Tag Archive : Advanced Analytics

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Sentiment Analysis

In a competitive era, when every industry is trying to reach the pinnacle of success, the healthcare industry too is picking up the pace with enhanced and exceptional Patient Experience

Be it the hospitals, nursing homes, physician practices or healthcare systems, all are laying special emphasis on Patient Satisfaction. Period.

Only healthcare facilities equipped with improved functionality and better convenience, providing whatever modern consumers look forward to, are emerging as the true leaders in the healthcare domain. 

Since patients these days are far more particular than before and have ample options to choose from, it is imperative for healthcare services to be proactive in roping in and hanging on to patients.

And Sentiment Analysis is one of the best ways to do it. 

To start of with Sentiment Analysis

Have you ever wondered what the feedback of your patients is once they leave your medical facility? 

Enters, SPIN NuInsights Model, with its Sentiment Analysis Application that can gather authentic patient feedback and transform them into reports and intuitive charts to help you draw a conclusion where the medical services are lacking or pleasing.

In tune with it, examining trends for different human emotions like sadness, anger, joy, disappointment, etc. by NuInsights Sentiment Analysis Model enlightens a healthcare provider about the present status of patient care services and the areas of improvement.

To cut the long story short, we want to endow healthcare providers with the tool and cutting-edge analytics (known as Sentiment Analysis application) that can nourish and boost their relationship with patients.

So what is Patient Sentiment Analysis?

Simply put, the process of evaluating and analyzing feedback from the patient’s experience (typically based on emotions at the time) is termed as Sentiment Analysis.

Unraveling of opinions, emotions, and reactions of patients based on the practice they just experienced is one of the biggest Sentiment Analysis benefits.

Add to it, such a form of analysis empowers healthcare caregivers with a competitive edge, revamping their service based on the feedback shared.

Furthermore, SPIN’s Sentiment Analysis Application can also be used to observe the texts or comments by patients and their overall experience in the facility, shared on Twitter, Facebook,LinkedIn and other popular online platforms.

The Significance of Patient Sentiment Analysis for Healthcare firms

It enables caregivers to evaluate the genuine notion of patients for them, figure out the gaps in patient experience, and employ corrective measures on time.

Here are a few pointers to support the above statement:

1. Accumulating data on patient experience

Patient satisfaction is the key for healthcare organizations to prosper and Nu Insights’ Sentiment Analysis Application excels in it. 

It analyzes the data accumulated from multiple common complaints or compliments, segment the data based on doctors and other parameters to spot the opportunities for patient care improvement.

2  Measuring performance 

Such analysis takes into consideration the emotions of patients to derive a conclusion about the performance of a medical facility. 

Such analysis classifies patient comments into various categories like places, processes, people, etc., and then gives them scores to uncover what patients actually feel about the facility services.

For instance, Nu Insights Sentiment Analysis model analyses the frequency of words used by the patients and selects only the most used words left in the comments. 

Here are a few examples:

  • We waited in the queue for a long time (Negative feedback)
  • Good staff and less waiting time (Positive)
  • Nice services but certain aspects need to improve(Neutral)

Based on the above such comments from patients, the Nu Insights Model determines whether the healthcare practice has any scope for improvement or it is going downhill.

Benefits

  • Insights into the performance of a healthcare facility are one of the biggest benefits of Sentiment Analysis. The evaluation of collected data gives a clear picture of what patients actually expect from your practice, how are your employees seen, and other aspects of the management.
  • Generating authentic and quantifiable data regarding the staff about their performance motivates employees to do better in the future. In case of negative comments, the gaps can be fulfilled by the staff. The bottom line is, as long as employees are motivated and get proper feedback for their hard work, patient care is bound to improve.

How Nu Insights Uses ML for Sentiment Analysis

Nu Insights’ Sentiment Analysis model can give you a clear idea of what patients are thinking about your practice by gathering feedback from various locations and using ML to analyze and use the data to make charts and reports.

Here is an example, how our Nu Insights’ Sentiment Analysis model applies to healthcare business scenarios.

A leading hospital chain in the US witnessed declining patient satisfaction to a significant level and wanted to incorporate the latest ML and Analytics trends to comprehend what opinions patients had about the facility. 

In this regard, effectively using Advanced Analytics to understand the root cause of the issue and creating a mechanism to track the same in a bid to timely correct customer satisfaction was the primary approach of SPIN.

 Scenario

With multiple facilities operating under the hospital chain, proper tracking and standardization of its operation became quite challenging and difficult. With an alarming fall of patient satisfaction leading to higher attrition, management decided to get to the bottom of the issue and address it.

Challenges

  • Removing unstructured data from different platforms
  • Same comments on different platforms
  • Determining fake reviews

Solution

Patient comments and reviews shared across different platforms like social media, review forms, blogs hospital websites were accumulated and were filtered for clarity, authenticity, and relevance. Then these comments were subjected to NLP for further filtration.

Results

The gaps that required quick attention were spotted and quick changes were applied in the operations, leading to enhanced customer satisfaction. Not only best practices for business were determined and standardized, the weekly tracking of the facility operations was also streamlined.

To improve healthcare, Sentiment Analysis is needed

Patient satisfaction takes the front seat when it comes to measuring the achievement of your healthcare practice and is always the primary focal point of any marketing campaign.

For marketing campaigns to prosper and reap necessary results, physicians, health centers and healthcare facilities can use Sentiment Analysis to take their clinical services to the next level, by analyzing the exact expectation of patients.

At SPIN, our healthcare marketing strategies are integrated with programs that boost patient experience significantly.

After all, it is a satisfied patient eventually lead to an increase in revenue.

Artificial Intelligence - Leading the way towards global development

Humans have already been taken a huge leap towards an advanced future while copying human intelligence and marking it up with machines. 

Artificial Intelligence and Machine Learning bring great potential to change several situations that the world is facing today. 

While the technology has embarked it’s impact outcomes to both general use and industrial use, Artificial Intelligence’s is a much-trusted solution to fight against terrorism globally.

Innovation has always helped humankind take a step ahead in the future and transfer knowledge into applications. 

Machine automation along with a replica of the human intelligence to understand, learn and react has revolutionized industrial operations and a lot more. We very well know the fact that data is the fuel that drives most of the daily operations over the internet and into our daily lives. With more data, machines now can learn and adapt to its users.

In a recent conference at Minsk, organized by the United Nations Office of Counter-Terrorism (UNOCT) and Belarus, Artificial Intelligence was considered to be a cutting-edge solution for dealing with global terrorism. Vladimir Voronezh, Under-Secretary-General for the UN Counter-Terrorism Office, declared that the international community is utilizing artificial intelligence and machine learning capabilities to track down criminal and terrorism data globally.

The recent trends in Artificial Intelligence find its way to different sectors but mostly are leveraged by the government and law enforcement bodies to deal with national threats. This is itself a great leap for the technology. Here is a list of four latest trends that are today widely accepted by business owners, the government, security agencies, etc.

  1. People Analytics: Pouring on the fuel of data, artificial intelligence can do miraculous things. Through AI, business and organizations can harness the data of people enrolled with them for any targeted campaign.
  2. Algorithmic Website Personalization: Ever noticed how YouTube personalizes its home page as based on what you like or prefer to watch? This is all AI and machine learning. 
  3. Automated Customer Service: Retrieving customer data can help businesses provide the most relevant marketing campaigns, product display and a lot more. AI will help in customizing the customer experience. 
  4. Automated Resource Management: AI learns how to organize and allocate their subjects.

Given the present scenario, it is imperative to boost the exchange of expert knowledge on technologies such as Synthetic Biology, 3D Printing, Robotics, the synthesis of the human face

Nanotechnology, etc. to identify risks before-hand and respond in a jiffy.

At SPIN Strategy, we have experts of Robotics Process Automation, AI, and Machine Learning who can not only guide you in these complicated routes of business but also aid you in meeting your quest.

How can Inferential Analytics help business with target customers?

 

Say, you wish to know the average salary of a data scientist professional of a particular region. What are the possible options you can think of?

  1. You personally meet with every data scientist of that region and make a note of his or her salary.
  2. You hand pick few professionals of that region and calculate the average salary.

Although the first method is not impossible, it is a Herculean task indeed, which will consume a lot of resource and time. And keeping in mind the swift moves of companies these days, easy and quick solution is not just preferred but a priority too.

So, what method should be used to figure out the average salary of the data scientist of that area? 

The answer is Inferential Statistics.

For starters, and to put it simply for all, Inferential Analytics is typically designed to draw assumptions beyond the present data available. 

How it works-By taking a random sample of data from a particular set of population and making assumptions and inferences about the people.

But how can this demographic analysis help a business meet its sales targets? Read on to know more.

How to grow business with Inferential Statistics?

With time, the marketplace shifts and evolves, and so does the list of your clients. 

So, it’s time to get ahead of the curve and get a step ahead in the competition-it is time to take the help of demographic data, and what better serves the purpose than ‘Inferential Analytics’. 

Here are three tips on how you can boost the revenue of your organization by making the most of Inferential Statistics.

  1. Development Plans– Often business leaders plan to expand their company or open a branch at a new location, but how to derive information about the customer base, delivery system, distribution scheduling etc. ? 

With Inferential Analytics, you can get key insights on such aspects, coupled with business intelligence reports. Such information is extremely crucial for expansion plans, especially at a new location.

  1. Locate your audience– With the help of Inferential Analytics that examines your current customer data, it is possible to find out where people are most likely going to take benefit out of your product or service. Add to it, you can also narrow down the region where the possibility of customer potential and expansion is high.
  2. Create a marketing campaign– With the help of Inferential Analytics, a business leader can narrow down the branding requirements and focus on specific consumer preferences in a bid to stand out of other competitors in the region. Together with such data, it becomes easy to create a successful marketing campaign.

Grow your business with Inferential Analytics

Expansion of business is nothing less than a big challenge. Not only it takes time and dedication, but also careful location planning. Only with proper location segmentation that helps categorize targeted customers can a business reach its heights.

When the importance of location and population is so impeccable, Inferential Analytics importance cannot be ignored.

If you are blown away by the relevance of Inferential Analytics on business and wish to incorporate it into your company, team members of SPIN Strategy can be of great help.

 

It is an inevitable fact and goes without saying that on account of the very nature of data, technology, and analytics that is always at odds for different enterprises, optimal Big Data Deployment strategy may sing a different tune for other business. Period!

This fact-based truth opens the door for strategies, customized only for particular organizations with the pre-conceived motive to deploy Big Data technologies minus any kind of fall out or interruption.

Sounds soothing to the ears?

Note: Before kicking off with the ‘deployment’ process, it comes as a de rigueur step to conduct a detailed evaluation of integration, governance, security, processes, and interoperability, in a bid to reap the pleasure of a seamless Big Data implementation.

Let’s dig deep and get to the pulse of new age Big Data architecture and its deployments know-how for a better understanding.

Age of Big Data Technology

Thanks to our good fortune, we live and breathe in an era of Big Data Analytics, where business enterprises go that extra mile to find ways to harness volumes of unstructured data efficiently.

Business organizations these days take the helping hand from analytics to convert data into valuable insights to pave the way for enhanced operations and informed business decisions.

Riding on the back of intelligent algorithms, organizations give birth to smart data, which can evaluate patterns and signals to help business leaders make informed decisions and thereby cut down costs to perk up profit margins.

However, such an objective is not a walk in the park and requires the assistance of requisite technology within Big Data Environments.

Taking the plunge in the absence of required knowledge and an infallible Big Data strategy is bound to witness a dead-end.

Imperfect deployment road-maps and wrong decisions which can drain out the resources and budget and adversely impact the business performance further gives clarity on the gravity of the situation.

So it is important to understand the Big Data Deployment framework for effective execution.

Big Data Deployment Framework

Out of the lot, there are certain primary factors that manipulate the mammoth decision of employing Big Data technology in a business enterprise.

Such factors include:

• The existence of traditional/non-traditional data in the system
• Presence of low latency data
• Delving into new analytics algorithms
• The requirement for real-time insights

Pillars of Big Data architecture- Analytics, Data, and Technology

Data
There can be no objection to the fact that ‘Data’ is the very heart of technology, analytics, and strategic decision making.

Based on the volume, shape, and latency the type of Big Data technology to be deployed in a company is determined.

Precise mapping of data properties, frequencies, and sources are tagged as significant angles while devising the development strategy.

Analytics
Analytics is quite likely to include cultivating and operationalizing predictive, descriptive, text mining leveraging data sources.

To make the most of analytics, an amalgamation of traditional technologies and a distributed environment for Big Data can possibly the best road open for some companies to accomplish their business objective.

Technology
For most business leaders, it is relatable when we quote that ‘the present infrastructure in many companies is limited to minor data problems’.

Close examination of the existing hardware and software can bridge the gap between tradition and modern approach with ace technologies and predominant systems.

Finally Big Data Integration

The whole idea behind the smooth integration of Big Data technologies in the present infrastructure is to achieve no disruption, zero business downtime, and no cost overruns.

For such integration, numerous databases, nodes, and clusters are required to be explored.

At a business enterprise level, cross-project inter-departmental and multi-platform integration of Big Data technologies must be decided at an early stage, since this can be a difficult task to complete later on.

Concluding Note

Like it or not, a comprehensive, rigorous and importunate decision-making is the absolute need of the hour for deploying Big Data Technologies in any company.

Furthermore, the strategy should make amends with the changing landscape of Big Data technologies.

The deployment strategy is more than a certain piece of information jotted down on a piece of paper.

At SPIN, we understand the mechanism to dispose of Big Data strategy within the present infrastructure of a company in order to bring to pass maximum impact (in a positive way).

Connect with us and believe us. Today!

The unremitting expansion of data with time has compelled businesses to place data at the very center of any strategic business decision to safeguard a bright lucrative future.

In a bid to stay ahead of the pack in the days to come, businesses are using Predictive Analytics to make use of unending growth opportunities.

Over time, Predictive Analytics has gained its glory, thanks to its multiple applications.

Time and again, the concept of Predictive Analytics (which is also called as Advanced Analytics) has been linked with one of the most popular trends-business intelligence.

Whether they are linked or not, is a different story altogether, but their motto is unanimous: provide benefit to the company and its clients.

So what is Predictive Analytics?

It refers to the effective amalgamation of ML, historical data along with AI to take the most feasible hunch about the business possibilities of the future.

The historical data collected is added in a mathematical model that gives assent to key patterns and trends in the data.

In the next step, the model is used for the current data to figure out what will happen in the future.

Here is the workflow of Predictive Analytics for a better understanding.

Access and explore data- Process the data-Develop Predictive models-Merge analytics with systems

Prescriptive Analytics – commonly used terms with Predictive Analytics

Companies that have effectively integrated Predictive Analytics tag Prescriptive Analytics as the next lucrative frontier to approach.

Questions may arise as to how both the terms are inter-linked.

The answer to this lies in the fact that while Predictive Analytics gives a vivid picture of the possible future.

While Prescriptive Analytics reels off how to respond in the best way possible, in tune with the prediction.

How Predictive Analytics exercises its duty?

  1. The first and foremost step of Predictive Analytics is to figure out what are the questions you wish to be answered, based on the past data.
  2. The second step includes figuring out if you have the right data to answer the questions you asked.
  3. The third step includes training your business system to learn everything from your data to forecast outcomes.
  4. Plan your modules
  5. Use your forecasts and insights in your line of business applications for priceless outcomes.

Does your business need Predictive Analytics?

Irrespective of the fact that there are numerous aspects in a business, that needs special attention, Predictive Analytics finds its fit in almost every bit of an organization.

Here are few pointers to start-off with:

  • Customer Relationship Management (CRM) – Predictive Analytics models can be applied to enterprise applications like CRM, to figure out proper messages to target the customers in the days to come. By predicting the next likely move of the customer, you can spend your messaging dollars effectively.
  • Marketing- Using Predictive Analytics it is possible to determine the preferences of the customers based on past data and previous history. This will help to predict the future course of action for the company to retain more customers and increase productivity tenfold.
  • Manage risks- Using Predictive Analytics effectively can help businesses to sketch a roadmap for the company. By predicting future outcomes and possibilities, Predictive Analytics can help organizations to cut down risks significantly.

Let’s start predicting

Companies that have deployed Predictive Analytics in their business operations have flourished beyond expectations, in comparison to the ones who still playing with the thought of it.

Comprehending customers better by tapping on their requirements, and customizing the content as per the needs does wonder for a business, and Predictive Analytics is the key to it.

Well-informed use of Predictive Analytics helps organizations to be aware of market forces and secure their dominance in today’s competitive world.

All in all, predicting the future outcomes guarantees one important fact- substantial gain for the business and its clients.

Still, think Predictive Analytics is a bit confusing for you? SPIN is here to clear all your doubts.