Archive for the 'Predictive Analytics' Category

What might several application areas be for predictive analytics?

Monday, January 28th, 2008

<meta name="GENERATOR" content="OpenOffice.org 2.3 (Linux)" /> <style type="text/css"> <!-- @page { size: 8.5in 11in; margin: 0.79in } P { margin-bottom: 0.08in } --> </style></p> <p style="margin-bottom: 0in">The other day a friend of mine was asking me about possible business areas in which <a title="Predictive Analytics at Wikipedia" target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">predictive analytics</a> could be used. I told him that the use of <a title="Predictive Analytics at Wikipedia" target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">predictive analytics</a> was limited only by the imagination of the people using it and the availability of data to create the models. Because he wanted a more concrete answer, I mentioned these examples (I hope they would give you some ideas on how to use predictive analytics in your organization):</p> <p style="margin-bottom: 0in"> <ul> <li>For <strong>Financial Institutions</strong>:</li> <ul> <li><strong><em>Response</em></strong>: Which customers are likely to respond to a specific offer such as a lower interest rate on credit card.</li> <li><em><strong>Cross-sell</strong></em>: Which customers will apply for a mortgage given they already have a credit card with us?</li> <li><strong><em>Up-sell</em></strong>: Which customers will upgrade to a platinum card given that they have a gold card?</li> </ul> <li>For <strong>Retailers</strong>:</li> <ul> <li><em><strong>Supply Chain Management</strong></em>: What products are sold together?</li> <li><em><strong>Sales</strong></em>: What key factors are associated with predicting our sales? (location, store size, promotions, etc.)</li> </ul> <li>For <strong>Web-based Companies</strong>:</li> <ul> <li><strong><em>Web site optimization</em></strong>: How are the users in Calgary different from those in Edmonton with regards to how they navigate the site?</li> </ul> <li>For <strong>Cable Companies</strong>:</li> <ul> <li><strong><em>Churn</em></strong>: Which customers are likely to leave and sign up with another company?</li> </ul> <li>For <strong>Nonprofit Organizations</strong>:</li> <ul> <li><em><strong>Donor identification</strong></em>: Who will give to us? Who will renew?</li> <li><strong><em>Strategic planning</em></strong>: Are we investing in the right areas to attain our campaign goal?</li> </ul> </ul> <p style="margin-bottom: 0in"> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/retail/" title="View all posts in Retail" rel="category tag">Retail</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a>, <a href="http://aranducorp.com/blog/category/fundraising/" title="View all posts in Fundraising" rel="category tag">Fundraising</a> | <a href="http://aranducorp.com/blog/2008/01/28/what-might-several-application-areas-be-for-predictive-analytics/#comments" title="Comment on What might several application areas be for predictive analytics?">1 Comment »</a></p> </div> <div class="post"> <h3 id="post-9"><a href="http://aranducorp.com/blog/2008/01/02/how-predictive-analytics-can-help-you-case-3-selling-your-home/" rel="bookmark" title="Permanent Link to How predictive analytics can help you. Case 3: Selling your home">How predictive analytics can help you. Case 3: Selling your home</a></h3> <small>Wednesday, January 2nd, 2008</small> <div class="entry"> <p><meta content="text/html; charset=utf-8" http-equiv="CONTENT-TYPE" /><title /><meta content="OpenOffice.org 2.0 (Linux)" name="GENERATOR" /><meta content="20070916;10251000" name="CREATED" /><meta content="20080102;16182500" name="CHANGED" /> <style type="text/css"> <!-- @page { size: 8.5in 11in; margin: 0.79in } P { margin-bottom: 0.08in } --> </style></p> <p style="margin-bottom: 0in"><a title="Predictive Analytics at Wikipedia" target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">Predictive analytics</a> or the analysis of current and historical data to make predictions about future events is being used to demystify the process of buying and selling <a title="Real Estate at Wikipedia" target="_blank" href="http://en.wikipedia.org/wiki/Real_estate">real estate</a>. <a title="Redfin: The Market-Leading Online Real Estate Brokerage" target="_blank" href="http://www.redfin.com/stingray/do/start">Redfin</a>, the first online brokerage for residential real estate, is using a branch of predictive analytics (<a title="Data Mining at Wikipedia" target="_blank" href="http://en.wikipedia.org/wiki/Data_Mining">data mining</a>) for lessons on how to sell homes. In the Fall of 2007, Redfin’s computer scientists analyzed data from more than 500,000 visitors to their listing of over 275,000 properties. The main finding of their study is that the primary determinant of how fast a home will sell, and for how much, is the home itself. However, by following seven recommendation that appear in their <a title="Seven Tactics for Selling Your Home" target="_blank" href="http://p1.rfimg.us/v4.3.6/images/4_0/text/pdf/Seven_Tactics_for_Selling_A_Home.pdf">report</a>, home sellers will yield a small but significant improvement in the results.</p> <p style="margin-bottom: 0in">Below is a summary of Redfin’s seven tactics for selling your home. For additional details, please, refer to the <a title="Seven Tactics for Selling Your Home" target="_blank" href="http://p1.rfimg.us/v4.3.6/images/4_0/text/pdf/Seven_Tactics_for_Selling_A_Home.pdf">Redfin’s report</a>.</p> <p style="margin-bottom: 0in"><meta content="text/html; charset=utf-8" http-equiv="CONTENT-TYPE" /><title /><meta content="OpenOffice.org 2.0 (Linux)" name="GENERATOR" /><meta content="20070916;10251000" name="CREATED" /><meta content="20080102;16182500" name="CHANGED" /> <style type="text/css"> <!-- @page { size: 8.5in 11in; margin: 0.79in } P { margin-bottom: 0.08in } --> </style></p> <ol> <li>Don’t overprice your property to avoid that it stays a long time in the market. The longer a property is in the market the more aggressive the buyers become in negotiating.</li> <li>Set your prices to show in web searchers. You need to take into account that buyers usually filter prices in $25,000 or $50,000 increments. For instance, a house priced at $300,000 is likely to be seen more than a house priced $301,000 because the $301,000 home will be excluded for buyers that set $300,000 as their maximum price.</li> <li>Debut your advertisement campaign on Friday to maximize the number of viewings during the first week.</li> <li>Stay engaged to increase your chances of selling your property faster.</li> <li>Market the property online using, for example, craiglist.</li> <li>Do not move until you have sold your house to avoid giving the impression that you are anxious to sell.</li> <li>Wait until neighboring foreclosures are off the market to avoid that low prices in the foreclosures affect your own pricing.</li> </ol> <p style="margin-bottom: 0in"> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/business-analytics/" title="View all posts in Business Analytics" rel="category tag">Business Analytics</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a>, <a href="http://aranducorp.com/blog/category/real-estate/" title="View all posts in Real Estate" rel="category tag">Real Estate</a> | <a href="http://aranducorp.com/blog/2008/01/02/how-predictive-analytics-can-help-you-case-3-selling-your-home/#respond" title="Comment on How predictive analytics can help you. Case 3: Selling your home">No Comments »</a></p> </div> <div class="post"> <h3 id="post-8"><a href="http://aranducorp.com/blog/2007/10/16/super-crunchers-a-fresh-view-to-predictive-analytics/" rel="bookmark" title="Permanent Link to Super Crunchers: a fresh view to predictive analytics">Super Crunchers: a fresh view to predictive analytics</a></h3> <small>Tuesday, October 16th, 2007</small> <div class="entry"> <p class="MsoNormal">Super Crunchers? What are they? Super Crunchers is a term used by <a target="_blank" href="http://en.wikipedia.org/wiki/Ian_Ayres">Ian Ayres</a> to refer to organizations that analyze massive datasets at lightning speed to gain greater insights into human behavior. In other words, Super Crunchers are organizations that are using predictive analytics to gain insights from data.</p> <p class="MsoNormal"> <p class="MsoNormal">If you want to have a fresh view on how predictive analytics can help you, I recommend you to have a look at the webcast: <a target="_blank" href="http://www.bettermanagement.com/seminars/seminar.aspx?l=14547">Super Crunchers: Why Thinking-By-Numbers is the New Way to be Smart</a>. In this webcast, <a target="_blank" href="http://en.wikipedia.org/wiki/Ian_Ayres">Ian Ayres</a>, the author of <a target="_blank" href="http://www.randomhouse.com/bantamdell/supercrunchers/">Super Crunchers</a>, tells the secrets of the “Super Crunchers”</p> <p class="MsoNormal"> <p class="MsoNormal">From the description of the webcast:</p> <p class="MsoNormal"> <blockquote> <p class="MsoNormal">In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us. Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.</p> </blockquote> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a> | <a href="http://aranducorp.com/blog/2007/10/16/super-crunchers-a-fresh-view-to-predictive-analytics/#respond" title="Comment on Super Crunchers: a fresh view to predictive analytics">No Comments »</a></p> </div> <div class="post"> <h3 id="post-6"><a href="http://aranducorp.com/blog/2007/10/02/predictive-analytics-how-long-before-seeing-the-fruits/" rel="bookmark" title="Permanent Link to Predictive analytics: how long before seeing the fruits?">Predictive analytics: how long before seeing the fruits?</a></h3> <small>Tuesday, October 2nd, 2007</small> <div class="entry"> <p style="margin-bottom: 0in">In two previous posts (<a title="Predictive Analytics in Retail" href="http://aranducorp.com/blog/2007/09/18/how-predictive-analytics-can-help-you-case-1-retail/">How predictive analytics can help you. Case 1: Retail</a> and <a title="Predictive Analytics in Fundraising" href="http://aranducorp.com/blog/2007/09/25/how-predictive-analytics-can-help-you-case-2-fundraising/">Case 2: Fundraising</a>), I described some of the benefits of implementing predictive analytics solutions. If you read with interest those articles, you might be wondering: how long does it take to implement an analytics strategy and start seeing the benefits? The short answer is: “It depends”. Before embarking on an analytics adventure, you need to identify a part of your business that you want to improve. It is important that you can collect data on that area (do you have the hardware, software, and communications strategy for doing so?). You must also remember that collecting data takes time. For instance, one manager of customer analytics at <a target="_blank" title="UPS Global Home" href="http://www.ups.com/">UPS</a> noted that they collected data for four years before it became usable. The next step is to make sure the leaders of your organizations are on the same page regarding making fact-based decisions. You must also secure and build analytics skills in your organization to ensure smooth “execution” and keep your competitive advantage. Once you have everything in place, you might be looking to several months for a pilot project on a very specific area or several years for an organization-wide analytics strategy.</p> <p style="margin-bottom: 0in">To conclude, I will leave you an excellent advice offered by <a target="_blank" title="Tom Davenport - Make IT Matter" href="http://www.tomdavenport.com/">Thomas Davenport</a> on his article: “<a target="_blank" title="Competing on Analytics" href="http://www.babsonknowledge.org/analytics.pdf">Competing on Analytics</a>”</p> <blockquote> <p style="margin-bottom: 0in">“The best advice is to begin working on it [an analytics implementation] now, because it typically requires several years for analytical competitive strategies to come to fruition. […] However, despite the difficulty and expense of establishing these capabilities, many of the firms we have identified as early adopters of analytical strategies are clear leaders in their industries. This suggests the time and trouble necessary to become analytical competitors are definitely worthwhile.”</p> </blockquote> <p style="margin-bottom: 0in">To learn more:</p> <p style="margin-bottom: 0in"><a target="_blank" title="Competing on Analytics" href="http://www.babsonknowledge.org/analytics.pdf">Competing on Analytics</a> by Thomas Davenport, Don Cohen, and Al Jacobson</p> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/business-analytics/" title="View all posts in Business Analytics" rel="category tag">Business Analytics</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a> | <a href="http://aranducorp.com/blog/2007/10/02/predictive-analytics-how-long-before-seeing-the-fruits/#respond" title="Comment on Predictive analytics: how long before seeing the fruits?">No Comments »</a></p> </div> <div class="post"> <h3 id="post-5"><a href="http://aranducorp.com/blog/2007/09/25/how-predictive-analytics-can-help-you-case-2-fundraising/" rel="bookmark" title="Permanent Link to How predictive analytics can help you. Case 2: Fundraising">How predictive analytics can help you. Case 2: Fundraising</a></h3> <small>Tuesday, September 25th, 2007</small> <div class="entry"> <p><meta http-equiv="CONTENT-TYPE" content="text/html; charset=utf-8" /><title /><meta name="GENERATOR" content="OpenOffice.org 2.0 (Linux)" /><meta name="CREATED" content="20070916;10251000" /><meta name="CHANGED" content="20070925;14413500" /> <style type="text/css"> <!-- @page { size: 8.5in 11in; margin: 0.79in } P { margin-bottom: 0.08in } --> </style></p> <p style="margin-bottom: 0in">Donors rarely explicitly reveal their preferences on what non-profit to support. They usually do so implicitly in their events attendance and membership participation. Analysing their behavioral, demographics, geographic, and previous giving data, we can gain insights on what donors want to support, how much they can or are willing to donate, and how they choose between non-profits.</p> <p style="margin-bottom: 0in"> <p style="margin-bottom: 0in">Consider the following example: Suppose a person donates to a children charity. Would this indicate that the person would likely support an educational non-profit? What if the person donates only to one charity consistently? Would this indicate loyalty to that charity? Predictive analytics can help answer those questions by “figuring out” what is on the donors’ mind.</p> <p style="margin-bottom: 0in">Some Canadian organizations that are using analytics to gain insight on their potential donors and target their fundraising efforts more effectively are <a target="_blank" href="http://www.queensu.ca/">Queen’s University</a>, <a target="_blank" href="http://www.ivey.uwo.ca/">Richard Ivey School of Business</a> at the <a target="_blank" href="http://www.uwo.ca/">University of Western Ontario</a>, <a target="_blank" href="http://www.utoronto.ca/">University of Toronto</a>, and <a target="_blank" href="http://www.msf.ca/en/index.html">Doctors Without Borders</a>.</p> <p style="margin-bottom: 0in"> <p style="margin-bottom: 0in">Predictive analytics allows organizations to “figure out” what is on the donors’ mind. Using this knowledge to optimize the performance of the fundraising programs is key to raise more revenue for their mission.</p> <p style="margin-bottom: 0in"> <p style="margin-bottom: 0in">To learn more:</p> <p style="margin-bottom: 0in"><a target="_blank" href="http://en.wikipedia.org/wiki/Main_Page">Wikipedia</a>’s entry on <a target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">predictive analytics</a></p> <p style="margin-bottom: 0in"><a target="_blank" href="http://en.wikipedia.org/wiki/Main_Page">Wikipedia</a>’s entry on <a target="_blank" href="http://en.wikipedia.org/wiki/Fundraising">fundraising</a></p> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/business-analytics/" title="View all posts in Business Analytics" rel="category tag">Business Analytics</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a>, <a href="http://aranducorp.com/blog/category/fundraising/" title="View all posts in Fundraising" rel="category tag">Fundraising</a> | <a href="http://aranducorp.com/blog/2007/09/25/how-predictive-analytics-can-help-you-case-2-fundraising/#respond" title="Comment on How predictive analytics can help you. Case 2: Fundraising">No Comments »</a></p> </div> <div class="post"> <h3 id="post-4"><a href="http://aranducorp.com/blog/2007/09/18/how-predictive-analytics-can-help-you-case-1-retail/" rel="bookmark" title="Permanent Link to How predictive analytics can help you. Case 1: Retail">How predictive analytics can help you. Case 1: Retail</a></h3> <small>Tuesday, September 18th, 2007</small> <div class="entry"> <p>Customers rarely explicitly reveal their preferences. They usually do so implicitly in their purchases and transactions. Analysing their purchases, we can gain insights on what customers want, how much they are willing to pay, and how they choose between competitors and competing brands.</p> <p>Consider the following example: Suppose a person’s credit card transactions includes a hockey stick. Would this indicate that the person likely plays hockey? What about if the same credit card is used during hockey season to buy hockey gloves and jerseys? Would this indicate, then, that the person likely plays hockey? What if the person purchased only a particular hockey team’s jerseys consistently? Would this indicate loyalty to that team? Predictive analytics can help answer those questions by “figuring out” what is on the customers’ mind.</p> <p>One business that illustrates profoundly the power of analytics is <a target="_blank" title="Wal-Mart" href="http://www.walmart.com/">Wal-Mart</a>. Wal-Mart’s ability to use predictive analytics to guess what customers will be interested in, how much they will buy, and at what price and its ability to act based on that information has made it a leader in the retail industry. For example, Wal-Mart have determine that before a hurricane, customers stock-up food items that do not require cooking or refrigeration. In that market segment, they found that Kellogg’s Strawberry Pop Tarts are the most popular. We can expect that Wal-Mart will make a rush order of Pop Tarts just before the hurricane hits.</p> <p>In short, predictive analytics allows retailers to “figure out” what is on the customers’ mind. Using this knowledge to optimize the performance of the entire value chain is key to outmaneuver competitors and guarantee success in today’s competitive marketplace.</p> <p>To learn more:</p> <ul> <li><a target="_blank" title="Predictive analytics" href="http://en.wikipedia.org/wiki/Predictive_analytics">Wikipedia’s entry on predictive analytics</a></li> <li><a target="_blank" title="Competing on analytics" href="http://www.amazon.com/Competing-Analytics-New-Science-Winning/dp/1422103323">Competing on Analytics</a> by T.H. Davenport and J.G. Harris</li> </ul> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/business-analytics/" title="View all posts in Business Analytics" rel="category tag">Business Analytics</a>, <a href="http://aranducorp.com/blog/category/retail/" title="View all posts in Retail" rel="category tag">Retail</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a> | <a href="http://aranducorp.com/blog/2007/09/18/how-predictive-analytics-can-help-you-case-1-retail/#respond" title="Comment on How predictive analytics can help you. Case 1: Retail">No Comments »</a></p> </div> <div class="post"> <h3 id="post-3"><a href="http://aranducorp.com/blog/2007/09/11/on-predictive-analytics/" rel="bookmark" title="Permanent Link to On Predictive Analytics">On Predictive Analytics</a></h3> <small>Tuesday, September 11th, 2007</small> <div class="entry"> <p><strong>What is predictive analytics?</strong></p> <p><a title="Wikipedia entry on predictive analytics" target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">Predictive analytics</a> is an umbrella term that groups techniques from <a title="Wikipedia entry on data mining" target="_blank" href="http://en.wikipedia.org/wiki/Data_mining">data mining</a>, <a title="Wikipedia entry on machine learning" target="_blank" href="http://en.wikipedia.org/wiki/Machine_learning">machine learning</a>, and <a title="Wikipedia entry on statistics" target="_blank" href="http://en.wikipedia.org/wiki/Statistics">statistics</a>. <a title="Wikipedia entry on predictive analytics" target="_blank" href="http://en.wikipedia.org/wiki/Predictive_analytics">Predictive analytics</a> is used to process trends, historical data, and current data to make informed predictions about future events.</p> <p><strong>What is the market size for predictive analytics?</strong></p> <p>According to <a target="_blank" title="IDC home" href="http://idc.com/">IDC</a> the revenues for predictive analytics reached US$ 1,244 Millions in 2006.</p> <p><strong>Which firms are major users of analytics services?</strong></p> <p>The list is big but some of the major users of analytics are:<br /> Wal- Mart, Dell, Amazon, Capital One, Boston Red Sox, Honda, Intel, Verizon, Novartis, Marriot, Netflix, Monster Canada, Scotiabank, ConocoPhillips Norway, and Environment Canada.</p> <p><strong>Who are the major players in analytics?</strong></p> <p>SAS, SPSS, Visual Numerics Inc., Oracle, Teradata, Microsoft, Insightful Corp., IBM, Fair Isaac, Unica Corp.</p> <p><strong>In which application areas are analytics services commonly used?</strong></p> <p>Some of the areas in which analytics are used are:<br /> Supply chain management, research and development, customer selection, pricing, quality assurance, financial performance, and recruitment.</p> <p><strong>What are some of the popular tools used for analytics?</strong></p> <p>Three of the most popular are: <span class="text">SAS Enterprise Miner, SPSS Clementine, and Oracle Data Miner</span></p> <p><strong>What training is available on predictive analytics?</strong></p> <p>Some universities offer training on data mining, statistics, and machine learning. You might want to check with your local universities. Most of the vendors mentioned above also offer good training programs. You can also find small companies such as <a target="_blank" title="Delivering the knowledge to make better decisions" href="http://www.aranducorp.com">AranduCorp</a> that offer training in particular areas (machine learning and data mining in <a title="Delivering the knowledge to make better decisions" href="http://www.aranducorp.com">AranduCorp</a>’s case).</p> <p><strong>Where can I learn more?</strong></p> <p>For a high level picture on the use of analytics you can have a look at the book:<br /> <a title="Competing on Analytics" target="_blank" href="http://www.amazon.com/Competing-Analytics-New-Science-Winning/dp/1422103323">Competing on Analytics: The New Science of Winning</a><br /> by Thomas H. Davenport and Jeanne G. Harris </p> </div> <p class="postmetadata">Posted in <a href="http://aranducorp.com/blog/category/business-analytics/" title="View all posts in Business Analytics" rel="category tag">Business Analytics</a>, <a href="http://aranducorp.com/blog/category/predictive-analytics/" title="View all posts in Predictive Analytics" rel="category tag">Predictive Analytics</a> | <a href="http://aranducorp.com/blog/2007/09/11/on-predictive-analytics/#respond" title="Comment on On Predictive Analytics">No Comments »</a></p> </div> <div class="navigation"> <div class="alignleft"></div> <div class="alignright"></div> </div> </div> <div id="sidebar"> <ul> <li> <form method="get" id="searchform" action="http://aranducorp.com/blog/"> <div><input type="text" value="" name="s" id="s" /> <input type="submit" id="searchsubmit" value="Search" /> </div> </form> </li> <!-- Author information is disabled per default. 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