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Marketing Will Spend More on IT Than IT - Peter Buxbaum | Big Data Republic

Marketing Will Spend More on IT Than IT - Peter Buxbaum | Big Data Republic | Data Nerd's Corner | Scoop.it
Thanks to big data, the CMO will soon be spending more on IT than the CIO.
Carla Gentry CSPO's insight:

Marketing executives tend to lean toward the latter two alternatives, according to Gartner research, because they see marketing as a non-technical discipline that doesn't want to become technical. As data crunching becomes more prevalent in support of marketing, marketing services will become even more favored. And there are a growing number of companies selling these types of services into marketing organizations.

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Big Data, IOT and Security - OH MY!

Big Data, IOT and Security - OH MY! | Data Nerd's Corner | Scoop.it
Why should I – as a data scientist or analyst be worried about security, that’s not really part of my job is it? Well if you are a consultant or own your own business it is! Say, you download secure data from your clients and then YOU get hacked, guess who is liable if sensitive information is leaked or gets into the wrong hands? What if you develop a platform where the client’s customers can log in and check their accounts, credit card info and purchase histories are stored on this system, if stolen, it can set you up for a lawsuit. If you are a corporation, you are protected in some extents but what if you operate as a sole proprietor – you could lose your home, company and reputation. Still think security when dealing with big data isn’t important?
Carla Gentry CSPO's insight:
Organizations need to get better at protecting themselves and discovering that they’ve been breached plus we, the consultants, need to do a better job of protecting our own data and that means you can’t use password as a password! Let’s not make it easy for the hackers and let’s be sure that when we collect sensitive data and yes, even the data collected from cool technology toys connected to the internet, that we are security minded, meaning check your statements, logs and security messages - verify everything! When building your database, use all the security features available (masking, obfuscation, encryption) so that if someone does gain access, what they steal is NOT usable!
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Data Mining and Predictive Analysis

Data Mining and Predictive Analysis | Data Nerd's Corner | Scoop.it
Data collection and curing is the core foundation of most businesses. Database building thus is an important function and activity where enterprises invest heavily. With information now available o...
Carla Gentry CSPO's insight:

Once a database is compiled, it needs to be cleaned, analysed and potential connections need to be built. This process involves filtering the relevant data and identifying the possible predictors. Data Exploration also sets a premise for preliminary feature selection to manage number of variables. This data is then prepared for statistical analysis using a wide variety of graphical and statistical parameters. This helps identify the most relevant variables and setups the predictive models to be built.

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Sponsored post: Big Data and Intuition: The Future of Marketing

Sponsored post: Big Data and Intuition: The Future of Marketing | Data Nerd's Corner | Scoop.it
Technology isn’t only getting faster, it’s getting smarter. Computers are able to recognize and learn from patterns and make changes in real-time. Their improved analytic and decision-making abilities now allow them to outperform humans in areas such as medical diagnosis and customized marketing campaigns.
Carla Gentry CSPO's insight:

However, it’s hard for marketers to embrace data analysis when they’ve trusted their own gut to fuel decisions for so long. It’s a point of pride for many.  The problem is, the strategy frequently fails. A 20 year studyof political pundits found that they were only as accurate as a coin toss, suggesting that successful “intuitive” decisions are often a lucky guess.

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The big data cloud challenge

The big data cloud challenge | Data Nerd's Corner | Scoop.it
Intel and its partners here say that enterprises can now run Cloudera Enterprise on the CenturyLink Cloud powered by Intel Cloud Technology for what should appear to be fast deployment and fast time to insight i.e. what we actually want from big data analytics in the cloud. What we should also get (in theory) here is flexibility to move between cloud and on-premises solutions.
Carla Gentry CSPO's insight:

Why do we need analytics at this level? Because we want to analyze the ever-increasing volume and variety of big data that’s pouring in from social media, clickstreams (see below), videos, sensors and more

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Making sense through order

Making sense through order | Data Nerd's Corner | Scoop.it
Qian and Aslin developed a rational computational model to explain how people infer such hidden structures in sequential data, which they refer to as "bundles." They call it the Hibachi grill process (HGP) mixture model, named for a popular Japanese-style dining experience. Imagine a restaurant at which one entrée is the primary offering at each table and customers are seated based on their meal preferences. The owner is trying to maximize customer satisfaction and staff efficiency by having customers sit at the tables of their preferred dishes. The HGP mixture model extends the metaphor to include the assumption that restaurant customers typically arrive as groups of friends who have similar tastes and would want to sit at the same table. The model uses mathematical computations in an attempt to identify those hidden groups of friends from a stream of customers by relying on the stimulus order—that is, the order in which the customers enter the restaurant. The additional feature—that different groups of friends may share the same table—gives the model its name - a resemblance to the typical seating arrangement in many Hibachi grill restaurants in the US.
Carla Gentry CSPO's insight:

It is unclear whether people should discover bundles from order in every situation. The Ebola crisis offers a real-world scenario. "If, for example, a person heard about three consecutive patients at a medical clinic who were diagnosed with the Ebola virus, he or she might suspect a community-wide epidemic," said Aslin. But, it's possible that the information conveyed by the patient order was not meaningful. It may be that the three patients were from the same household and contracted the disease because they were living together.

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In Big Data, Shepherding Comes First

In Big Data, Shepherding Comes First | Data Nerd's Corner | Scoop.it
Big data is increasingly moving into the mainstream, as companies in every industry begin to combine an abundance of digital data with smart software to analyze it. It is a potential gold mine for software makers, with analysts predicting torrid growth for the market overall.

But building big data businesses is proving to be anything but a get-rich-quick game, and to require both agility and patience.
Carla Gentry CSPO's insight:

“Everybody is scrambling to take revenue where they can get it,” said Jonathan Gray, chief executive of Cask, which was previously Continuuity.

The challenge is similar for major technology corporations pursuing the big data market, but it is most acute for start-ups, which lack the financial ballast of the tech giants.

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What Artificial Intelligence Is Not

What Artificial Intelligence Is Not | Data Nerd's Corner | Scoop.it
Finally AI, like all computer programs, are ultimately controlled by humans. Of course AI can be designed with malicious intent and weaponized like nuclear or biological technology, but that’s not a fault of the science but of ourselves.
Carla Gentry CSPO's insight:

While Elon Musk is a personal hero of mine, and a genius on so many levels, his recent comments on artificial intelligence have been a little less than brilliant. He mentions that AI is more dangerous than nuclear weapons and that we may summon an AI “demon” (his words, not mine). My only explanation is that he must have fallen asleep watching Terminator.

 

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How to Become A Numbers Person in Journalism | Mediashift | PBS

How to Become A Numbers Person in Journalism | Mediashift | PBS | Data Nerd's Corner | Scoop.it
Another thing to remember in your quest for numeracy is that you must read. Not just essays and tutorials on the Internet; you must also read books. That’s how the pros do it. Some fabulous books that are written for ordinary people and journalists include: Sarah Cohen’s Numbers in the Newsroom; Jordan Ellenberg’s How Not to be Wrong; John Allen Paulos’ Innumeracy or A Mathematician Reads the Newspaper; Joel Best’s Damned Lies and Statistics.

As you read, rid yourself of math anxiety. Your math education has probably prepared you better than you think. Math (especially journalism math) is not an unapproachable discipline only for elites, as mathematician John Allen Paulos reminds us in his book Innumeracy. He writes, “Almost everybody can develop a workable understanding of numbers and probabilities, of relationships and arguments, of graphs and rates of change and of the ubiquitous role these notions play in everyday life.” Most of the battle for becoming numerate is confidence. You will make mistakes, sure. But you are writing journalism, which is a collective rather than a solo venture. Reach out to people who can help you validate your findings. Preferably before publication.
Carla Gentry CSPO's insight:

Of course, you’ll want to validate your potential finding with some shoe leather reporting. Data is a source, and it requires confirmation just like controversial information from any other source. You want to talk to the bridge inspection authorities to give them a chance to respond or clarify. Verify that the bridge was not inspected more recently than the data suggests. Talk to a bridge expert to find out why the bridge wasn’t inspected, or what the consequences could be if a bridge is in disrepair. You may also want to talk to other data journalists, who can be found on an email list such as NICAR or ddj.

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Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise on Environmental XPRT

Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise on Environmental XPRT | Data Nerd's Corner | Scoop.it
Rivo, the market leading cloud risk management platform for leading brands around the world has announced the recruitment of three world renowned experts in ...
Carla Gentry CSPO's insight:

Helping businesses leverage and understand Big Data and Analytics


Carla Gentry is one of the most respected names in data mining and analytics and behind the scenes Carla is working closely with the Rivo Lab on their Analytics solution helping to provide Advanced Analytical capabilities to Rivo’s customer base by bridging the chasm between technology and business needs. - Thanks for the Great intro, happy to be part of the team!!!

http://www.environmental-expert.com/news/rivo-s-thought-leader-programme-strengthens-big-data-and-sustainability-expertise-458151

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How CEOs recognize data as a corporate asset

How CEOs recognize data as a corporate asset | Data Nerd's Corner | Scoop.it
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Carla Gentry CSPO's insight:

As CIOs, you do not own the data,” Ms. Logan told the audience. “When retiring an asset, have you been able to get a straight answer from your business on how long to keep the data? They aren’t making decisions, and you can’t make the decisions about the data

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Carla Gentry CSPO's comment, December 14, 9:59 AM
Thanks for sharing my scoops :)
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Buddy Profiling: The Latest Big Data Tool

Buddy Profiling: The Latest Big Data Tool | Data Nerd's Corner | Scoop.it
Our social networks have incredible value in collecting data for business decisions.
Carla Gentry CSPO's insight:

We all prefer to interact with those we have some sort of connection to. We’ll only go to a party if so-and-so is there. We’re hesitant to accept a facebook request because we don’t have any mutual friends. We’ll only do it if they do it first. If we’ve never met someone, we’re a lot more likely to get along if we have a common friend. What’s true in our personal lives remains constant in our professional lives. We’re more likely to trust and do business with those we have a connection with over someone we don’t

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Data Science is real » Data Analysis

Data Science is real » Data Analysis | Data Nerd's Corner | Scoop.it
Data Mining is about explaining the past and predicting the future by means of data analysis.

We are collecting more data than ever before, yet many organizations are still looking for better ways to obtain value from their data and compete in the marketplace.
Carla Gentry CSPO's insight:

How old are my customers, did they go to college, do they have children, where do they live, where do they shop, what is their annual income, etc? I bet you can answer most of these questions with your existing data! Have millions of records, that my specialty!

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Top 7 free social media measurement tools from 7 experts |

Top 7 free social media measurement tools from 7 experts | | Data Nerd's Corner | Scoop.it
90% of CMOs say social data has impacted at least some of their decisions; only 47% use data to make predictions or forecast sales. (source: Bazaarvoice)
87% of marketers want to know how to measure their return on investment for social media activities (source: Social Media Examiner)
85% use social networks in some way; only 14% tie financial metrics to it (source: AdAge)
Carla Gentry CSPO's insight:

These facts indicate most companies use social media but don’t measure it. Yet, virtually all agree they would make better business decisions, possibly determine their return of investment, if they did.

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PRESS RELEASE: Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise - Rivo

PRESS RELEASE: Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise - Rivo | Data Nerd's Corner | Scoop.it
Carla Gentry is one of the most respected names in data mining and analytics, named one of Information Week’s 10 IT Leaders to follow on Twitter and Business Insider’s 25th Most Influential Tech Woman of 2014.  Most recently she spoke for the IBM Insight 2014 event in Las Vegas. Behind the scenes Carla is working closely with the Rivo Lab on their Analytics solution helping to provide Advanced Analytical capabilities to Rivo’s customer base by bridging the chasm between technology and business needs.
Carla Gentry CSPO's insight:

LONDON, UK: Rivo, the market leading cloud risk management platform for leading brands around the world has announced the recruitment of three world renowned experts in Data Analytics and Sustainability Reporting to an elite panel of Rivo Thought Leaders. The move by Rivo demonstrates how the global software player is offering value-added content and expertise to its customers

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10 data science predictions for 2015

10 data science predictions for 2015 | Data Nerd's Corner | Scoop.it
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Carla Gentry CSPO's insight:

These predictions were published by the International Institute for Analytics (IIA). They produced a nice infographics, featured below, and re-tweeted many times by various bloggers, using the hash tag#2015Analytics. Other interesting predictions include those by Tableau, those by Pivotal, as well as my own predictions.

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IT Hiring, Budgets In 2015: 7 Telling Stats - InformationWeek

IT Hiring, Budgets In 2015: 7 Telling Stats - InformationWeek | Data Nerd's Corner | Scoop.it
No doubt some of today's technologies -- such as improved automation that allows for lights-out, remotely managed, highly virtualized data centers -- will eliminate some IT jobs. Virtualization continues to let IT organizations spend less time manipulating physical boxes. But as Choice Hotels International CIO Todd Davis told us recently, increased complexity in the data center also has made top-flight infrastructure professionals among the hardest IT pros to find.
Carla Gentry CSPO's insight:

But today's rising IT demand isn't just about project volume -- generating 500 BI reports in the coming year instead of 450 this year. It's about IT doing entirely new things, the kind of creative work that doesn't just lower costs but also helps companies grow. It's about mobile apps that build new customer ties, data analysis that spots new opportunities, technology-powered services that drive new revenue.

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The Internet Of Things' Best-Kept Secret

The Internet Of Things' Best-Kept Secret | Data Nerd's Corner | Scoop.it
So today we have smart products and software is eating the world. But why connect the product to the Internet? “The number one reason,” says Heppelmann, “is to service them better. The number two reason is to operate them better.” But the sum of the changes is greater than the parts, resulting in improved, even new, business models. It’s a business transformation driven by digitization.
Carla Gentry CSPO's insight:

The evolution of PTC’s business is a great case study of how digitization is eating the world. For Heppelmann, taking a company known as “a CAD company, maybe a CAD and PLM company” to the suddenly-hot Internet of Things (IoT) market “is pretty logical.” He takes me on a 30-year journey, starting with the founding of the company by Sam Geisberg: “When you hear about 3D printers, think Sam Geisberg. The 3D technology that’s in use today is almost identical to what he invented—the first line of code he wrote is still running out there every day.”

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Mario Lenz's curator insight, Today, 6:51 AM

Number one reason for #IoT is to service products better.

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2014: A Year in Which Big Data Dominated Every Conversation

2014: A Year in Which Big Data Dominated Every Conversation | Data Nerd's Corner | Scoop.it
One of the primary drivers for hybrid cloud adoption this past year was big data analytics. With so many big data analytics projects underway in all business sectors, the agility, scalability, and elasticity of the cloud was a natural fit.

On-demand Hadoop services, such as Elastic Map Reduce, made it simple and cost effective for organizations to prototype and operationalize big data processing and analysis. Cloud storage solutions like Amazon S3 provided a unique storage platform for data processing and archiving, and offered organizations a viable alternative to growing existing on-premise SAN infrastructure. And one of the true stars of the show was Amazon Redshift. The combination of low cost, no maintenance elasticity and scalability have enticed customers enough to make it the fastest growing service on AWS.
Carla Gentry CSPO's insight:

In 2014, there was a strong move to hybrid cloud solutions and hybrid IT organizations. Migration to the cloud by the enterprise was in full force this year. This migration included “hybrid cloud,” a concept in which businesses used both private and public cloud-based solutions that provide the best of both worlds. This year, we saw hybrid solutions offer the much-needed storage and flexibility of the cloud, as well as the speed and safety of having internal networking where it matters. - See more at: http://data-informed.com/2014-year-big-data-dominated-every-conversation/#sthash.uKWa2es7.ybeTGP5G.dpuf

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More Businesses Are Diving Into Big Data Analytics

More Businesses Are Diving Into Big Data Analytics | Data Nerd's Corner | Scoop.it
Survey analysis points to "the newness of the technology and the skills required for tactical investment" as factors delaying full-scale adoption of big data analytics. The lack of infrastructure investment coincides with increased experimentation and the use of cloud services as businesses probe the idea of analytics for business insights.
Carla Gentry CSPO's insight:

Midsize businesses considering big data analytics are a key audience for cloud services, particularly during the early analytics experimentation phases. As businesses of all sizes explore the possibility of cloud analytics, service providers that are motivated to develop cost-effective solutions may be able to meet this demand. The availability of cloud analytics options and the skills to manage data migration, transformation and integration can tilt midsize businesses toward cloud offerings.

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Data science: 'Machines do analytics. Humans do analysis' | ZDNet

Data science: 'Machines do analytics. Humans do analysis' | ZDNet | Data Nerd's Corner | Scoop.it
Booz Allen has a team of 500 devoted to data science projects and 50 of them are "national treasures," says Sullivan. Those elite 50 data scientists have worked on multiple projects in many industries and have all the traits required for asking the right questions needed to transform business.

"These people are curious and relentless in the face of failure," Sullivan said. "They keep pushing and no matter and they think they can contribute no matter how big the problem is." For instance, a team may fail 340 times before finding the pattern that means something. You can't get disappointed easily.

Via Don Dea
Carla Gentry CSPO's insight:

Sullivan isn't big on analytics technology that serves as a magic bullet to data science. No machine can be a miracle cure. Humans have to find the patterns, ask the right questions and make the connections in the data. "Machines do analytics," explained Sullivan. "Humans do analysis." Computers are good at detail and examining the past, but real data science requires imagination and cognitive ability.

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Don Dea's curator insight, December 10, 1:06 AM

No machine can be a miracle cure. Humans have to find the patterns, ask the right questions and make the connections in the data. "Machines do analytics," explained Sullivan. "Humans do analysis." Computers are good at detail and examining the past, but real data science requires imagination and cognitive ability.

Luca Naso's curator insight, December 11, 11:33 AM

In Data Science "talent" means to be "relentless in the face of failure"

 

Insights (aka Big Data Value) builds on Big Brains:

No machine can be a miracle cure. Humans have to find the patterns, ask the right questions and make the connections in the data.

Fàtima Galan's curator insight, Today, 3:48 AM

"Data science is a team sport and you need a diverse team to explore multiple angles."

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Disney Research builds computer models to analyze play in pro basketball and soccer

Disney Research builds computer models to analyze play in pro basketball and soccer | Data Nerd's Corner | Scoop.it
In a new study, researchers at Disney Research Pittsburgh showed they could use player tracking data from more than 600 basketball games of the 2012-13 NBA season to build models that can make accurate in-game predictions of what each player is likely to do next in a game situation: pass or shoot.
Carla Gentry CSPO's insight:

In a separate study using a season's worth of ball and player tracking data from a professional soccer league - more than 400 million data points - Disney Research Pittsburgh researchers performed a different type of analysis that looked at team behavior rather than individual players. They showed their system could accurately detect and visualize team formations - well enough that they could identify teams based just on their style of play 70 percent of the time.

Read more at: http://phys.org/news/2014-12-disney-pro-basketball-soccer.html#jCp

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5 Prescriptions For A Healthy Customer Data Plan

5 Prescriptions For A Healthy Customer Data Plan | Data Nerd's Corner | Scoop.it
Marketing data, and the productive management of it, continues to be a challenge for all B2B marketers. According to the NetProspex 2014 State of Marketing Data Benchmark Report, more than 25% of the average B2B database is simply inaccurate. And two-thirds of companies surveyed had an overall data-health scale of “unreliable.”
Carla Gentry CSPO's insight:

But that database is an important key to capturing the attention of your customers and prospects. A white paper title, “Demand Generation Strategies,” may not be nearly as compelling a title as “Tech Marketing Strategies for a Start-up Budget.” But without understanding the audience that’s actually seeing that content, you’ll never know. The ability to be specific in your content promotion across channels where attention span is limited often depends on how complete and accurate the associated fields in your database are. They can make all the difference in the effectiveness of the pieces you write. Combine that contact knowledge with buyer persona insights, and online behavior, and all of a sudden the content you’re creating is not only strategic, but actually drives conversions, engagement, and ultimately, revenue for your business.

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Is Big Data Already Tracking Your Kindergartner? - Credit.com

Is Big Data Already Tracking Your Kindergartner? - Credit.com | Data Nerd's Corner | Scoop.it
Technology is often held up as a silver bullet to solve big social problems. It’s not just education. Remember all the money spent (and wasted) on facial recognition software for airports in the wake of 9/11? Tech is often set up to fail by expectations that are too high and an underlying agenda that has more to do with cost savings than investment. Last month, CNN aired a documentary named “Ivory Tower” that explored the issue of rising college costs and reduced government aid. It devoted an entire segment to an experiment at San Jose State University, which had contracted with a private firm to replace in-class courses with online offerings to save money. The school quickly suspended the experiment after dismal pass rates.
Carla Gentry CSPO's insight:

“It is really tough. On one hand, the tools …whether hardware like smartboards or infrastructure such as broadband connections… can provide tremendous vehicles for improving and augmenting instruction, especially in Title I schools or rural schools or other such with heavy challenges. The caveat is that [tech solutions] should be approached with a mind towards best practices and proper return on investment. Simply increasing budgetary spends do not improve education.”

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Running an Email A/B Test? How to Determine Your Sample Size & Testing Time Frame

Running an Email A/B Test? How to Determine Your Sample Size & Testing Time Frame | Data Nerd's Corner | Scoop.it
In theory, to determine a winner between Variation A and Variation B, you need to wait until you have enough results to see if there is a statistically significant difference between the two. Depending on your company, sample size, and how you execute the A/B test, getting statistically significant results could happen in hours or days or weeks -- and you've just got to stick it out until you get those results. In theory, you should not restrict the time in which you're gathering results.

For many A/B tests, waiting is no problem. Testing headline copy on a landing page? It's cool to wait a month for results. Same goes with blog CTA creative -- you'd be going for the long-term lead gen play, anyway. 

But on email, waiting can be a problem -- for several practical reasons:
Carla Gentry CSPO's insight:

Unlike a landing page (where you can continue to gather new audience members over time), once you send an email A/B test off, that's it -- you can't "add" more people to that A/B test. So you've got to figure out how squeeze the most juice out of your emails. This will usually require you to send an A/B test to the smallest portion of your list needed to get statistically significant results, pick a winner, and then send the winning variation on to the rest of the list. 

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What Are the Clinical Analytics Lessons from EHR Adoption Data?

What Are the Clinical Analytics Lessons from EHR Adoption Data? | Data Nerd's Corner | Scoop.it
For clinical analytics advocates, both the pros and cons of health IT adoption seem very familiar.  The financial incentives and penalties related to data analytics adoption are much less codified and clear than the regulations of the EHR Incentive Programs, but there certainly are monetary benefits and quality penalties associated with the ability to stratify risk, predict high cost patients, and provide effective preventative care and chronic disease management.  They are largely driven by cost-conscious payers at the moment, but as the stages of meaningful use advance to encompass more of these population health features, CMS and the ONC will be keeping a sharper eye on metrics that require more advanced health IT capabilities.
Carla Gentry CSPO's insight:

Could clinical analytics benefit from its own separate incentive program that rewards population health management and penalizes poor outcomes?  Or will the EHR Incentive Programs provide enough structure and motivation in its latter states to prompt sufficient growth?  With Stage 2 in full swing and the proliferation of analytics frameworks and adoption models provided by HIMSS and other organizations, the industry is starting to lay the groundwork towards robust analytics in a variety of ways.  As providers accomplish analytics goals, they may wish to look back to the pitfalls and successes of the early parts of the EHR Incentive Programs to provide clues to motivating healthcare organizations to move forward towards true accountable care.

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Facebook Graph Search Now Lets You Find Old Posts: Here's What You Need to Know

Facebook Graph Search Now Lets You Find Old Posts: Here's What You Need to Know | Data Nerd's Corner | Scoop.it
Turns out I wasn't the only one who was disappointed. People wanted to be able to easily find old posts they saw in their News Feed -- Graph Search could only return queries like "Friends in [LOCATION] who go to [SCHOOL]." People wanted to be free to search for something wherever and whenever they wanted -- not having to wait until they got back to their desktop. 

Well, for us disappointed folks, yesterday was our lucky day. Facebook's answered our two biggest gripes:

You can now use keywords to search for old News Feed posts (not just people, Pages, Groups, events, and apps).
You can now use Graph Search on mobile. 
That's pretttty exciting for most Facebook users ... but it's even more exciting for marketers, especially those who've felt burned by Facebook's recent organic reach changes. 
Carla Gentry CSPO's insight:
The Facts

Here are the basics on Facebook's Graph Search update.

 
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