{"id":438,"date":"2019-12-30T08:41:40","date_gmt":"2019-12-30T08:41:40","guid":{"rendered":"https:\/\/spinanalyticsandstrategy.com\/blog\/?p=438"},"modified":"2019-12-30T08:41:40","modified_gmt":"2019-12-30T08:41:40","slug":"13-predictive-models-that-are-tagged-as-game-changer-for-business","status":"publish","type":"post","link":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/13-predictive-models-that-are-tagged-as-game-changer-for-business\/","title":{"rendered":"13 Predictive Models that are tagged as game-changer for business"},"content":{"rendered":"<h4><b>PREDICTIVE MODELS 2020<\/b><\/h4>\n<p><span style=\"font-weight: 400;\">Be more accurate towards forecasting your data. Know the hidden patterns within your data to explain statistical abnormalities and explore the relation behind the unexpected Customer Patterns and sudden fluctuations in the audience segmentation metrics.&nbsp;<\/span><\/p>\n<p><strong>Here are a few Predictive Models that make it happen:<\/strong><\/p>\n<h4><span style=\"text-decoration: underline;\"><strong>1. CUSTOMER SEGMENTATION:&nbsp;<\/strong><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Dividing customers into groups based on common characteristics is Customer Segmentation.&nbsp;&nbsp;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Knowing your customers and targeting them in the most relevant way to boost Customer Retention and Customer Satisfaction is the primary motive for any business.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Get Answers for every doubt you have related to your customers using this Model:<\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">&nbsp;Know your customer requirement before launching a new product<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Target specific Customer Branding<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Rebrand new customers<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Customer Demographics, Customer Buying Behavior, Customer Interests, and Customer Profiling are some of the additional benefits of the Customer Segmentation model that businesses look forward too.<\/span><\/p>\n<h4><span style=\"text-decoration: underline;\"><strong>2. CROSS SELL AND UP SELL MODELS:<\/strong><\/span><\/h4>\n<p><b>Looking for quick wins and easy growth?<\/b><\/p>\n<p><strong>Upselling&nbsp;and&nbsp;cross-selling<\/strong><span style=\"font-weight: 400;\"><strong>&nbsp;<\/strong>are considered to be the two most effective ways to boost revenues for retailers. Upsell is used when business owners want to convince their customers to purchase a more expensive&nbsp; product\/ service, while salespeople use cross-sell to encourage consumers to buy more products based on instinct.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is the strategy used by Cross-Sell and Up-Sell model:<\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">Loyal Clients Feedback First<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Business Quarterly Reviews<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Gathering testimonials and Case studies<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Blog sharing<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Trial and error<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Time to time discounts and Offers<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Know your Needs<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Employee Retention<\/span><\/li>\n<\/ul>\n<h4><span style=\"text-decoration: underline;\"><b>3. CHURN MODELS:<\/b><\/span><\/h4>\n<p><b>Customer Churn Prediction<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Churn Rate defines the percentage of Customer Retention for your products\/services. <\/span><span style=\"font-weight: 400;\">Customer Churn prediction tasks will often use customer data to determine:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">&nbsp;Time spent on a company website<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">&nbsp;Products\/ services&nbsp; purchased<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">&nbsp;Demographic information of users<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">&nbsp;Links clicked<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">&nbsp;Text analysis of product reviews<\/span><\/li>\n<\/ul>\n<p><b>Types of churn Models:<\/b><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Define Metrics with Consumer data<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Shifting insights based on Outputs<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Adding machine Learning to Churn<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><b>4. SENTIMENT ANALYSIS:<\/b><\/span><\/h4>\n<p><b>Discover Customer emotional connect towards a product\/service and boost Brand Reputation Management with Sentiment Analysis.<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Sentiment analysis and opinion mining find numerous applications in e-commerce, marketing, advertising, politics, and research, with:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Text Polarity<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Sentiment ranking<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Feature Sentiment Analysis<\/span><\/li>\n<\/ul>\n<h4><span style=\"text-decoration: underline;\"><b>5. PRICE PLANNING AND ANALYSIS:<\/b><\/span><\/h4>\n<p><b>It is important to analyze the pricing situation to develop a Price planning and Analysis strategy to:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Evaluate new product ideas<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Test marketing<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Introduce strategy<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Add Positioning&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <\/span><\/li>\n<\/ul>\n<p><b>Analyzing the pricing strategy benefits the business by:<\/b><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Establishing the responsiveness of the market to price<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Determining cost<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Analyzing competition<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Assessing legal constraints<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><strong>6. CUSTOMER SPENDING PATTERN ANALYSIS:&nbsp;<\/strong><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Customer spending patterns can be divided into regular spend pattern and lifestyle spend patterns.<\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400;\">Regular spending&nbsp; means basic necessities of life,&nbsp;<\/span><\/li>\n<li><span style=\"font-weight: 400;\">Lifestyle spending means spending on a computer, internet, car, cell phone, etc.<\/span><\/li>\n<\/ul>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Cultural<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Social<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Psychological<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Personal<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><b>7. PRODUCT RECOMMENDATION:<\/b><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Product recommendations will work for ECommerce Businesses where there are unfriendly sales assistants to help customers with each step of their shopping journey.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Product recommendation engines fall into 2 main categories:&nbsp;<\/span><\/p>\n<ol>\n<li><span style=\"font-weight: 400;\">Unpersonalized <\/span><\/li>\n<li><span style=\"font-size: 1rem;\">Personalized<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><b>8. IMPACT ANALYSIS OF SALES PROMOTION:<\/b><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">What are the promotional offers that has the highest impact at present?&nbsp; This question is relevant for every product\/service-based business.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Promotional analysis is a technique of analyzing success or failure of a promotion using past time series data.&nbsp;<\/span><\/p>\n<p><strong>Types of Promotion Analysis include:<\/strong><\/p>\n<ol>\n<li><span style=\"font-weight: 400;\"> Quantity\/Product concession<\/span><\/li>\n<li><span style=\"font-weight: 400;\"> Price discount<\/span><\/li>\n<li><span style=\"font-weight: 400;\"> Ads<\/span><\/li>\n<li><span style=\"font-weight: 400;\"> Shipping promotion<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><strong>9. CONSUMER CHOICE MODEL:<\/strong><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">The consumer choice model is used to determine the buying decisions for several commodities with different results. Such models take into consideration different families, classes, attitudes, etc.<\/span><\/p>\n<p><strong>The basic steps for Consumer Choice Model include:<\/strong><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Recognition<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Information search<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Alternative evaluation<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Purchase decision<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Post-purchase behavior<\/span><\/li>\n<\/ol>\n<h4><span style=\"text-decoration: underline;\"><strong>10. AD OPTIMIZATION<\/strong><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Some ads do well than others and generate more clicks, revenue, conversions, higher conversion ratio, etc. Based on these features, you can display the better performing ads more and show a red flag to the poor ones to boost the ROI.<\/span><\/p>\n<p><strong>The Ad Optimization models operate by:<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Adding a call-to-action model<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Adding emotional content<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Using Ad Extensions<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Trying dynamic keyword insertion<\/span><\/li>\n<\/ul>\n<h4><span style=\"text-decoration: underline;\"><b>11. PROPENSITY MODEL<\/b><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">The method of predicting the possibility that visitors, customers, or leads to conduct certain actions are termed as Propensity Analysis.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Based on Propensity modeling, marketing teams forecast the likelihood of whether a lead will convert to a customer, or will churn. Add to it, propensity modeling also helps to predict whether an email recipient will unsubscribe or not.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is how Propensity Modeling works:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Determining the features<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Preparing the propensity model<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Calculating your Propensity scores<\/span><\/li>\n<\/ul>\n<h4><span style=\"text-decoration: underline;\"><b>12. TIME SERIES AND CASUAL ANALYSIS:<\/b><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Time Series Analysis is used to clarify, track, and forecast casualty behaviors of customers. Whatever time-based patterns business experiences, Time Series Analysis can be used to determine it.<\/span><\/p>\n<p><strong>Time Series models can be applied to the following applications:<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Business- Web traffic, Supply Chain, etc.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Finance- Stock option, econometrics, etc.<\/span><\/li>\n<\/ul>\n<h4><span style=\"text-decoration: underline;\"><b>13.FRAUD MANAGEMENT AND PREVENTION:<\/b><\/span><\/h4>\n<p><span style=\"font-weight: 400;\">Spotting potentially fraudulent behavior and identifying unusual patterns of behavior consistent is termed as Fraud Management and Prevention.<\/span><\/p>\n<p><strong>Fraud Prevention models provide:<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Expert alert scenarios<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Real-time integration<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Quick roll-out<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Audited workflow and case management<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">High performing testing tools<\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>PREDICTIVE MODELS 2020 Be more accurate towards forecasting your data. Know the hidden patterns within your data to explain statistical<\/p>\n","protected":false},"author":1,"featured_media":520,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,3,8],"tags":[],"class_list":["post-438","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-big-data","category-predictive-analytics"],"_links":{"self":[{"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/posts\/438","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/comments?post=438"}],"version-history":[{"count":0,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/posts\/438\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/media\/520"}],"wp:attachment":[{"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/media?parent=438"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/categories?post=438"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.spinanalyticsandstrategy.com\/blog\/wp-json\/wp\/v2\/tags?post=438"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}