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5 Best Tools Transforming Predictive Analytics in 2018

5 Best Tools Transforming Predictive Analytics in 2018

Gone are the days of sloppy decision-making techniques. Competitive businesses are embracing predictive analytics and associated tools.

Predictive analytics is a real game changer that allows companies to implement marketing strategies and serve customers with renewed efficiency. Customers in their natural interactions and networking with a company leave behind huge amounts of data. Predictive models extract valuable information from all this data, thereby helping enhance the performance of products and services, promoting better customer retention strategies, and improving core business competencies.

‘’The capacity for predictive analytics to learn from experience is what renders this technology effective, differentiating it from other business intelligence tools and analytics techniques’’, says the predictive analytics experts at Quantzig.

From thoroughly examining data, to figuring out correlations and patterns in data, predictive analytics tools effectively manage the entire business process. In this blog, we talk about some of the latest predictive analytics tools that are all the rage in 2018! So let’s dive in!

SAP Business Objects:

  • A powerful Business Intelligence platform that provides techniques to make swift and informed business decisions.
  • Offers a novel perspective on forming scalable solutions
  • SAP Business Object helps develop insights that encourage real time actions.
  • Enables users to visualize data in a self-serving manner

Image Source: Technosap

IBM Predictive Analytics:

  • Offers predictive analytics solutions that are simple to use and meet the requirements of different types of businesses.
  • Two important softwares, namely IBM SPSS Modeler and IBM SPSS Analytics, allow all users to implement predictive analytics and improve their businesses, irrespective of their skill levels.
  • The platform helps prevent frauds and maximizes profits.
  • It transforms extraneous data into predictive insights that steer key business decisions.
  • It is built with abilities to perform geospatial analysis and text analytics.
  • Runs on open source platforms with optional coding
  • Secure and private

Image Source: SlideShare

QlikView:

  • Flexible and easy-to-use business intelligence platform
  • Created by QlikTech
  • Allows enterprises to pull out relevant information from a given data set, which in turn helps design guided analytics applications.
  • Platform adopts a user-driven approach towards building charts and creating dashboards
  • BARC’ BI Survey 10 recognizes the ‘Agile BI’ ability of QlikView

Halo:

  • Ideal pick for an uninterrupted supply chain management system that aids in business forecasting
  • A smart platform with a dependable data repository, where cases can be run over and over again in order to perfectly match predictions with results.
  • Accessible through all kinds of browsers and available for cloud or hosted.
  • Self-serving nature of supply chain management allow organizations to increase customer satisfaction.

Image Source: Software Advice

Dataiku-DSS:

  • Dataiku is capable of transforming raw data into predictions.
  • Allows users to employ analytics appropriate algorithms
  • Allows users to leverage available libraries and apply custom codes in R and Python
  • Permits integration of external libraries by means of code API’s
  • Equipped with 80+ in-built functions that help investigate and clean raw forms of data
  • The best feature is a visual data profile at each step of analysis.

Image source: The Dataiku Blog

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5 On-Going Predictive Analytics Applications That Marketers Should Be Familiar With

5 On-Going Predictive Analytics Applications That Marketers Should Be Familiar With

Predictive Analytics is a very popular concept, and increasingly often, the marketing strategies are tied to the very idea of predictive analytics. However, businesses seeking insights about the future aren’t satisfied with whatever happened in the past. They want to know more, and that’s where the promising role of predictive analytics comes forth.

In this article, we will talk about some modern applications of predictive analytics that are deriving great results in the marketing sphere:

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Five On-Going Predictive Analytics Marketing Applications

Customer behavior models

Once only bigwig companies, like Amazon and eBay had the ability to do customer behavior prediction, but with increasing expansion of technology, even smaller companies have adopted the practice. Developing a comprehensive catalogue of predictive models is for sure a challenging task, but fortunately a number of relatively easier model types are plying assistance in the marketing scope. Amongst them, three most significant predictive models are Cluster Models, Propensity Models and Collaborative Filtering.

Assessing and prioritizing leads

With 3 B2B marketing use cases, here’s how we can predict early success and prepare the base for more complex use of predictive analytics:

  • Predictive Scoring – Prioritizing known leads, prospects, and accounts based on how they are probable to act upon.
  • Identification Models – Determining and acquiring prospects with characteristics akin to existing consumers.
  • Automated Segmentation – It’s crucial to segmenting leads for customized messaging.

The above-said groundwork helps prepare sales team to better apply the strategies and prioritize leads that can be converted into buyers. But of course, the techniques mentioned above need a high sales volume to perfectly prepare a robust predictive model.

Assessing which products or services to introduce into the market

Data visualization is crucial. It is not only visually effective, but is also ideal in guiding actions, based on customer behavior. It notifies which type of customers lives near a particular store, what is their average age-density and what kind of products they buy: do they purchase hard or soft goods, who goes for grocery shopping, the aged ones or the younger ones, and so on.

Content is the king

Targeting the right customers with the right content at the right moment boosts customer segmentation. It’s one of the most common predictive analytics marketing tricks because it’s simple, effective and directly impacts ROI. Some of the most popular predictive analytic models for content targeting are response modeling, affinity analysis and churn analysis – all of them can foretell you whether it would be fruitful to combine digital and print subscriptions or keep them separate or help you differentiate between a content that should levy a subscription fee from a content that has a one-time sales price.

Enhancing marketing strategies with predictive analytics

 Apart from the above 4 uses, few other drilled-down uses of predictive analytics in the marketing domain are as follows:

  • Gaining access to internal structured data
  • Accessing social media data
  • Employing behavior scoring on customer data

These applications could ascertain whether a social media- based marketing campaign would meet a raging success or a mobile marketing strategy would be more beneficial for the target audience.

For readers interested in making predictive analytics your career option, opt for SAS certification for predictive modeling from DexLab Analytics. At present, SAS predictive modeling training is the go-to course program you need to give wings to your analytics career.

 

The article has been sourced from   https://www.techemergence.com/predictive-analytics-for-marketing-whats-possible-and-how-it-works

 

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6 Predictive Analytics Use Cases Proven To Ace Marketing Efforts

6 Predictive Analytics Use Cases Proven To Ace Marketing Efforts

Predictive analytics includes a set of functions that leverage customer information to construct interesting assumptions about future potential customers. They play an integral role in determining a customer’s lifecycle.

What’s more, predictive analytics influences company strategy even before any prospect gets converted into a lead. That’s the way it functions, and as the leads are converted into customers, the new data collected impacts the next-generation marketing activities. The process is almost cyclical.

In this post, we will discuss about 6 use cases for predictive analytics that shows a significant impact on marketing ROI.

And here it starts:

Better Lead Scoring

With predictive analytics, lead scoring becomes a whole data-driven process that targets customers. It helps you leverage the actions of existing customers to build better future strategies. No more it remains an anecdotic listicle of measures from sales, instead it points out the ‘hot’ leads that can be pushed down through the funnel of sales.

Improved Lead Nurturing

Remember, one-size-fits-all doesn’t apply to lead nurturing.

For converting prospects into leads, a definitive plan for lead nurturing should be adopted. Predictive analytics is the hands-down tool to consider: take cue from behavioral and demographic data to push leads towards the sales funnel.

Smart Content Distribution

Today, every company invests in quality content creation. Content marketing has the power to fetch measurable ROI for your company. And this is where predictive analytics play a vital role: it analyses the type of content customers would find interesting, based on certain behavioral and demographic data and then automatically distribute them to the prospective leads.

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Protecting Baseline Becomes Easy

Predictive analytics help learn from the past mistakes. Past behavior is a testimony of future behavior, and it holds true for customers, as well. A clear analysis of behavioral patterns of previously-churned customers in your company would help identify the red flags your present customers are showing, thus results in protecting your baseline for a better, secure future.

Develop Products Fit For Customers

Understanding what customers need becomes a tad too easier when you are armed with a set of behavioral, demographic and psychological data of your customers. Again possible with predictive analytics! Leverage customer data and figure out what they are looking for.

Design Successful Future Campaign

Past performance analysis always leads to constructing better future campaign designs. As more and more new customers seem to enter your business, you need to leverage your data more precisely and curate content based on their preferences and requirements. And may even have to target specific audiences! So, treat past data as a treasure!

As parting thoughts, these six strategies for predictive modeling are perfect for transforming your business. Today, data is the power. Clean, high-quality data have the potential to take your business venture to unforeseeable heights of success.

And for that and more, DexLab Analytics is here to help. Our skilled consultants can crack the toughest data management problems and provide solutions to make predictive modeling using SAS better. For SAS predictive modeling training, peruse over our course section on the website.

 
The article has been sourced from – https://blog.reachforce.com/blog/8-use-cases-for-predictive-analytics-in-marketing
 

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SAS Conducts India’s Largest Analytics Forum in Mumbai

SAS Conducts India’s Largest Analytics Forum in Mumbai

This May, India is making preparations to host the largest analytics forum in association with SAS – the top notch player in the world of business analytics. The conference on machine learning, AI, IoT, fraud management and customer experience hosted by SAS Forum India is going to be held on Tuesday, 15th May 2018 at Renaissance Mumbai Convention Centre Hotel, Mumbai.

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In its eight year, SAS Forum India is a highly acclaimed knowledge sharing platform wherein business consultants, users and industry honchos come together and meet every year to share crucial knowledge and experience in regards to Analytics. It offers incredible learning and networking experience, while focusing on the imposing role of Analytics across versatile industry domains.

Data is like a new currency impacting the world around – it’s being used right from dealing with humanitarian issues to solving intricate business challenges. In this scenario, the scope of data scientists becomes limitless. They are ushered into countless opportunities to establish connection with their customers, along with developing new profound experiences in the technology world.

Rightfully so, this year’s Forum is going to talk about the latest trends in machine learning, cognitive computing, artificial intelligence, Internet of Things, fraud intelligence, risk management, IFRS9 compliance and customer experience. Industry stalwarts and thought leaders hailing from various business verticals are expected to exchange nuanced notions about each concept to set off breakthrough outcomes and bang open doors of new possibilities.

However, this year the theme is Inspire the Extraordinary, and some of the influential speakers are noted below:

  • Mrutyunjay Mahapatra – Deputy Managing Director, State Bank of India
  • Daniel Zeo Jimenez – Regional Research Director, IDC Asia/Pacific
  • Rahul Shandilya, SVP and CIO – Customer Experience and Product Development, Mahindra & Mahindra
  • Goutam Datta – Vice President – Technology – ICICI Lombard
  • Mridul Sharma, CIO, IndusInd Bank
  • Sudip Banerjee, CTO, Reliance Capital and many more

The summit is also going to screen live demos of diverse analytics SAS solutions, including SAS Viya, the open, next-gen and cloud-ready solutions that help tackle analytics challenges, right from experimental to mission-critical.

Commenting on the occasion, Noshin Kagalwalla, Managing Director, SAS Institute India Pvt. Ltd  was found saying, “New age machine Learning & Deep Learning techniques that form the fulcrum of AI are now opening a whole new world of possibilities for businesses. At the SAS India Forum this year, we are delighted to be joined by some of the best and brightest leaders in analytics who will enlighten you on how to leverage these emerging technologies to succeed in the Analytics Economy.”

Now, as you are reading this blog we are sure you are interested in SAS certification courses. DexLab Analytics offers best SAS analytics training Delhi for aspiring candidates at decent prices. Check out the course details now!

The blog has been sourced from – http://www.dqindia.com/sas-host-indias-largest-analytics-forum-may-15-2018-mumbai

 

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The Soaring Importance of SAS in Creating jobs Across Various Industry Domains

In a survey held in 2016, 54 million employees across 350 industries picked out SAS as the most valuable skill to possess. SAS skills still top the list. With predictive analytics gaining speed and accuracy in the world, one just cannot ignore SAS – the oldest and brightest data analytics tool. Though SAS-dominating days are gone, as R and Python has come up ruling the world , 41% of talented data science professionals still prefer SAS as compared to any other languages. The data science market is conquered by R and Python to a great extent, yet you will find a substantial number of clients still putting their bet on SAS predictive modeling.

SAS-Certification-India

To test how SAS certification is taking the job world by storm, open your web-browser and type ‘SAS jobs’ in the search panel – the following results in front of your eyes will give you all your answers. In fact, you’ll be more than surprised to see how many jobs springs up that calls for SAS expertise. A lot of clients and data houses seek SAS certified professionals to take care of the data-induced challenges and the numbers are quite overwhelming!

 

In total, SAS has around 85000 clients across the globe – owing to which, the demand for SAS should come as no surprise to you.

Benefits of SAS:

  • High Salary
  • Increasing Global Demand
  • Marketability
  • Role-focused
  • Validation of Skills

 

Besides the benefits enumerated above, SAS certification sizzles with myriad other perks related to data and analytics, and is regarded to be extremely useful in bagging entry-level jobs in data science and analytics. A diligent SAS expert explores the broadening field of SAS ANALYTICS, while streamlining his individual skill and expertise to add credibility to his job profile.

 

Want to get an instant pay hike? SAS skills may come to your rescue. Once you hone your SAS analytics skill, you can start expecting 6% to 10% pay hike, which further expands, if you add data mining and data modeling skills to in your resume, likewise.

 

Financial analytics and SAS

To improve the performance of business and act upon the loopholes present in an organization, financial analysts backed by advanced SAS analytics skills pore over a vast amount of company’s financial data. They help you answer all the business related questions and predict the future of your organization.

Healthcare and SAS

As healthcare pushes boundaries to ace the digital transition, Statistical Analysis Systems (SAS) is bringing all kinds of latest technical updates and modifications across a wide spectrum of care, right from the way healthcare providers perform tests to measuring patient safety and health outcomes. It is playing a pivotal role in tapping a lot of disease states and assessing ways to commercialize treatments.

 

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Who specializes in SAS and why?

SAS skill is for experienced professionals. Old timers are its biggest fan, especially those who have more than 15 years of job experience. For them, nothing suits better than this miracle tool for data analysis.

However, the tides of time is changing, the current pool of students is somewhat showing keen interest in this field of study for quite some time now. But it takes a real effort of time and practice both to excel in this highly advanced software.

 

Drop by DexLab Analytics to avail SAS online training. The course here is designed and delivered by industry experts with crisp content and student-friendly learning techniques. Visit their website today!

 

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Why B2B Marketers Should Use Predictive Analytics in 2018?

The Risks are indispensable. In any business.

But what if you can nullify the risks?

Or find a suitable solution to limit them?

Why B2B Marketers Should Use Predictive Analytics in 2018?

That’s probably where Predictive Analytics ring the bell. Right from logistics and inventory to marketing initiatives and sales to applications in hiring and HR, predictive analytics is the ultimate tool that impacts business decisions across every domain of a B2B enterprise.

Continue reading “Why B2B Marketers Should Use Predictive Analytics in 2018?”

Researchers Peer into the Hood of Computational Linguistics

Researchers Peer into the Hood of Computational Linguistics

 

To start, give a look at these two sentences:

“This house is in a detestable location.”

“This detestable house is in this location.”

 

Well, these two sentences have virtually similar words, but owing to their structure, they exude entirely two different meanings. Understanding the true meaning of the sentences just by having a look at the words was something only reserved for the human intelligence, until now. Breakthroughs in Natural Language Processing (NLP), also known as computational linguistics have blazed a trail in this domain, which was once dominated by humans.

Continue reading “Researchers Peer into the Hood of Computational Linguistics”

Interactive Data Discovery and Predictive Analytics: Extract Useful Knowledge from Data

Impressive predictive analytics coupled with interactive data discovery technology enable rational SAS analysts to distinguish pertinent trends and interactions in datasets, and pan out questions from all dimensions. This smashing concoction of technologies also allows business users to exchange ideas with pundits, to create, modify and pick the best predictive models, constructively.

 

Interactive-Data-Discovery-and-Predictive-Analytics-Extract-Useful-Knowledge-from-Data

 

A comprehensive SAS solution might be the key to empower users in taking better business decisions, without wasting much time. This kind of interactive solution must involve ceaseless communication, giving enough room to even non-technical users to explore data visually, develop analytic models, and share fruitful results.

Continue reading “Interactive Data Discovery and Predictive Analytics: Extract Useful Knowledge from Data”

INTCK and INTNX: All about SAS Dates and Computing Intervals between Dates

INTCK-and-INTNX

The INTCK and INTNX functions in SAS helps you compute the time between events. This technical blog is based on the timeline of living US presidents, sourced from a Wikipedia table. The table data shows the number of years and days between events.

So, let’s start.

LivingPresidents2

Gaps between dates

To calculate the interval between two dates, you can use these two SAS functions:

The INTCK function returns the number of time units between dates. The time unit can be selected in years, months, weeks, days, or whatever you feel like.

The INTNX function helps you compute the date that is 308 days away in the future from a specific date. This was just an example to help you understand what it means. The INTNX function returns a SAS date that is particular number of time units away from a particular date.

These two functions share a complimentary bond: where one calculates the difference between two dates, the other entitles you to add time units to a specified date value. Also, the INT part in both the functions denotes INTervals, and the terms INTCK and INTNX means Interval Check and Interval Next, respectively.

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How to calculate anniversary dates

These two prime functions tend to be useful in counting the number of anniversaries between two dates along with calculating a future anniversary date. Use the ‘CONTINUOUS’ option for the INTCK function and the ‘SAME’ option for the INTNX function in the following manner:

The ‘CONTINUOUS’ option in the INTCK function helps you count the number of anniversaries of one date that occur before a second date. For example, the statement

Years = intck('year', '30APR1789'd, '04MAR1797'd, 'continuous');

returns the value 7 because there are 7 full years (anniversaries of 30APR) between those two dates. Without the ‘CONTINUOUS’ option, the function returns 8 as 01JAN occurs 8 times between those dates.

The statement

Anniv = intnx('year', '30APR1789'd, 7, 'same');

returns the 7th anniversary of the date 30APR1789. In some ways, it returns the date value for 30APR1796.

The most exciting part about these two functions is that they automatically handle leap years! Yes, you read that right. If you ask for the number of days within two dates, the INTCK function will show leap days in the result. If an event takes place on a leap day, and you ask the INTNX function to reveal the anniversary date, it will report 28FEB of the next year to the next anniversary date.

An algorithm calculating years and days between events

Go through the following algorithm to calculate the number of years and days between dates in SAS:

  • Use the INTCK function with the ‘CONTINUOUS’ option to calculate the number of completed years between two dates
  • Use the INTNX function to discover a third date, i.e. anniversary date, which is the same month and day like the start date, but takes place less than a year before the end date.
  • Use the INTCK function to ascertain the number of days occurring between the anniversary date and the end date.

Here are the data steps that enable you to compute the time interval in years and days between the first few US presidential inaugurations and deaths.

data YearDays;
format Date prevDate anniv Date9.;
input @1  Date anydtdte12.
      @13 Event $26.;
prevDate = lag(Date);
if _N_=1 then do;                               /* when _N_=1, lag(Date)=. */
   Years=.; Days=.; return;            /* set years & days, go to next obs */
end;
Years = intck('year', prevDate, Date, 'continuous'); /* num complete years */
Anniv = intnx('year', prevDate, Years, 'same');      /* most recent anniv  */
Days = intck('day', anniv, Date);                    /* days since anniv   */
datalines;
Apr 30, 1789 Washington Inaug
Mar 4, 1797  J Adams Inaug
Dec 14, 1799 Washington Death
Mar 4, 1801  Jefferson Inaug
Mar 4, 1809  Madison Inaug
Mar 4, 1817  Monroe Inaug
Mar 4, 1825  JQ Adams Inaug
Jul 4, 1826  Jefferson Death
Jul 4, 1826  J Adams Death
run;
 
proc print data=YearDays;
var Event prevDate Date Anniv Years Days;
run;

 

LivingPresidents3

 

In a nutshell, the INTCK and INTNX functions are consequential for calculating intervals between dates. In this blog, I discussed about two-less-popular options inn SAS, for more such SAS training related blogs, follow us at DexLab Analytics.

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This post originally appeared onblogs.sas.com/content/iml/2017/05/15/intck-intnx-intervals-sas.html
 

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