analytics

8月 272016
 

For the uninitiated, SAS 360 Engage enables organizations to interact with consumers by allowing them to create, manage and deliver digital content over web and mobile channels.  Wait a minute. SAS does more than the analytics? That is correct. SAS 360 Engage is a marketing super force serving as a one-stop shop for data capture all the way through delivering highly-targeted, personalized digital experiences.

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Being able to dynamically place content and offers into digital channels – across devices and points in time – is nothing new for savvy marketing brands focused on optimization. As customer journeys spread across fragmented touch points while customers are demanding seamless and relevant experiences, content-oriented marketers have been forced to reevaluate their strategies for engagement. But the complexity, pace and volume of modern marketing easily overwhelms traditional planning and design approaches that rely on historical conventions, myopic single-channel perspectives and sequential act-and-learn iteration.

Presently, marketers primarily use a variety of content optimization approaches that include A/B testing and multivariate testing. A/B testing, at its simplest, is a method of website or mobile optimization in which the conversion rates of two versions of a page are compared using visitor response rates. By tracking the way visitors interact with the content– the videos they watch, the buttons they click, or whether they sign up for a newsletter – you can infer which version of the content is most effective.

Due to the popularity of this technique, SAS 360 Engage supports A/B/n testing.  A/B/n testing is an extension of A/B testing, where “N” refers to the number of versions being tested, anywhere from two versions to the “nth” version. For example, when a brand has more than one idea for what the ideal digital experience should be, A/B/n can be used to compare each hypothesis and produce an optimized decision based on data, not subjectivity.

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Testing is attractive because it is efficient, measurable and serves as a machete cutting through the noise and assumptions associated with delivering effective experiences. In parallel, the evolving marketing landscape is driving a greater mandate for testing: to operate in more channels, handle more data and support more users. Testing must mature beyond traditional on-site experimentation to fully optimize a multifaceted customer journey.

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The majority of today’s technologies for personalization have generally failed to effectively use data science to offer consumers a contextualized digital experience. Many of today’s offerings are based on simple rules-based segmentation to drive recommendations. Building off the benefits of multi-channel A/B/n testing, this is where SAS 360 Engage injects its analytical muscle to differentiate from other personalization technologies.  Let's break this down:

  • At the conclusion of an A/B/n test, there is usually a winner and one or more losers.
  • Is there really one superior experience for your entire marketable audience? Is it possible that experiences should vary by segment?

Performing algorithmic segmentation sounds awesome, but who really has the time to do it? We have so many tests to run.360 Engage 4

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The time has arrived for predictive marketing to have its moment in the sun, and with Forrester recently naming SAS the leader in customer analytics, it's official - the 800-pound gorilla in advanced analytics is locked in on solving complex issues facing the space of data-driven marketing. Making digital personalization more relevant for target audiences is just like preparing a delicious meal; it all comes down to the ingredients and preparation process to rise to the occasion!

A beautiful and interpretable visualization is generated highlighting what is unique about this segment, as compared to everyone else who was exposed to the test. If the brand wants to target this audience in future campaigns, a single click populates this segment in the platform for future journey orchestration.

If you look closely at the image, you will note in the upper half of the report that the winner of the A/B/n test is variant A. However, the lower half of the report showcases a newly discovered segment. It turns out that when a specific customer segment with recent purchase, stay and amenity activity interacts with this hospitality brand, variant B produces better results. How did SAS 360 Engage do this? By applying automated firepower (i.e. algorithmic clustering) to produce this prescriptive and actionable insight. To learn more about this segment, marketers can profile the audience:

SAS 360 Engage was built with the recognition that some marketing teams don't have data scientists available, and have real needs for analytical automation. To improve upon the concept of A/B/n testing, augmenting this capability with automated, algorithmic segmentation with prescriptive results addresses an important need. Let's assume you've run an A/B/n test with four versions of a page, and variant A was crowned the champion. Wouldn't it be nice to know that if a specific segment arrived at your website, an alternative experience would facilitate a better result?

tags: A/B Testing, Campaign Management, customer journey, data science, digital marketing, Digital Personalization, marketing analytics, predictive analytics, Predictive Marketing, Prescriptive Analytics, SAS 360 Engage, SAS Customer Intelligence 360, segmentation

SAS 360 Engage: A/B testing and algorithmic segmentation was published on Customer Intelligence.

8月 262016
 

With the analytics skills gap and rise in big data, there’s never been a better time to study analytics. In this series, Students in Analytics, I’ll interview several students and recent grads about why they’re pursuing degrees in analytics. Jason Bentley is a PhD student at the University of Sydney. […]

The post Students in analytics: Jason Bentley appeared first on Generation SAS.

8月 252016
 

Have you ever wondered how far you live from the closest nuclear power plant? I've crunched the numbers for cities here in the US, and created an interactive SAS map to help answer that question! The average age of US nuclear power plants is 35 years, and there just doesn't […]

The post How close are you to a nuclear plant? appeared first on SAS Learning Post.

8月 232016
 

Gender and race discrimination has been banned in most countries for many years, although gender did have specific exclusions for the insurance industry, where the risk for males and females could be shown to substantially different (e.g. females have a higher life expectancy than males). In the European Union (EU) […]

It’s not fair… was published on SAS Voices.

8月 222016
 

A huge proportion of big data is unstructured text (such as client interactions, product reviews, call center logs, emails, blogs and tweets). Organizations starting to invest in advanced analytics often overlook the value text analytics could add to the process. But when data scientists or analysts get to work exploring […]

3 Steps to big data success with text analytics was published on SAS Voices.

8月 192016
 

Ever wanted to test out the latest SAS® technology on your own data, but lacked the time or administrative backing of IT to make that happen?  Ever wanted to test drive Hadoop with your own data and SAS® but are lacking the support or skills to do that?  If I piqued […]

The post Free POC, on the latest SAS technology, in your own office appeared first on SAS Learning Post.

8月 182016
 

If you're into 1980s pop music, then I bet you love Billy Joel's song We Didn't Start the Fire. But do you know every word, and the significance of every reference? Let's use SAS software to create an interactive visualization that will help you fully understand this song! I first saw […]

The post If we didn't start the fire, then who did? appeared first on SAS Learning Post.

8月 182016
 

You could say we've been working toward the internet of things (IoT) since computers were first invented. Look at how airplanes have changed from flying by wire to now, quite literally, flying by IoT (or connected plane). The connected car is another example of how big data analytics is the […]

Big data analytics had to come before IoT was published on SAS Voices.