024/09/11/creating-effective-customer-retention-campaigns/</link>
					<comments>https://blog.jimnovo.com/2024/09/11/creating-effective-customer-retention-campaigns/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 11 Sep 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=6055</guid>

					<description><![CDATA[Have you ever offered a $100 off coupon to a new retail customer? I have. And guess what? There was no response, even though the average order size across all customers was $38! So how is this kind of situation possible? Some products attract customers that are only interested in that product, and they are &#8230; <a href="https://blog.jimnovo.com/2024/09/11/creating-effective-customer-retention-campaigns/" class="more-link">Continue reading <span class="screen-reader-text">Creating Effective Retention Campaigns</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/09/11/creating-effective-customer-retention-campaigns/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Customer Retention in a High Churn Business Model</title>
		<link>https://blog.jimnovo.com/2024/08/28/customer-retention-high-churn-business/</link>
					<comments>https://blog.jimnovo.com/2024/08/28/customer-retention-high-churn-business/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 28 Aug 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5995</guid>

					<description><![CDATA[Yea, sometimes customer retention is a very tough gig; some businesses are simply not likely to encourage repeat purchase. But you can still try, right? Or perhaps focus your efforts on where the real power to affect customer value is for this type of business &#8211; acquisition and onboarding. Let&#8217;s Drill Down &#8230; Q:&#160; I &#8230; <a href="https://blog.jimnovo.com/2024/08/28/customer-retention-high-churn-business/" class="more-link">Continue reading <span class="screen-reader-text">Customer Retention in a High Churn Business Model</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/08/28/customer-retention-high-churn-business/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Analyzing Airline Customer Frequency Programs</title>
		<link>https://blog.jimnovo.com/2024/08/14/analyzing-airline-customer-frequency-programs/</link>
					<comments>https://blog.jimnovo.com/2024/08/14/analyzing-airline-customer-frequency-programs/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Thu, 15 Aug 2024 00:10:11 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5875</guid>

					<description><![CDATA[Recency and the RFM model are both very powerful predictive models of customer behavior, But they&#8217;re not always the BEST models to use, because the nature of some business activities do not create the kinds of behavior these models are good at predicting. For example, any business &#8211; or segment of the business &#8211; that &#8230; <a href="https://blog.jimnovo.com/2024/08/14/analyzing-airline-customer-frequency-programs/" class="more-link">Continue reading <span class="screen-reader-text">Analyzing Airline Customer Frequency Programs</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/08/14/analyzing-airline-customer-frequency-programs/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Second Purchase Marketing</title>
		<link>https://blog.jimnovo.com/2024/07/31/second-purchase-marketing-retention/</link>
					<comments>https://blog.jimnovo.com/2024/07/31/second-purchase-marketing-retention/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 31 Jul 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Digital Analytics]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5884</guid>

					<description><![CDATA[HIgh end hardgoods. One of the most difficult retail categories to deal with from a customer retention perspective, both offline and online. Only vehicles are tougher. In some ways, the category can be easier online, but perhaps not for a single local store due to competition. So what&#8217;s the best way to attack the repeat &#8230; <a href="https://blog.jimnovo.com/2024/07/31/second-purchase-marketing-retention/" class="more-link">Continue reading <span class="screen-reader-text">Second Purchase Marketing</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/07/31/second-purchase-marketing-retention/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Using RFM Scores to Predict Profits</title>
		<link>https://blog.jimnovo.com/2024/07/17/using-rfm-scores-to-predict-profits/</link>
					<comments>https://blog.jimnovo.com/2024/07/17/using-rfm-scores-to-predict-profits/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 17 Jul 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5846</guid>

					<description><![CDATA[Subsidy costs. You&#8217;re just starting to hear people talk about these ideas in online marketing, but they&#8217;ve been around for years offline in direct marketing. The basic idea is this: sending a discount to someone who is very highly likely to make a purchase without the discount is a waste of margin dollars best spent &#8230; <a href="https://blog.jimnovo.com/2024/07/17/using-rfm-scores-to-predict-profits/" class="more-link">Continue reading <span class="screen-reader-text">Using RFM Scores to Predict Profits</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/07/17/using-rfm-scores-to-predict-profits/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>How Long is a Customer  LifeTime?</title>
		<link>https://blog.jimnovo.com/2024/07/03/how-long-is-customer-lifetime/</link>
					<comments>https://blog.jimnovo.com/2024/07/03/how-long-is-customer-lifetime/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 03 Jul 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing Research]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5872</guid>

					<description><![CDATA[There&#8217;s always two questions about the topic of Lifetime Value &#8211; how do you quanitify value, and how long is / how do you measure / decide what a Lifetime is? For now we&#8217;ll leave the value question unanswered, because a lot of that depends on company culture and what question you are trying to &#8230; <a href="https://blog.jimnovo.com/2024/07/03/how-long-is-customer-lifetime/" class="more-link">Continue reading <span class="screen-reader-text">How Long is a Customer  LifeTime?</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/07/03/how-long-is-customer-lifetime/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Using Multiple, Related Customer Models Across the LifeCycle</title>
		<link>https://blog.jimnovo.com/2024/06/19/using-multiple-customer-lifecycle-models/</link>
					<comments>https://blog.jimnovo.com/2024/06/19/using-multiple-customer-lifecycle-models/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 19 Jun 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5868</guid>

					<description><![CDATA[So you have all these simple but powerful customer models &#8211; Recency&#160;alone,&#160;Latency, &#160;RFM, or&#160;LifeCycle Grids &#8211; how do you know which one (or ones) are best to use for your business? Guess what &#8211; it depends on the specific features of your business and also how you run the business. Now, while that might sound &#8230; <a href="https://blog.jimnovo.com/2024/06/19/using-multiple-customer-lifecycle-models/" class="more-link">Continue reading <span class="screen-reader-text">Using Multiple, Related Customer Models Across the LifeCycle</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/06/19/using-multiple-customer-lifecycle-models/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Segment to Best Determine LifeTime Value (LTV)</title>
		<link>https://blog.jimnovo.com/2024/06/05/segment-to-best-determine-lifetime-value-ltv/</link>
					<comments>https://blog.jimnovo.com/2024/06/05/segment-to-best-determine-lifetime-value-ltv/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 05 Jun 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Digital Analytics]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5849</guid>

					<description><![CDATA[LTV has to be actionable.&#160; If &#160;you can&#8217;t take action on the information, it&#8217;s not relevant anyway. There you go, the most universally true rule when attempting calculation of LTV. And the best / easiest way to accomplish this is to identify similar customer behaviors and segment the customers by these behaviors &#8211; THEN figure &#8230; <a href="https://blog.jimnovo.com/2024/06/05/segment-to-best-determine-lifetime-value-ltv/" class="more-link">Continue reading <span class="screen-reader-text">Segment to Best Determine LifeTime Value (LTV)</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/06/05/segment-to-best-determine-lifetime-value-ltv/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Modeling Defections &#8211; When is a Customer No Longer a Customer?</title>
		<link>https://blog.jimnovo.com/2024/05/15/extended-purchase-latency-recency-models/</link>
					<comments>https://blog.jimnovo.com/2024/05/15/extended-purchase-latency-recency-models/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 15 May 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing / Tech Interface]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=5823</guid>

					<description><![CDATA[Metrics are not usually also Models; the metrics have to be fine-tuned / combined and built up into models. And executing this process usually depends alot on what type of business is being analyzed, and what kind of problem is targeted for a solution. So while it&#8217;s pretty simple to define a metric, creating a &#8230; <a href="https://blog.jimnovo.com/2024/05/15/extended-purchase-latency-recency-models/" class="more-link">Continue reading <span class="screen-reader-text">Modeling Defections &#8211; When is a Customer No Longer a Customer?</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/05/15/extended-purchase-latency-recency-models/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>When Acquisition Spoils Retention</title>
		<link>https://blog.jimnovo.com/2024/05/01/when-acquisition-spoils-retention/</link>
					<comments>https://blog.jimnovo.com/2024/05/01/when-acquisition-spoils-retention/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 01 May 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytical Culture]]></category>
		<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<category><![CDATA[Customer State]]></category>
		<category><![CDATA[Relationship Marketing]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=4737</guid>

					<description><![CDATA[OK, here&#8217;s a bit of a tough one &#8211; what if while investigating customer retention problems you find out that customer defection is highly correlated to specific salespeople or marketing programs? What if I told you this correlation is pretty common &#8211; but unrecognized, because hardly anybody goes looking for it? And if found, find &#8230; <a href="https://blog.jimnovo.com/2024/05/01/when-acquisition-spoils-retention/" class="more-link">Continue reading <span class="screen-reader-text">When Acquisition Spoils Retention</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/05/01/when-acquisition-spoils-retention/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>How to Define &#8220;Frequency&#8221; Metric in B2B</title>
		<link>https://blog.jimnovo.com/2024/04/17/define-frequency-metric-b2b/</link>
					<comments>https://blog.jimnovo.com/2024/04/17/define-frequency-metric-b2b/#respond</comments>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Wed, 17 Apr 2024 19:00:00 +0000</pubDate>
				<category><![CDATA[Analytics Education]]></category>
		<category><![CDATA[Customer Experience]]></category>
		<category><![CDATA[DataBase Marketing]]></category>
		<category><![CDATA[Driller Q & A]]></category>
		<category><![CDATA[Marketing Research]]></category>
		<category><![CDATA[Marketing thru Operations]]></category>
		<category><![CDATA[Measuring Engagement]]></category>
		<guid isPermaLink="false">https://blog.jimnovo.com/?p=4728</guid>

					<description><![CDATA[If you&#8217;re not really clear on what you&#8217;re trying to accomplish, designing a successful customer retention program can be a bit of a struggle. Hey, maybe you just don&#8217;t know what to look for / what needs fixing / where to start? Gotcha, fellow Driller, the current value / potential value matrix is a great &#8230; <a href="https://blog.jimnovo.com/2024/04/17/define-frequency-metric-b2b/" class="more-link">Continue reading <span class="screen-reader-text">How to Define &#8220;Frequency&#8221; Metric in B2B</span> <span class="meta-nav">&#8594;</span></a>]]></description>
		
					<wfw:commentRss>https://blog.jimnovo.com/2024/04/17/define-frequency-metric-b2b/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>
