--- title: "Opera Solutions' Blog: The Hottest Spot for Practical AI and Big Data Science | Marketing (2)" description: Marketing | Opera Solutions is the largest independent predictive analytics company in the world, providing Practical AI and Big Data Analytics as an ongoing service to blue-chip clients across the globe. (2) --- [![](https://blog.operasolutions.com/hs-fs/hubfs/Opera_Solutions_Logo_Standard_RGB-72.png?width=369&height=202&name=Opera_Solutions_Logo_Standard_RGB-72.png "Opera_Solutions_Logo_Standard_RGB-72.png")](https://www.operasolutions.com/) ![Blog_Header-4](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Header-4.png?width=3377&name=Blog_Header-4.png "Blog_Header-4") [![Blog_Banner_v3](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Banner_v3.png?width=3713&name=Blog_Banner_v3.png "Blog_Banner_v3")](https://blog.operasolutions.com) ## [Customer Aspirational Value – A First Principle for Business](https://blog.operasolutions.com/customer-aspirational-value-a-first-principle-for-business) Posted by [Georges Smine](https://blog.operasolutions.com/author/georges-smine) on Fri, Jun 10, 2016 - [Tweet](https://twitter.com/share) [![grec_banner-no_Webinar.jpg](https://blog.operasolutions.com/hubfs/grec_banner-no_Webinar.jpg)](https://blog.operasolutions.com/customer-aspirational-value-a-first-principle-for-business) --- Conventional wisdom leads you to think that when a company knows its customers, it ends up providing better service, increasing loyalty, and generating more sales. Right? Yes, but the truth lies between what is desired and what is achieved. Opera Solutions has been helping Fortune 500 companies apply Big Data analytics to address challenges in operations, sales, and marketing, among other business functions. In today’s business climate, one of the most relevant challenges is how businesses can most effectively grow revenues from their existing customers. We have chosen this to be the topic of our next [webinar](https://www.brighttalk.com/webcast/14039/206753). [Read More](https://blog.operasolutions.com/customer-aspirational-value-a-first-principle-for-business) Topics: [Signal Hub Technologies](https://blog.operasolutions.com/topic/signal-hub-technologies), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [The Key to Making Big Data Valuable: Make It Personal](https://blog.operasolutions.com/the-key-to-making-big-data-valuable-make-it-personal) Posted by [Laks Srinivasan](https://blog.operasolutions.com/author/laks-srinivasan) on Mon, Oct 26, 2015 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hubfs/OS_SignalCentral_SandHill_Byline_GP_2015_V1.0-02-1.png)](https://blog.operasolutions.com/the-key-to-making-big-data-valuable-make-it-personal) Most companies realize they are sitting on a treasure trove of customer data that has the potential to deliver tremendous business benefits; however, most also have no idea how to realize those benefits. How can companies use their data to bring in more customers, increase the amount they spend, and make them more loyal? How can companies use data to turn unhappy customers into loyal champions of the brand? And perhaps most important, how can companies use that data to drive a significant increase in revenue?   [Read More](https://blog.operasolutions.com/the-key-to-making-big-data-valuable-make-it-personal) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [The Realization of Personalized Marketing](https://blog.operasolutions.com/the-realization-of-personalized-marketing) Posted by [Sarah Anderson](https://blog.operasolutions.com/author/sarah-anderson) on Thu, May 07, 2015 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-2640182200-jpg/images/os_signalcentral_personalization-optb_gp_2015_v1.0.jpg)](https://blog.operasolutions.com/the-realization-of-personalized-marketing) *2015 could be the year that true personalization finally takes hold, but to achieve it, you’ll need to change the way you think about marketing.* Customers expect to be treated as individuals. They require relevancy and prefer having a relationship with a company that keeps track of their preferences, purchases, and correspondence. Customers are ready for personalized marketing, and now, finally, more and more companies are, too. [Read More](https://blog.operasolutions.com/the-realization-of-personalized-marketing) Topics: [Analytics](https://blog.operasolutions.com/topic/analytics), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [How Data Science Adds Value to Credit Card Loyalty Programs](https://blog.operasolutions.com/bid/397748/How-Data-Science-Adds-Value-to-Credit-Card-Loyalty-Programs) Posted by [Christopher Bazett](https://blog.operasolutions.com/author/christopher-bazett) on Mon, Oct 06, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1763353669-jpg/images/os_signalcentral_spend_passion-main_gp_2014_fnl.jpg)](https://blog.operasolutions.com/bid/397748/How-Data-Science-Adds-Value-to-Credit-Card-Loyalty-Programs) Most redemption programs suffer from the same challenge: delivering rewards that customers actually *want*. To make this possible, the programs offer ever-more rewards, which puts the onus on the customer to find desirable ways to spend their points. In the end, redeeming points can be more of a chore than a reward, ultimately diminishing the value of the very program that was supposed to create value and differentiation in a crowded space. But with millions of customers, no one (or even 100) reward(s) will meet the desires of everyone. So what are credit card issuers to do? How do they put the value back into these programs, so customers are incentivized to choose one card over another? [Read More](https://blog.operasolutions.com/bid/397748/How-Data-Science-Adds-Value-to-Credit-Card-Loyalty-Programs) Topics: [Data Science](https://blog.operasolutions.com/topic/data-science), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [How Telcos Are Using Signals to Drive Savings and Revenues](https://blog.operasolutions.com/bid/396997/how-telcos-are-using-signals-to-drive-savings-and-revenues) Posted by [Ankur Desai](https://blog.operasolutions.com/author/ankur-desai) on Thu, Sep 25, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1680620692-jpg/images/os_signalcentral-telco-savings-optc_gp_2014_v1.0-300.jpg)](https://blog.operasolutions.com/bid/396997/how-telcos-are-using-signals-to-drive-savings-and-revenues) When to nudge a delinquent customer for a payment — that is the question. Or rather, that is one of many — many — questions that Signals are helping telecom companies (telcos) answer. Because *when* to call and ask for payment can actually help determine *whether* to call at all, and eliminating calls can lead to significant savings. So how do Signals do this? And more important, how can telcos, specifically, take advantage of these Signals to improve customer experience and maximize bottom-line impact? [Read More](https://blog.operasolutions.com/bid/396997/how-telcos-are-using-signals-to-drive-savings-and-revenues) Topics: [Analytics](https://blog.operasolutions.com/topic/analytics), [Signals](https://blog.operasolutions.com/topic/signals), [Marketing](https://blog.operasolutions.com/topic/marketing), [Supply Chain & Operations](https://blog.operasolutions.com/topic/supply-chain-operations) ## [How Data Science Helps Ease the Pain of Flight Cancelations](https://blog.operasolutions.com/bid/394687/how-data-science-helps-ease-the-pain-of-flight-cancelations) Posted by [Chunping Wang](https://blog.operasolutions.com/author/chunping-wang) on Wed, Sep 03, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1483550781-jpg/images/os_signalcentral_airline_cancellations_opt_a_gp_2014_v1.0.jpg)](https://blog.operasolutions.com/bid/394687/how-data-science-helps-ease-the-pain-of-flight-cancelations) We’ve all been there. That place in the airport where you’ve just learned your flight has been canceled. If the weather’s bad, you can understand and roll with it. But if it seems arbitrary and royally screws up your plans — well, that’s another story. As a customer, you wonder, “Why do airlines do this? And how do they decide that my flight is canceled when others are not?” But airlines are asking their own questions, namely: “We have to cancel X number of flights, but which flights should we cancel to minimize the loss of revenue and customer loyalty?” Here, we delve into both sides of the issue, and the answers should provide a little context — and hopefully quell the frustration for everyone. [Read More](https://blog.operasolutions.com/bid/394687/how-data-science-helps-ease-the-pain-of-flight-cancelations) Topics: [Data Science](https://blog.operasolutions.com/topic/data-science), [Signal Hub Technologies](https://blog.operasolutions.com/topic/signal-hub-technologies), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [My Struggle With Marketing Automation](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) Posted by [Todd Higginson](https://blog.operasolutions.com/author/todd-higginson) on Mon, Jun 30, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1106290924-jpg/images/wheels.jpg)](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) *Marketing automation's time has finally come, but it's been a long, tortuous road.* I’m a big fan of marketing automation. My experience goes back a few years. I was just getting settled at a new company when our CFO received a renewal invoice from a marketing automation vendor. She didn’t know how we were using the software, and neither did I.  [Read More](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [Data Science: Recommender Engines with Collaborative Filtering](https://blog.operasolutions.com/bid/387700/data-science-recommender-engines-with-collaborative-filtering) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Mon, Jun 02, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-921967470-jpg/images/os_signal-central-recommendation_gp_2014_v2.0-300.jpg)](https://blog.operasolutions.com/bid/387700/data-science-recommender-engines-with-collaborative-filtering) Ever wonder how services like Netflix or Pandora choose media to suggest to you? If you’ve been reading this blog for a while, you’re familiar — at least a little bit — with recommender engines. In our post “[How Machine Learning Will Affect Your Next Vacation,](https://blog.operasolutions.com/bid/350568/How-Machine-Learning-Will-Affect-Your-Next-Vacation)” we talked about the impact machine-learning recommender engines have on regular consumers. But here, we want to dive deeper and talk about the math and science behind recommender engines. [Read More](https://blog.operasolutions.com/bid/387700/data-science-recommender-engines-with-collaborative-filtering) Topics: [Data Science](https://blog.operasolutions.com/topic/data-science), [Analytics](https://blog.operasolutions.com/topic/analytics), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [Increase Revenue and Improve Business Strategy with Retail Analytics](https://blog.operasolutions.com/bid/381674/increase-revenue-and-improve-business-strategy-with-retail-analytics) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Mon, Apr 07, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-641000376-jpg/images/os_sc_retail_analytics_gp_2014_v1.6-09.jpg)](https://blog.operasolutions.com/bid/381674/increase-revenue-and-improve-business-strategy-with-retail-analytics) When people shop online, they know they’re sharing personal data to be collected and used for marketing purposes. And yet we’re surprised by how many companies fail to do even the bare minimum of analysis with the data they’ve painstakingly gathered. By implementing just a few basic analytics techniques into your marketing practices, you can quickly gain insight into your site’s performance, your customers’ satisfaction, and the effectiveness of your marketing campaigns. And if you take your analytics a few steps further, you can actually predict what your customers want and gain specific recommendations about how best to market to them — whether you have hundreds of customers or millions of them. Here, we’ll show you the basic building blocks of retail marketing analytics. The insights gathered from these techniques can help you optimize business strategies and increase revenues. We’ll show you which metrics, or key performance indicators (KPIs), matter the most and how they can be used to measure the success of a retail enterprise. We’ll also shed some light on what’s possible once you establish the basics: the more advanced analytics techniques that deliver predictive insights and recommended actions. Your crash course starts now. [Read More](https://blog.operasolutions.com/bid/381674/increase-revenue-and-improve-business-strategy-with-retail-analytics) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Analytics](https://blog.operasolutions.com/topic/analytics), [Signals](https://blog.operasolutions.com/topic/signals), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [Big Data — Are Marketers Blinded by Science?](https://blog.operasolutions.com/bid/379650/Big-Data-Are-Marketers-Blinded-by-Science) Posted by [Todd Higginson](https://blog.operasolutions.com/author/todd-higginson) on Fri, Mar 21, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-597964216-jpg/images/science_on_a_blue_board.jpg)](https://blog.operasolutions.com/bid/379650/Big-Data-Are-Marketers-Blinded-by-Science) Way back in 1982, Thomas Dolby famously quipped [“She blinded me with science and hit me with technology.”](http://www.dailymotion.com/video/x11lvw_thomas-dolby-she-blinded-me-with-sc_music) While musical tastes have since changed, the sentiment is stronger than ever. Science, especially data science, can be an intimidating subject for marketers and other non-mathematicians. [Read More](https://blog.operasolutions.com/bid/379650/Big-Data-Are-Marketers-Blinded-by-Science) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Analytics](https://blog.operasolutions.com/topic/analytics), [Marketing](https://blog.operasolutions.com/topic/marketing) [Previous](https://blog.operasolutions.com/topic/marketing/page/1) [All posts](https://blog.operasolutions.com/all) [Next](https://blog.operasolutions.com/topic/marketing/page/3) ### Subscribe to Email Updates ### Recent Posts ### Posts by Topic - [Big Data (75)](https://blog.operasolutions.com/topic/big-data) - [Machine Learning (38)](https://blog.operasolutions.com/topic/machine-learning) - [Data Science (32)](https://blog.operasolutions.com/topic/data-science) - [Signal Hub Technologies (27)](https://blog.operasolutions.com/topic/signal-hub-technologies) - [Analytics (26)](https://blog.operasolutions.com/topic/analytics) - [Marketing (23)](https://blog.operasolutions.com/topic/marketing) - [Press Releases (22)](https://blog.operasolutions.com/topic/press-releases) - [Arnab Gupta (16)](https://blog.operasolutions.com/topic/arnab-gupta) - [Events (10)](https://blog.operasolutions.com/topic/events) - [Healthcare (10)](https://blog.operasolutions.com/topic/healthcare) - [Signals (10)](https://blog.operasolutions.com/topic/signals) - [Partners (8)](https://blog.operasolutions.com/topic/partners) - [Artificial Intelligence (7)](https://blog.operasolutions.com/topic/artificial-intelligence) - [Competitions (7)](https://blog.operasolutions.com/topic/competitions) - [Supply Chain & Operations (7)](https://blog.operasolutions.com/topic/supply-chain-operations) - [Videos (6)](https://blog.operasolutions.com/topic/videos) - [Mobiuss (5)](https://blog.operasolutions.com/topic/mobiuss) - [Security & Defense (4)](https://blog.operasolutions.com/topic/security-defense) - [Data Equity (3)](https://blog.operasolutions.com/topic/data-equity) - [Customer Yield Management (2)](https://blog.operasolutions.com/topic/customer-yield-management) - [Hadoop (2)](https://blog.operasolutions.com/topic/hadoop) - [OperaNotebook (2)](https://blog.operasolutions.com/topic/operanotebook) - [Practical AI (2)](https://blog.operasolutions.com/topic/practical-ai) - [SoftwareUpdates (2)](https://blog.operasolutions.com/topic/softwareupdates) - [Spark (2)](https://blog.operasolutions.com/topic/spark) - [Transformative AI (2)](https://blog.operasolutions.com/topic/transformative-ai) - [CinemaAI (1)](https://blog.operasolutions.com/topic/cinemaai) - [Data Management (1)](https://blog.operasolutions.com/topic/data-management) - [Data Preparation (1)](https://blog.operasolutions.com/topic/data-preparation) - [Data Quality (1)](https://blog.operasolutions.com/topic/data-quality) - [EMR (1)](https://blog.operasolutions.com/topic/emr) - [Integration (1)](https://blog.operasolutions.com/topic/integration) - [MDM (1)](https://blog.operasolutions.com/topic/mdm) - [Optimization (1)](https://blog.operasolutions.com/topic/optimization) - [Payment Integrity (1)](https://blog.operasolutions.com/topic/payment-integrity) - [Personalization (1)](https://blog.operasolutions.com/topic/personalization) - [Revenue Commander (1)](https://blog.operasolutions.com/topic/revenue-commander) - [Revenue Cycle AI (1)](https://blog.operasolutions.com/topic/revenue-cycle-ai) - [SignalExpressionSyntax (1)](https://blog.operasolutions.com/topic/signalexpressionsyntax) - [Telecommunications and Media (1)](https://blog.operasolutions.com/topic/telecommunications-and-media) - [TravelAI (1)](https://blog.operasolutions.com/topic/travelai) - [predictive analytics (1)](https://blog.operasolutions.com/topic/predictive-analytics) - [revenue cycle management (1)](https://blog.operasolutions.com/topic/revenue-cycle-management) see all [![Opera Solutions](https://www.operasolutions.com/themes/opera/logo.svg)](http://operasolutions.com/) © Opera Solutions OpCo, LLC. 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