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Swift programming language is very powerful and intuitive. It incorporates the best of C and Objective-C for iOS, OS X, tvOS, and watchOS. It proves to be effective as it can eliminate the constraints of C compatibility.

Swift has the potential to become the de-facto programming language for creating immersive, responsive, consumer-facing applications for years to come. Comments can include Markdown syntax to add rich text and embedded images that display in Xcode’s Quick Help. A new assistant shows your Swift API in a “header-like” view. And new syntax features combined with improvements to the Cocoa frameworks and Objective-C will make your code more expressive, and even safer.

Swift programming language has not only received widespread acceptance but has also become one of the software developers’ favorite tools. So, here we’ll discuss 10 reasons to learn swift programming language.

  1. Swift is easier to read.
  2. It is also easy to maintain because programmers need not put effort into bookkeeping..
  3. The Swift run-time crash will stop on the line of code where a nil optional variable has been used, preventing errors in codes. Thus, swift is a safe programming language.
  4. The huge memory leaks that a programmer can have in Objective-C are impossible in Swift. We can say — it unifies with efficient memory management.
  5. It has a concise code structure.
  6. Swift is an extremely fast programming language.
  7. With Swift, namespaces are based on the target that a code file belongs to. This means programmers can differentiate classes or values using the namespace identifier. 
  8. It supports dynamic libraries.
  9. With playgrounds, it encourages interactive codings.
  10. Swift provides the development community a direct way to influence a language to create intuitive apps.

Let’s look at the benefits of learning swift in detail.

1. Swift is Easier to Read

Objective-C suffers all warts you’d expect from a language built on C. To differentiate keywords and types from C types, Objective-C introduced new keywords using the @ symbol. Because Swift isn’t built on C, it can unify all the keywords and remove the numerous @ symbols in front of every Objective-C type or object-related keyword. Swift drops legacy conventions. Thus, you no longer need semicolons to end lines or parenthesis to surround conditional expressions inside if/else statements. Another large change is that method calls do not nest inside each other resulting in bracket hell — bye-bye, [[[ ]]]

You’ll be amazed to know that currently there are nearly 2.1 million swift developers, surpassing the number of Objective-C developers (1.6 million). Also, according to the Stack OverFlow survey 2019, swift is also one of the programming languages associated with highest salaries worldwide. Perhaps, this gives many developers a reason to learn swift! ;)

Method and function call in Swift use the industry-standard comma-separated list of parameters within parentheses. The result is a cleaner, more expressive language with a simplified syntax and grammar. Swift code more closely resembles natural English, in addition to other modern popular programming languages. This readability makes it easier for existing programmers from JavaScript, Java, Python, C#, and C++ to adopt Swift into their toolchain — unlike the ugly duckling that was Objective-C. Thus, to learn swift isn’t like getting into a completely new programming language at all.

2. It is Easier To Maintain

Swift drops the two-file requirement. Xcode and the LLVM compiler can figure out dependencies and perform incremental builds automatically in Swift 1.2. As a result, the repetitive task of separating the table of contents (header file) from the body (implementation file) is a thing of the past. Swift combines the Objective-C header (.h) and implementation files (.m) into a single code file (.swift).Xcode and the LLVM compiler can do work behind the scenes to reduce the workload on the programmer. With Swift, programmers do less bookkeeping and can spend more time creating app logic. Swift cuts out boilerplate work and improves the quality of code, comments, and features that are supported.

Benefits of Swift Programming Language

3. Swift Programming Language is Safe

Optional types make the possibility of a nil optional value very clear in Swift code, which means it can generate a compiler error as you write bad code. This creates a short feedback loop and allows programmers to code with intention. Problems can be fixed as code is written, which greatly reduces the amount of time and money that you will spend on fixing bugs related to pointer logic from Objective-C. Unlike in Objective-C, in Swift, the optional types and value types make it explicitly clear in the method definition if the value exists or if it has the potential to be optional (that is, the value may exist or it may be nil).

To provide predictable behavior Swift triggers a run-time crash if a nil optional variable is used. This crash provides consistent behavior, which eases the bug-fixing process because it forces the programmer to fix the issue right away. The Swift run-time crash will stop on the line of code whenever it finds a nil optional variable. This prevents the bugs in the swift code.

4. It is Unified with Memory Management

Swift unifies the language in a way that Objective-C never has. The support for Automatic Reference Counting (ARC) is complete across the procedural and object-oriented code paths. The huge memory leaks that a programmer can have in Objective-C are impossible in Swift. A programmer should not have to think about memory for every digital object he or she creates. Because ARC handles all memory management at compile-time, the brainpower that would have gone towards memory management can instead be focused on core app logic and new features. Because ARC in Swift works across both procedural and object-oriented code, it requires no more mental context switches for programmers, even as they write code that touches lower-level APIs — a problem with the current version of Objective-C.

Automatic and high-performance memory management is a problem that has been solved by Swift and it has proven it can increase productivity. The other side effect is that both Objective-C and Swift do not suffer from a Garbage Collector running cleaning up for unused memory, like Java, Go, or C#. This is an important factor for any programming language that will be used for responsive graphics and user input, especially on a tactile device like the iPhone, Apple Watch, or iPad (where lag is frustrating and makes users perceive an app is broken).

5. Concise Code Structure

Swift reduces writing the amount of code for repetitive statements and string manipulation. Swift adopts modern programming language features like adding two strings together with a “+” operator, which is missing in Objective-C. Support for combining characters and strings like this is fundamental for any programming language that displays text to a user on a screen. The type system in Swift reduces the complexity of code statements — as the compiler can figure out types. 

Swift supports string interpolation, which eliminates the need to memorize tokens and allows programmers to insert variables directly inline to a user-facing string, such as a label or button title. The type inferencing system and string interpolation mitigate a common source of crashes that are common in Objective-C. Swift relieves you from bookkeeping work, translating into less code to write (code that is now less error-prone) because of its inline support for manipulating text strings and data.

6. Swift is Really Fast

Swift code performance continues to point to Apple’s dedication to improving the speed at which Swift can run app logic. The enhancements also enabled Swift to outperform C++ for the Mandelbrot algorithm by a factor of a mere 1.03.

With an optimized compiler for performance and the language for development, it generates faster code across the board, both for release and debug builds. The Swift compiler is also faster, even while adding new Fix-it suggestions such as where you can use let instead of var.

7. There’s Fewer Name Collision With Open Source Projects

One issue that has plagued Objective-C code is its lack of formal support for namespaces, which was C++’s solution to code file-name collisions. Swift provides implicit namespaces that allow the same code file to exist across multiple projects without causing a build failure and requiring names like NSString (Next Step — Steve Jobs’ company after being fired from Apple) or CGPoint (Core Graphics). Ultimately, this feature in Swift keeps programmers more productive. They don’t have to involve in bookkeeping that exists in Objective-C. 

You can see Swift’s influence with simple names like Array, Dictionary, and String instead of NSArray, NSDictionary, and NSString, which were born out of the lack of namespaces in Objective-C. With Swift, namespaces are based on the target that a code file belongs to. This means programmers can differentiate classes or values using the namespace identifier. This change in Swift is huge. It greatly facilitates incorporating open source projects, frameworks, and libraries into your code. The namespaces enable different software companies to create the same code filenames without worrying about collisions when integrating open source projects. Now both Facebook and Apple can use an object code file called FlyingCar.swift without any errors or build failures.

8. Swift Supports Dynamic Libraries

The biggest change in Swift is the switch from static libraries, which are updated at major point releases (iOS 8, iOS 7, and so on), to dynamic libraries. Dynamic libraries are executable chunks of code that can be linked to an app. This feature allows current Swift apps to link against newer versions of the Swift language as it evolves. 

The developer submits the app along with the libraries, both of which are digitally signed with the development certificate to ensure integrity (hello, NSA). This means Swift can evolve faster than iOS, which is a requirement for a modern programming language. Changes to the libraries are included with the latest update of an app on the App Store, and everything simply works. It reduces the initial size of an app by linking the external codes on use-basis.

Dynamic libraries in Swift make it possible for programming language changes and improvements to propagate faster than ever before. Users no longer need to wait for iOS point releases to benefit from any performance or reliability improvements Apple introduces into Swift.

9. Swift Playgrounds Encourages Interactive Coding

Swift’s newly introduced Playgrounds are a boon to experienced developers. Playgrounds enable programmers to test out a new algorithm or graphics routine, say 5 to 20 lines of code, without having to create an entire iPhone app. 

Apple has added inline code execution to Playgrounds. It helps programmers create a chunk of code or write an algorithm while getting feedback along the way. This feedback loop improves the speed of writing codes by replacing the traditional programming with data visualizations in Playgrounds. Programming is an iterative process. Any effort to reduce strain and complement the creative process can make programmers more productive. It can also free their time to solve bigger problems rather than focusing on boring details that traditional compilers impose on programmers.

10. Swift Is A Future You Can Influence

Objective-C isn’t going anywhere, but it won’t see as many major changes, thanks to the introduction of Swift. Some Swift features will likely migrate over to Objective-C, but Objective-C’s legacy in C means it can absorb only so much. Swift provides the development community a direct way to influence a language to create apps, embedded systems (if Apple ever licenses an embedded framework and chip for third parties), and devices like the Apple Watch.

Wrapping up with the best of Swift Programming Language

Writing Swift code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift possesses safer patterns for programming and it adds modern features to make programming easier, more flexible, and more fun.

Apple is focused on providing the best consumer experience and is building only those features deemed worthy of attention. The team supporting the development and evolution of Swift is keen on improving the language to better support the development community that builds apps and systems using Swift. If you’re thinking of learning Swift, this is the right time to get started.

If you’ve queries around different programming languages, we’ve covered some. Take a look.

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Insurance consumers around the globe are seeking convenience and expecting better customer experience. From millennials to Gen Z, with the agile connectivity, irrespective of the industry has numerous options to choose from. As the competition intensifies the insurance industry has to jump into the bandwagon of technovation in order to provide improved accuracy, cost-saving and excellent customer experience. 

Here is a list of the marketing trends in insurance that will prove to be a game-changer in the year 2020.

1. Robo Financial Advisors

According to a Business Insider Intelligence forecast, by the year 2020 Robo-advisers will manage investment products worth $1 trillion, which will spike up to $4.6 trillion by as early as 2022.

Robo advisors have been around for quite some time. In the year 2008, during the financial crisis, Jon Stein, a 30-year old entrepreneur launched “Betterment”, the first Robo-advisor. In recent years due to its low investment rates and data input based research results, it has increased in popularity. 

It is basically designed for the people who want to manage their finances with low management cost. Based on respective data inputs, the Robo-advisors offer any advisory services. 

The main purpose behind the making of the Robo-advisor is to bring the financial services to the wide range of population with lower investment cost as compared to the traditional human advisors. Upwardly.com, 5Paisa.com and Goalwise.com are some applications of Robo-advisors.

Behind the scenes of the software of Robo-advisors are actual human beings who track the market regularly and adjust the algorithms based on the current market condition. Robo-advisors are a boon to the end-users as they can invest in direct plans of mutual funds without shelling any commission. However lack of personalization and one-size-fits-all products are the areas of improvement.

2. Data Integration: The Future of Marketing

IDC estimates that, by the year 2020, the digital cosmos will reach 44 zettabytes, further complicating the lives of marketing professionals.

Integrating data sources is vital for any company, whether B2B or B2C to successfully meet Customer Experience expectations thereby drive accelerated sales revenue.

With an integrated source of information, retailers can administer and optimise marketing through KPI’s, metrics and dimensions that would not have been possible with the separate source system. In order to upscale marketing operations, a connected viewpoint is essential to evaluate the campaigns, audiences, events and channels, and drive the strategic goals.

From an operational viewpoint, CRM solution provides the organization with new business and the ERP system allows to manage and drive businesses around obstacles. A good place to start with the data integration is by Integrating these two systems shall provide marketers and the organizational sales-force with vital information, that can be shared with the stakeholders.

3. AI-driven Copywriting

Artificial intelligence can create cancer combating drugs, control self-driving cars, defeat the best brains at incredibly complex board games, but one realm it can’t perform flawlessly is communicating.

To help solve the issue, Google has been feeding it’s AI with more than 11,000 unpublished books, including 3,000 steamy romance titles. 

Autoencoder, a type of AI network, uses a data set to reproduce a result (in this case copywriting) using fewer steps. Insurers can harness this AI capability to create sentences and suggest the best-optimised language to approach the customers.

AI copywriting is evolving to a whole new level. Google granted  €706,000 (£621,000) to the Press Association, to run a news service with computers writing localised news stories. AI with the help of human journalists can write up to 30000 news stories a month and scale up the volume of the stories that would otherwise be impossible to produce manually.  

“Skilled human journalists will still be vital in the process, but Radar allows us to harness artificial intelligence to scale up to a volume of local stories that would be impossible to provide manually. It is a fantastic step forward for PA.”

  • PA’s editor-in-chief, Peter Clifton 

4. Gamification of Insurance

At the nexus of marketing trends ranging from social networking to the IoT to behavioural science and wearable tech;  gamification is a powerful lever for insurers and insurance agents. It creates an enriching digital experience and customer-centric business model.

Gamification offers great potential value to the insurance business process in the realm of consumer engagement and customer experience. From millennials to Gen Z, it has emerged as a useful practice and effective means to target early technology adopters by:

  • Transforming mundane tasks into interesting and fun experiences that keep users returning.
  • Increases brand awareness, brand penetration and affinity.
  • Increase sales by educating customers about product suitability and guide them to buying the product.
  • Motivating people to act in areas of healthcare and wellness, safe driving, financial planning and sustainability.

Ingress and AXA redefined the world of gaming and advertisement. December 5th, 2014, Niantic Labs the creator of ‘Ingress’ partnered with AXA. In the game, AXA Shield was initially only obtainable from AXA Portals, leading you to AXA business locations in person.

5. Advanced AI Capabilities in Insurance

Innovation and technology are the next frontiers in the insurance industry. While automation and IoT are already a reality for insurance, with the advent of AI there has been a holistic approach to Insurance automation. With insurance leveraging AI, it has expanded its reach to more ecosystems than ever before. Deploying AI capabilities in insurance can help make smarter underwriting decisions, fraud detections, risk assessment and create a better customer experience.

AI is driving significant change in business with insurance being no exception. It has the potential to enhance the insurance business model by-

  1. Improving the speed of the workflow: AI and RPA in insurance reduce redundancy of task. Automation of day to day tasks would reduce cost and time consumption thereby increasing accuracy, quality and competency.
  1. Customizing the services for better customer experience: One size no longer fits all, and the same goes for the insurance industry. With focus on individual markets, insurers can create niche usage-based products to sell the packages in a variety of ways.

Parag Sharma, CEO, Manta Labs and AI thought leader is going to speak about the Internet of Intelligent Experiences™: CX for the Digital Insurer at India Insurance Summit and Awards 2020 on March 12, 2020. Catch him live at IISA 2020.

Details

  1. Providing new insights: Insurance is no guessing game. Data in silos is the biggest drawback for any industry. AI in insurance can integrate this data and provide analytics to help actuaries have a better insight while making a decision about a product.

Marketing Trends in Insurance: The Bottom Line

Today, at the core of marketing in Insurance, lies AI, Machine Learning and advanced data analytics to foster better experiences for the end-user. We’ve listed 5 most important trends that have the potential to shape marketing business models for Insurance and InsurTech firms. Be it Robo financial advisors or gamification, impressing customers remains the prime goal for Insurers.

Have thoughts and queries regarding upcoming marketing trends in Insurance? Please feel free to drop us a word at hello@mantralabsglobal.com.

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Data Science is enormous. It brings forth a scientific approach to gather a massive amount of useful data from raw & disordered information (often collected from open sources). According to recent research, over 2.5 million terabytes of data appear daily. In 2020 every person produces 1.7 MB of data per second. Scientists, Analysts, and numerous other specialists use this data to derive decision-ready insights.

Using data science, marketers can get a clearer picture of their target audience. With this knowledge, any organization’s marketing department can formulate strategies to target customers who portray higher chances of conversion. Also, by delivering values, organizations can eventually maximize revenues. Going with the traditional methodologies, data processing can be a daunting task. Data Science offers a cost-effective solution to businesses seeking data-driven insights.

Let’s delve deeper into 5 most profitable and practical use cases of data science in marketing.

1. Budget Optimization

The primary goal of any marketer is to achieve the highest possible ROI from the allocated budget. This objective is undoubtedly difficult and time-consuming. On top of which, because of changing market dynamics and user preferences, strategies often go off the track leading to unanticipated outcomes.

Data science can be a saviour here. By analyzing the marketing department’s spending and acquisition ratio, organizations can build a model to distribute the budget in the smartest way possible. A clear picture will help marketers to invest money in the most relevant and surplus channels, thus optimizing key metrics.

2. Defining Audience Persona

While every marketer is familiar with the process of building the target audience portrait, determining the exact persona of the potential customer can still be a challenge. The lack of proper data insights might lead to ineffective advertiser decisions leading to a waste of resources.

Data science methods help marketers to understand the user persona and their preferred communication channels with data-driven insights. This means that the marketing budget will be spent on the right channels of influence, ignoring the irrelevant media, which a normal human being will think of covering for “just in case”. Such adjustment will inevitably increase the ROI and optimize the entire advertisement campaign. This will also retain brand relevance to the customers.

[Related: Your shopping cart just got a lot smarter!]

3. Brand New Social Media Marketing Strategy

Social media trends change faster than a human can track it. Facebook, LinkedIn, and Twitter define what is popular, and a marketer has to catch up with the trends.

Data science can keep you on track with the changing trends. Using the logic of Data Science in Marketing, one can get a bigger picture of what type of content people like interacting with. Data science allows us to gather and analyze data about people’s online behaviour. It provides the key metrics to adjust the SMM (Social Media Marketing) goals, which include – the time of posting, content type, amount, etc. These simple adjustments using data science insights can help increase the marketing ROI drastically.

4. Clearer Content Strategy

One of the biggest gaps between planning and execution that marketers face is knowing which channels will be affected and what kind of people will interact with their content and with what sentiment. Will be potential customers? Are interactors content gatherers? Are they the competition? Do they intend to ruin your reputation?

Knowing all this information will help streamline your content strategies.

As long as you know who your customers are; what are their perceptions about your brand; what information can attract/repel your customers; what social channels they are mostly active on; what are their sentiments with your content; what they usually do when they like or dislike a content; you’ll know what type of content you should produce.

For instance, some people hate emails, while others adore reading them. Some people want to resolve their queries publicly on social media, which some care about their online image. Data science can help achieve personalization to some extent, which can help humanize the conversations with your followers.

Let’s take another example of how data science in marketing can help stakeholders. It gives marketers insights about what phrases a customer would use while searching for a product/services online. Marketers can utilize this insight and prepare a content strategy that embeds these terms more often in your posts and articles.

Therefore, we can say that data science brings a variety of actionable insights about customer acquisition channels, their preferences, and engagement style, which can help plan content strategy accordingly.

5. Increasing Customer Loyalty

Your best customers are the ones who will not just purchase your product once but also will repeat buying and bring their friends and relatives to your store. Organizations realize that customer retention is easier than acquiring new customers.

But consolidating loyalty may be tricky. Data science can provide the marketing department with all the necessary information that can help boost customer loyalty. Based on purchase history and current search queries, analysts can predict their customer’s inclination towards a product. Accordingly, brands can create the most relevant offers for their customers. With personalized offers, existing customers feel special and will return to your brand and not go to the competitors.

The Essence of Data Science in Marketing

Using data science in marketing may ease the work of employees and uplift your strategies to new heights. We have to admit that the more structured information marketing teams have, the more effective their strategies become. At the core of any marketing efforts, data science can optimize cost for data processing and result in overwhelming conversion rates.

[Related: 5 Deep Learning Use Cases in Insurance]


About the Author: Marie Barnes is a writer for Bestforacar and an enthusiastic blogger interested in writing about technology, social media, work, travel, lifestyle, and current affairs. She shares her insights with the world through blogging. You can follow her on Medium.

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