Several companies look for talented resources that possess both UI and UX design skills. The major reason is that having both the skills proves to be an attractive combo for the employer. Although having both UI and UX design skills may prove to be beneficial, there are certain unique differences between the two. In this blog, we will understand the differences between UI and UX Design.
UI stands for User Interface, which is a series of specific assets users interact with in order to experience a product or service. For example: screen, pages, and other visual design elements such as colors and typography, button, icons, etc.
UX stands for User experience which deals with the interaction and experience users have with a company’s internal products and services. Based on a user’s experience, the interaction patterns can be modified and made better.
Both these terminologies may seem to be similar, but they are not. While a good UI design helps to attract users, a good UX design helps to sell the products or services. While UI caters to only interfaces, UX designing caters to products and services in addition to interfaces.
UI designers are responsible for creating an attractive product appearance which results in branding and graphic development, customer analysis, and creating user guides or storylines. They work on developing UI prototypes and implementing it.
The UX designer is responsible for content strategy, customer analysis, and product strategy. They work on prototyping, testing, development and planning of overall user experience for company’s products and services.
3.Colors in Use
This is a unique difference between both the designers. UI designers tend to design the prototypes in full color. On the other hand, UX designers use only three colors in the prototype design – Black, White, and Gray.
This difference can be prominently seen in their designing styles specially in the usage of assets like icons, buttons, pages, images, drop down lists, text fields, checkboxes, etc.
The functioning of the two roles differ because of the different tools used by the UI and UX designers.
For UI designers, designing images is of utmost importance. They tend to use the best tools for creating images such as, Flinto and Principle. Both these tools offer the ability to sketch, which comes handy for developing images.
UX Designers look for tools that help them modify and improvise user experience from time to time. This means, they must be able to test and preview projects from time to time. Mockplus is one such prototyping tool that is helpful during the testing process.
Both the roles may be distinct, but they complement each other. However, it is important to understand the differences between the two roles in order to use them wisely. In conclusion, let us summarize all the differences.
Takes care of how things look
Takes care of how things work
UI elements include icons, drop down lists, text fields, buttons, and more.
UX elements include visual design, usability, interactive patterns, and more
Uses full colors for prototyping
Uses White, Black, and Gray colors for prototyping
The world is digital more than it was a year ago, with Covid-19 pushing most human activities online. There is a huge surge in the demand for information online. Web pages, email, science journals, e- books, social media websites, news feeds provide a lot of data. In order to sort the data into information and make sure that it reaches the target audience fast is what text classification is all about.
According to IBM, 80 % of all information is unstructured and companies have hard time extracting required information from textual data with analyzing, understanding, organizing and sorting taking a lot of time.
As the CEO and President of Amazon, said in his annual shareholder’s letter, over the past decades that computers have broadly automated tasks that programmers could describe with clear rules and algorithms. Modern machine learning techniques make it easier to do the tasks for which tracing the precise rules is much harder. – Jeff Bezos
This is where auto-classification comes in, as the name implies it is classification of text into categories. Tasks are automated using machine learning making the whole process super-fast and efficient. Artificial Intelligence applies machine learning, deep learning and other techniques that make tasks faster. AI has enabled IoT that uses technology to make smart Televisions to Flasks.
Reasons for Leveraging Text Classification with Machine Learning
Automating the process of analyzing and organizing data which is in the form of text results in much faster and efficient results. Reading and restructuring each text is time consuming for the human mind’s.Machine learning enables analyzing millions of texts at a fraction of cost.
Companies could use real – time analysis for critical situations to take immediate action. Text classifiers with machine learning can make accurate predictions in real time that can be used to make decisions right away.
Machine learning with text classifications outputs accurate results consistently. Humans make errors due to fatigue, boredom and distractions that are overcome by text classifications.
Applications of Text Classification
It involves an automated process of scanning texts for positive, negative or neutral emotions. It is also called sentimental analysis. Emotion Analysis covers a range of applications like product analytics, brand monitoring, customer support, market research, workforce analytics, and much more.
The topic is studied carefully for clubbed for related subjects. It involves rearranging of data according to the related topic, for ex: sorting out the latest news of the hours, organizing customer reviews by its topic or clubbing together
Language detection is an important element of text classification; it is the process of classifying text according to its language. These text classifiers are used for routing purposes (e.g. route the related customers to according to the services they are looking for).
Text classifiers are used for detecting the purpose of customers from their conversations like phone calls, email, chat and social media posts that is used to promoted customized products or for product analytics
For example, the following classifier was trained for detecting the intent from replies in customer’s chats. The classifier tags the customers as Interested, Not Interested, Unsubscribe, Wrong Person, Email Bounce, andAuto Responder etc.
This technology is used in applications such as:
Social media monitoring
Voice of customer
Resources for Text Classification
Dataset to provide examples for training the classifier – We need training data that will guide your text classifier. An efficient classifier depends on the right data that best represents the outcome that you are looking for. Gathering the right data is the key. E.g.: you want to predict the intent from particular data sets like chats on social media, you need to identify and gather such data exchanges that represent different intents so as to predict the outcome. If you feed your algorithm with another type of data, it is not going to give the desired result.
Training data can be found internally and externally. Internal data generated from apps and tools that we use everyday such as CRM, chat apps, help desk software, survey tools etc. External data include data available publicly on the internet, on social media sites or public data sets.
Some publicly available datasets that you can use for building text classifier
Reuter’s news dataset
It contains 21,578 news articles from Reuters labeled with 135 categories with varied topic, such as Politics, Economics, Sports, and Business
20 Newsgroups: It is a popular, widely accessed dataset that consists of 20,000 documents across 20 different topics.
Datasets for Sentiment Analysis
Amazon Product Reviews: A well-known dataset that contains around 143 million reviews and star ratings (1 to 5 stars) spanning from May 1996 – July 2014.
IMDB reviews: It is much smaller dataset with 25,000 movie reviews labeled as positive and negative from the Internet Movie Database (IMDB)
Twitter Airline Sentiment: With around 15,000 tweets about airlines that is labeled as
Labeled as positive, neutral, and negative, this dataset is very handy
Other Popular Datasets
Spambase: This dataset consists of 4,601 emails labeled as spam and not spam
SMS Spam Collection:spam detection dataset that consists of 5,574 SMS messages tagged as spam or legitimate.
A tool for generating and consuming the classifier- Once the classification categories are defined, the labeled data is fed into the machine learning algorithm and it is called supervised classification. The algorithm is set up to take on the labeled dataset, making sure that it generates the desired output. Example of supervised classification is spam filtering where the incoming email is automatically categorized based on its content. Other examples are Emotion Analysis, Topic Labeling, Purpose Detection, Identifying emergency situations by analyzing online information etc.
Some of the resources used in the different phases of the process, that is transforming texts into vectors, training machine learning algorithms and using the model to make predictions are:
Open Source libraries
Open source libraries are available for developers interested in applying text classification. Python, Java, and R offer a wide selection of machine learning libraries that are actively developed with a diverse set of features, performance, and capabilities.
SaaS APIs for Text Classification
Software as a Service (SaaS) for text classification is for people without any knowledge in machine language. SaaS don’t require machine learning experience and even people who don’t know how to code can use and experience the power of text classifiers. Some of the SaaS solutions and APIs for text classification include:
Google Cloud NLP
Supervised Classification is where the computer imitates human actions. The classifier has to be trained to identify emergency situations with accuracy from millions of text lines which could be from email text or online conversations.
It uses functions, sampling techniques and methods like building a stack of multiple classifiers in a step by step result oriented process. Algorithms are given a set of data called the train data which generate AI models that are given untagged data that are automatically classified.
Unsupervised Text Classification
Unsupervised classification does not depend on external information for the process. The algorithms are formulated to discover natural structure in data. Natural structure is not what we think of as logical division. Similar patterns and structures data points are identified and grouped into clusters by the algorithms. Data is classified based on the clusters formed. An example is Google search. Here the algorithm makes clusters based on the search sequence that the user requests and outputs them as results to the user.
Every data point is embedded into the hyperspace. The data exploration helps to find similar data points based on textual similarity. Similar data points form a cluster of nearest neighbors. Unsupervised classification enables generating quality insights from textual data and is language agnostic since it is customizable as no tagging is required and can operate on any textual data without the need of training and tagging it.
Custom Text Classification
A lot of the time, the biggest barrier to Machine learning is the unavailability of a data-set. Businesses and individuals are looking to apply AI for categorizing data but the necessity of a data-set is giving rise to a situation similar to a chicken-egg problem. That is where Custom text classification comes in; it is one of the best ways to build your own text classifier without any data set.
Altius has come up with unique methods for text classification using algorithm structures that are able to identify customer emotions on a large dataset and come up with new categories or dataset. This allows for the algorithm to create its own data set which is used to work against the data clusters. This training methodology is used in multiple neural network algorithms to get better results from different datasets. It brings down the cost and time takes to build a text classification model, since no training data is needed.
With the right tools and guidance, developing a mobile app is a piece of cake, whether it’s for amateurs or professionals for personal or business needs. Have a working app in more than a week’s time, by following the steps below:
Day 1: Look for problems that your app can solve
Your app should have value in day to day life, making people’s tasks easier. For example the most popular app is the Covid-19 app that has become an essential nowadays and there is room for the same kinds of apps with different functionalities. Coming up with innovative app ideas that users can implement in their day to day lives is the key to getting started, keeping in mind about your target audience.
Day 2: Get your plan on paper using wireframe
Create a rough sketch on how your app screen needs to be, with all the graphical features and options that you have imagined. This gives clarity on how your app needs to be designed. It helps to get a flow and to keep check on the developments in the designing phase.
Day 3: Choosing the Development Environment
The environment is where you do all your coding for the app. It is called the ‘Integrated development Environment’, IDE. Building Android apps require downloading of Android Studio and Java and Android SDK which is fairly easy to begin with clear user instructions available online.
Day 4: Keeping a day to get around Java would help
Get familiar with the basics of programming like variables, classes and conditional statements. There are numerous java basic tutorials online that can help the reader to catch up.
Day 5: Getting your Images
Figuring out the appropriate images and gathering them would be the next step. Free Image editing tools like Adobe and Illustrator would be best choices to edit images.
Day 6: Using Android Designer to create your layout
This tool allows you to drag and drop the frames or widgets to the pages. Let’s keep the app as simple as possible with one or two pages. Start a new project in the Android Studio; select File-> New->New Project. You need to follow the steps leading to selecting ‘Empty Activity’. This will launch the designer mode of the Android studio.
Day 7: Writing the Java Code
Knowing the basics of java will come in handy in this step. Catching up with java resources online like ‘Build an Android App’ is recommended. Here you will get a clear way of going around with operations, variables and button clicks. A debug APK or AVD (Android Virtual Device) Manager is needed to test the code.
Day 8: Make sure the functionalities are working
Look for codes to make the Text Boxes, Buttons, animations work. Google on the internet with keywords ‘Android Studio Play MP3 on click” to get the corresponding code. Make sure you get all your functionalities running this day.
Day 9: Testing
Your app is ready with all the required elements. Even though it is an amateur representation, it is worth testing it thoroughly, maybe your close friends and family can help you with this.
Day 10: Publish your app
Create a new APK that users will download to use your app. Go to this link ‘Sign your app’. This ensures that only you can update your mobile application. Use this link to ‘ Build and run your app’ which lets you publish your app.
After providing the products with the right amount of data, it is also important that the right product images are uploaded to your product page. Your customers want as much information as possible within a few clicks or within a few seconds.
Your visitors do not have the patience or the time and will leave if they don’t find the right information. It is also proven that some people like images, some people like data sheets, some people like technical specifications.
We have to look at the entire process of giving the right kind of data to our buyers.
Look at it from an example of a department store.
The kind of support that the customers got earlier reduced constantly.
There used to be a helper per bay which reduced to a helper per aisle, per floor and it has now moved to a low touch model of having no people.
The stores have a human-machine interface where people go to the aisle which is guided by retail signage.
They select the products in the cart, pay the money and walk out.
However, in an online store, with the aisle by the mile model, your data is your sales representative.
Giving the right information about the product is very important because the aisle concept is dead in an online model. Buyers cannot find products on their own because they only see one home page and they have to search.
This is important because there is no point having the product on the website if people cannot find it.
The right images also need to be there because of a low touch purchase model where the feeling of uncertainty post-purchase will be high. When you make your website very flexible because of the richness of the site, even a robot can even pick up and place the order.
When they started, they made “Google Search” so that anyone can find what they need among the gazillion things in the world. But today, sometimes its easy to feel like you need a little help just in your own world. Your photos, phones, videos, calendars, messages, friends, trips, reservations and so on.
Wouldn’t it be nice if you had help with all that?
Wouldn’t it be nice if you had a google for your world?
That’s exactly why they built something called google assistant.
Google assistant is getting smarter day by day, no doubt about that. Your assistant can respond in English, French, German, Hindi, Indonesian, Japanese, Portuguese and Spanish.
That’s a lot of languages, yet they are working on expanding the range. This device can not only work in different languages, but it can literally control your entire life digitally.
The assistant can basically do anything you want. You can ask random questions and your personal google assistant will have an answer.
All you have to say is “Ok Google” or press and hold the home button on your android phone for it to obey your commands.
That’s right, it’s as simple as that!
This artificial intelligent helper can call and send messages to your loved ones, when you give a vocal command.
You can even carry on a conversation with it. The assistant is always there for you, so if you’re on the road and you need to find a gas station, you can ask where to fill up.
If you are at home, you ask for it to favourite music, or if you are in a chat with a friend, it can show you what movie is playing tonight.
Its like your own personal google. Your google assistant can work on any device.
It can even wake you up. Waking up is a huge task for everyone, it becomes harder when you must wake up to a wailing noise. Well, google assistant can make it peaceful.
All you must do is say “hey google, set an alarm at 6 o’clock that plays (any one of your favourite songs)” your day starts off well when you wake up listening to your playlist.
Naturally, everything you share with your google assistant is safe and secured. The more you use your google assistant, the more useful it becomes.
Now what are you waiting for? Start using your personal assistant immediately.
Say Hi to your own personal google, always ready to help!
t is a known fact that the distributor ends up getting quite a bit of product returns(At least 30% of all products ordered online are returned).
The reasons are product damage, wrong pricing, wrong order to name a few.
From an e-commerce company owner or a product owner perspective, the reasons for damage and the price may not be relevant, but you can take steps in ensuring that your customers don’t order the wrong products.
Wrong orders happen because the visitors do not see adequate information about the product that they search. Since some customers may have a time pressure to purchase, they end up making some assumptions about the product and buys it in-spite of this lack of product information.
However, the customers figure out the lack of fitment, when the product reaches the warehouse. The customers return the products to the store. The store owner incurs the cost of shipment, inventory and a loss of faith with these customers.
How can you ensure adequate product information?
You have to locate the product information from multiple sources and provide the information in a structured manner. You should also give adequate technical specifications about the product for the customers to compare and to confirm the fitness of the product to the industrial use case requirement. You should cross map the products in multiple application areas which are the place where the bulk of oversight happens
“Getting a quality website is not an expense, but rather an investment.” – Dr Christopher Dayagdag
A website is undoubtedly the most important aspect of any business. It serves as a platform to present your offerings to prospective customers. Moreover, a good website helps you in establishing your business credibility. As a website is almost always accessible, it acts as a medium for interested people to look up for information at their convenient time.
You can opt for a static website, a dynamic website or an e-commerce website for your business.
This blog aims at giving you an idea of each type of website along with its pros and cons to help you decide on the website that best meets your needs.
A static website is the simplest kind of website, and is very easy to create. The contents of this website get changed only when a manual update is done.
An example is a website that gives information about a company and the services that it has to offer.
It is quick, easy and cheap to develop such a website.
Indexing of this type of website by search engines is relatively easy.
This website loads reasonably fast in case of slow Internet connections.
Functionalities are restricted in a static website.
Content updation may become difficult because you may have to rely on web designers to do this.
Long-term cost for maintaining this kind of website can be very high.
A dynamic website is interactive in nature and displays content according to the user’s requirements. You can login, chat and get information, as well as make payments using such a website.
Two common examples are a social media website and a search engine.
You can modify a dynamic website easily based on your preferences or requirements.
There will be minimal ongoing maintenance charges.
The loading time may slow down because of the multiple functionalities involved in displaying the contents.
The initial development and hosting charges tend to be high.
An e-commerce website allows you to buy products or receive services online from across the globe. The payment is often made online through the same secure portal. The common types of e-commerce websites are Business-to-Business (B2B), Business-to-Consumer (B2C), Consumer-to-Business (C2B) and Consumer-to-Consumer (B2B).
Amazon, eBay and Flipkart are some well-known examples of e-commerce websites.
You can get your products across to customers round the clock.
There is no cost involved in establishing a physical company setup.
You can sell both products that are your own and those of other retailers.
You can reach out to customers in any geographic location and thus increase the customer base.
There is very less possibility of the customer interacting with the company personnel face to face when he wants to know about a product or service.
This website is prone to attacks by hackers, putting the payment gateway at stake if appropriate safety measures are not taken.
If your website crashes for some reason, you are less likely to be able to make your offerings available through any other source.
To conclude, if you have a small-scale business with always the same offerings for all customers, a static website is the best choice. On the other hand, if you would like to display customized content, a dynamic website is a better idea. Finally, if you have a wide range of offerings and want a lot of customers with minimum overhead costs, you might want to give a thought to having an e-commerce website for your business.
E-Commerce is a huge online industry that commands a good amount of revenue in the digital marketing space. Business has been booming in the last couple of years, as the millenials prefer to buy online instead of walking into a brick & mortar store.Leading companies now focus their marketing spends on promoting their e-store rather than traditional advertising.
Your e-store is now the face of your brand. Having an enriched e-store is crucial to increase brand image and tempt purchase to online surfers.
Now people prefer to purchase items online , that are not readily available in their hometown area. They look at product descriptions, feedback and reviews and make an informed purchase decision.
The main features for E-commerce Product content services
Good product information
Good site design & photos
Easy search in website.
Information is the lifeblood of your organization & business. Altius Technologies has the resources and technology to help you enhance your data at any given point in time.
Enrichment allows you to value-add details for your product on a variety of landing pages and navigation links, which makes it rich and thorough.
An enriched e-store will always score above static pages. With many e-commerce market places now operating on a B2C level, customers expect the same kind of quality in B2B e-stores aswell.
Research shows that most e-store owners lose customers prior to check out due to the lack of product descriptions, SEO friendly keywords or low-res images. Purchase decisions are based on the product descriptors and tech specs the e-store provides. It is imperative that this information is correct and relevant to your customers.
Product data enrichment provides contextual and useful information related to your products and helps drive sales. Entities like us offering B2B product content services have been forced to switch or upgrade our strategies, particularly in product catalog management aswell.
Benefits of Product Data Enrichment
Reduce overhead costs associated with in-house enrichment and management of product catalogues.
Consistently deliver high-quality product information at scale to address your need for high-volume quality content.
Get insight-driven content that makes product information relevant and engaging for your customers
Product Data Enrichment Services
MSDS (Material Safety Data Sheets)
Videos for example
Qualitative research is an important factor for Product content services, revolves around describing characteristics. It does not use numbers. A good way to remember qualitative products which are key for good content writing.
The Best E-commerce Platformfor Growing Sales includes good images, content information in detail, web research, price details and most important is the payment gateway which gives a good kick start for the companies.
User Experience (UX) and User Interface (UI) are two key parameters that play a key role in any design process. UX design is almost always followed by UI design.
The right combination of user experience and user interface marks the success of any product or service. The following are the key components of any UX/UI design.
Strategy pertains to analyzing various parameters related to a particular product or service. These factors include business objectives like why the product or service is needed and who the user is.
Scope takes into consideration both the functional and content requirements of the product or service.
Functional requirements deal with the functions and features. They specify how the various functions and/or features work independently and with each other.
Content requirements relate to the information required for proper functioning. These include details like videos, audios, images, text and more.
Utility focuses on building the right product for the right users. The factors analyzed above in Strategy are implemented in developing the product or service.
Usability aims at making the product or service easy to use for the customer. It deals with identifying the problems faced in using the same and correcting them. This helps the customer accomplish his/her task effortlessly.
This component also deals with how the system addresses errors and the instructions were given to a user if he encounters the same.
The structure is based on two features – Interaction Design and Information Architecture.
Functional requirements serve as the input for Interaction Design. It highlights how the user interacts with a product or service and the return response.
Content requirements form the inputs for Information Architecture. It helps to determine how the various content elements must be placed and/or organized for better human understanding.
Skeleton deals with the visual or sensory design of the product or service. It focuses on the appearance of content and controls like the correct layout, typography and such aspects. This guides the user on what he can do with the product.
Prototyping involves testing the look, interactive elements and usability of various elements of the product or service using multiple scenarios. This process is carried out before the actual development phase begins.
Desirability focuses on retaining the customer’s engagement with a product or service. The aim is to make his/her experience enjoyable and delightful each time the product is used.
Credibility assesses the user’s trust in the product or service offered. The user must have the assurance that the information rendered is accurate. He/she should also be convinced that the product does what it is expected to do. The performance will be steady for a considerate period of time.
Accessibility ensures that the product or service can be used by people with varying abilities. The ideal offering must be easily usable by both normal and differently-abled people alike.
The surface is the implementation of all the factors decided upon in Structure and Skeleton in the final product or service.
In general, User Experience highlights the attitudes and emotions of a person regarding the use of a product or service. User Interface focuses on the look and feels aspects while acting as the medium of interaction between humans and machines.
The number of domains deploying artificial intelligence using various technologies is increasing day by day.
AI in Healthcare
Artificial Intelligence based systems are widely deployed in the healthcare sector to help in faster and better diagnoses than human beings. Systems have been developed to analyze a patient’s reports and help in suggesting the correct and customized treatment path.
Manufacturers like Apple and FitBit AI have also incorporated AI in their fitness and health trackers to monitor users’ activity and heart rate levels.
AI in Business
Businesses make use of robotic process automation systems to perform repetitive tasks. Similarly, CRM platforms utilize machine learning algorithms to analyze how to serve customers.
Many e-commerce websites use virtual assistants in the form of chatbots. These chatbots act as online customer service representatives and interact with users. They respond to their queries and help them with what they want.
AI in Virtual Assistants
Virtual assistants like Siri and Alexa incorporate speech recognition systems that allow users to find solutions to their queries using voice based commands. Such systems recognize spoken sounds as words and convert them into text. This saves a lot of time spent on typing what you want to know.
AI in Gaming
Video games rely heavily on neural networks and deep learning to create a realistic and human like experience. They also help game avatars to move around in various ways. On the other hand, deep learning contributes to creating lively gaming content.
Artificial Intelligence also plays an important role in developing strategic games like tic-tac-toe and chess. These games make use of heuristic knowledge to offer many moves and combinations.
AI in Finance
AI techniques help financial institutions to perform various tasks like to identify fraudulent transactions, analyze and manage risks, detect money laundering and predict credit score.
Banks offer voice assisted banking using natural language processing to connect users to the various services available and resolve their queries. Chatbots facilitate two-way communication round the clock and save customers the hassle of waiting in long queues for their turn.
AI in Transportation
Automobile giants like Tesla have begun including fuzzy logic systems in their vehicles. These systems offer various driver assist features like parking, reversing and even turning. They can also help the driver determine the wait time at a signal and save fuel by turning the ignition ON or OFF appropriately.
Big players in the automobile industry have started considering the feasibility of autonomous or self-driven cars. These cars will be capable of judging their environments by themselves and moving accordingly with no or minimum human input.
Artificial Intelligence has actually made its way into almost all domains to make the life of humans easier with better and faster performance.