The Importance of Retail Data Analytics

A correct set of retail data is sufficient to figure out if a customer is going to purchase from a store or will visit once again. Whenever folks go out shopping, they want to have an experience which is convenient, informative, and personalized. A retailer cannot provide a personalized experience if he does not have access to retail data analytics technology for obtaining information about particular shoppers and end users.

As compared to traditional retailers, e-commerce retailers find it easier to track and obtain information related to individual shoppers. This is because web technology makes it very easy for these e-tailers to gather data regarding customer purchases.

Web technology is also able to track the device through which customers access the website. What a customer went searching for from the showcased items to the time he spent on the site, every minute detail can be tracked. All this helps to understand customer persona and preferences at a deeper level.

With all this data, e-commerce websites are then able to deliver targeted emails, advertisements and personalized deals for customers, thus luring the customer to check out and make a purchase.

Access to such retail analytics helps in two things-

1) increases customer stickiness on the website with a personalized shopping experience and

2) increased sales from related items based on previous customer purchasing data

Video streaming services like Netflix are great examples where algorithms related to recommended videos drive more user engagement. All these benefits of data analytics are complicated to be derived from a physical store.

In short, the absence of data analytics technology can impact the physical store retailers negatively as they may not be able to provide a great experience to customers.

The use of Beacon Technology in Retail Analytics 

Store beacons are a piece of retail analytics technology which is becoming more and more popular in retail stores all over, mainly because of the multiple uses these beacons provide to the retailers. For instance, the tags can figure out those parts of your store that are busiest with the maximum number of customers.

This is a small detail, but it can help the retailers to a great extent. Such information can help store owners adjust and modify their display with products which they want the customers to be aware of. Promotional goods, for example, can be placed in areas where the traffic of customers is high usually.

The data collected through these beacons can also be used to monitor the traffic at particular hours of the day. A retailer with such a piece of information can plan out the allocation of his workforce and also the best position inside the store to place his items. 

These beacons can also be well-integrated into the mobile phones of shoppers. Once connected, customers can be sent welcome messages. Not only that, even reminders to purchase some particular items or any promotional offers available can be sent to these customers through the in-store beacons.

We are still not done. The beacons also provide help to trace the physical path through which a customer roams in the store while making his purchases. This is again a useful function as it helps to obtain and analyze specific shopping behaviors of particular customers while visiting a retail store. Walmart and Amazon Go stores have already been utilizing this piece of technology to yield significant benefits.

Amazon Go, in particular, has tweaked the use of beacon technology. Because these stores operate in a cashless manner, every customer gets a barcode scanned while entering the store. This barcode is on the Amazon Go app in the visiting shopper’s mobile phone. The customers then shop for their items and leave the store. A countless number of cameras inside the store track customers and their behavior.

It analyses all information such as what items they picked up, what they finally bought, and the items which they left behind, all of this os crucial information which gets recorded with the help of these cameras. Sophisticated computer systems take the data from the weight sensors to evaluate which products have been removed from a rack.

The moment a particular customer leaves the store, they are automatically charged for all the products which they have purchased. This is the closest a retail store can come to an e-commerce website, all of which is possible with the right technology.

Omnichannel Experience with Retail Data Analytics

If new retail analytics and reporting technology are merged cohesively, a considerable amount of data can easily be collected. This data will be capable enough to monitor every little piece of detail related to the behavior and buying preferences of customers. All of this data can be obtained from just one visit from a consumer.

Thus, with retail data analytics, stores can create an omnichannel shopping experience for customers. With smart stores, customers can have easy and cashless checkouts. Amazon Go is a great example. It gives customers the same online experience with its high-tech offline store.

Challenges with the adoption of Retail  Data Analytics

A lot of innovative products are there to help retailers who wish to have a better understanding of the customers visiting their stores. The issue is that only huge companies have financial resources where they can test and put the new technology-driven solutions to use.

The progress of these latest tools for retail analytics and reporting technology is pretty slow. What cannot be denied though, is the fact that technology is essential for any retailer today. If a customer does not receive an experience which is according to his expectations, no retailer will find the customer coming back to his doorstep.

Retailers should consider technology as an investment through which they can offer customized options according to customers’ preferences. Brick and mortar stores need to have the best retail technology possible without which retailers will not be able to provide the desired customer experience. 

If you are looking for data analytics solutions for your business, then GoodWorkLabs can help! Send us a short message with your requirements and our data analytics team can help you with a free consultation on the best data analytics solution for your business.

How Staff Augmentation can help your Business

Having a tough time hiring nerds every week?

Can’t get your hold on the cream talent of the mass?

Working in an IT firm means the staff turnover ratio is quite high. We have only one straight simple solution for all your hiring related worries – Outsource!

At GoodWorkLabs, we have helped both startups and fortune 500 companies with their technology needs by providing them with the right resources. Be it popular, on-demand, or niche skills, we have helped thousands of clients achieve their product development needs by deploying the best talent pool.

Not just that, GoodWorkLabs has also helped companies set up large teams in design, development, and QA with a concentrated staff augmentation strategy.

In this blog, we share FIVE reasons why you should outsource your tech requirements.

1. Massive reach of a highly-skilled talent pool

Consulting or staff augmentation firms have a grip on both the active and passive market. While an active resource pool is accessible to all, the real cream of talent sits in passive markets that are mostly untapped. Here is where outsourcing to a staffing firm makes all the difference to your hiring process.

The reach of consulting firms is much higher and you can hire highly skilled professionals easily. We all want technology experts to work on ever-changing product demands. Hence, it definitely makes business sense to outsource hiring.

2. Credibility with hiring managers

Staffing firms often work with the same hiring managers in order to keep the trust factor high. Corporate recruiters, on the other hand, work with several hiring managers. This trust factor and credibility is leveraged by the staffing firms and they continue to source better candidates for a given profile in comparison to the corporate recruiters.

3.  Longer guarantee periods

The best add-on benefit that comes with using staff augmentation services is that they offer an employee guarantee of 6 months to 1 year.  This is a great assurance and also a big relief to the IT firms as usually the minimum project length is 6 months. Businesses will be able to complete at least one project with the resource in the minimum guarantee period. 

4. Very Flexible and Cost-effective

The compensation of the staffing firm depends on the placement and not on how many candidates they managed to schedule for an interview. One of the biggest advantages of outsourcing your technology needs is that you enjoy the flexibility of utilizing a resource. From 6 months to 2 years, you can choose to renew your outsourcing contract and not worry about having too many resources on bench.

The staff augmentation model is very cost-effective as well. You don’t have to worry with admin and other employee onboarding costs as all of this will be taken care of by the staffing agency.

5. More consultative and less transactional

The primary aim of a technology consulting company is to find resources that are passionate, skilled, and are the perfect fit for your organization. Rather than being transactional, they go over and beyond to hand-pick candidates who will support your business in the long-run.

“Build relations and not quick transactions.”  At GoodWorkLabs, we give quality of candidates the highest priority.

Final Takeaway

Using the services of a high-quality external recruiting firm should be in your talent acquisition strategy if you are an IT firm. Instead of forcing these firms to stick to your internal control policies, leverage their potential of finding the best resource for you. Look at staff augmentation services as a multi-year investment that will continue to give you ROI. 

Get a gist of the consulting services provided by GoodWorkLabs and if you would like to get a free consultation on your outsourcing needs, then contact us.

GoodWorkLabs is conducting a massive walk-in drive on Saturday, 26th January between 10 am and 1 pm.

We are specifically looking for Java Developers who have a working experience of Spring boot and Microservices and has good knowledge of data structures, distributed systems, and algorithms.

Walk-in details:

Date: 26th January | Saturday

Time: 10 am to 1 pm

Venue: GoodWorkLabs, 4th floor, Akshay Tech Park, EPIP Zone, Whitefield, Bangalore – 560066.

Why you should join GoodWorkLabs

GoodWorkLabs is one of the fastest growing technology companies in India and is also a Google Certified Agency. We have been ranked as the 3rd Fastest Growing Technology Company by Financial Times in 2018. Right from Startups to Fortune 500 companies, the best of the brands have trusted GoodWorkLabs for all their technology requirements.

If you join GoodWorkLabs, you will get the opportunity to accelerate your career to the next level. You will get hands-on experience in working with top clients and will also work on the latest trending technologies.

Come attend the walk-in interview on 26th January 2019 at 10 am and give your career a boost

Data Analytics Tools for Business

Got your hands on millions worth of data, but can’t find ways to monetize it?

You aren’t alone! There are thousands of businesses experiencing the same issue.

With the advancement in technology, and better IoT and machine learning models, modern businesses are bound to deal with big ounces of data that require a lot of curating before it can be put any good use.

Knowledge was power, today data is power! With this powerful weapon, you definitely require guidance on how to curate this data and make it relevant. We first built the cloud, then data visualizations and business dashboards crashed their way in, thus replacing spreadsheets for analyzing and observing data insights.

But now, data analytics isn’t just for the sake of analyzing, it is much more.

Business Intelligence is also finding its way to enterprises. It has been a focus light throughout 2018, and now it’s time to continue its reign in 2019 too. Businesses, whether small or large are now looking for expanding their business intelligence and seeking solutions from the huge canopy of BI.  

Today, every businessman’s focus is on how to manage their increasing data this year. So, here are the top 5 data analytics tools to help you drive business growth in 2019!

Let’s see how these great tools can help using the era of multi-cloud accessibility and business intelligence, let’s see how these tools help:

1) Sisense for Artificial Intelligence and Business Intelligence

AI is helping machines to synthesize the functioning of a human brain. We need to know how our business is performing every day and every week. But with the help of artificial intelligence, we can understand the live performance of our firm. It means, we can see the insights every second!

Sisense is a great tool for building an intelligent AI system. The AI algorithm is supported by high-performing neural networks and is completely accurate. A lot of tech giants are using AI in many ways to keep themselves in the forefront. So, in 2019 it’s no surprise that this trend will keep growing. 

It is highly customizable and it transforms your complete data into dashboards and elastic tubes. You will come across a lot of statistical tools and features in this tool. You can create customizable dashboards for each team member in your company.

By maintaining and managing your data levels properly, the companies get leverage to compete in the global market and uphold their business intelligence principles.

2) Click tale – Track and View Data Insights the right way

To know how your business is doing online, you will have to trust web analytics tools such as Google analytics. But to give a tough competition to the Google Analytics itself, you have the Click tale that also provides an in-depth analysis of your website. This is becoming very popular amongst the businesses and website owners due to its amazing features.  

The Click tale tool also makes it easy for assisting business. This tool also offers you insights on behavioral analysis along with web analytics. It offers data optimized tools so that you can improve the inward flow of business. You can also check the path analytics of your website with this tool. With this platform, you can reach the required goals and formulate a good customer acquisition strategy.

3) SEMrush for Marketing Analytics

SEMRush is the right data analytics tool for examining your marketing strategies. They offer features which help you track KPIs and also the analysis of how your content or business is doing online. Also, this tool helps you analyze according to the search engine visibility of your website.

SEMRush is a one-stop shop for all your SEO and Digital Marketing Analytics. It also gives insights on keyword performance, backlinking data and other website analytics. With SEMRush, you can also review and track the performance of your competitor’s website and use that information to bid for keywords to improve your digital marketing efforts.

4) DataMelt Tool

Data Melt helps in power analytics. It comes to your rescue when there is a need for intense analysis. Also, if you are thinking this comes with a set of tools, then you are mistaken. You can customize it according to your will.

Also, you can use it for decoding fields like mathematics, financial marketing, engineering, and statistics. Also, it has a great number of tools and is available over 500 Python modules. DMelt or Data Melt is in various languages. This tool can also be applied for any kind of business analysis.

5) Kissmetrics for Predictive Business Analysis & Social Media Marketing

Kissmetrics is used especially for understanding the whole route of customer’s behavior. For a business to grow, there is a need for understanding what the customer wants. By studying his/her searches or predicting what he/she usually looks for, we need to strategize in a way that our product is reaching them and striking a right chord with them.

Also, Kissmetrics will be of huge help if you are making any digital marketing strategies. The tool, which was founded by the famous SEO strategist and Guru Neil Patel, offers an exclusive and holistic marketing analytics solutions for all business challenges. This tool also helps in engaging more customers.

The Kissmetrics tool easily integrates with your already existing analytics tools and also provides constructive criticism on the insights you drive. Also, you can execute smooth digital marketing initiatives with the help of its customer behavior- based automation features.

With these tools in hand, you can now do social media marketing in the right way. Thus, with such data analytics, it can help restructure your marketing approach and also attract more paying and prospective customers.

Conclusion

There are many factors for a business to flourish. You have to cater to your customers, their expectations, and in a similar way, you have to look at growing your sales funnel too.

If you are turning towards being a more data-driven organization, then understanding the data triggers of your business is crucial. Deploying or using any of the above tools will really put your company in high fame, or if you are looking for a custom-made data analytics tool for your business, then drop us a quick message here.

4 React Tutorials You Must Follow

Are you looking for reliable tutorials for learning React Native? You have just found the right resource library for learning React Native.  In this blog post, we will guide you on how to learn React Native app development smoothly. 

React Native: An overview

React Native is a mobile app development framework which can be used to build both Android and iOS apps. Facebook launched React Native as an open-source technology that is available to everyone’s disposal.

React Native is in demand for mobile app development as it allows one to build apps at a very fast pace with almost native performance. It provides a great extent of flexibility to the mobile app developers. With the flexibility React Native provides, you can pick any IDE/text editor for writing a React Native app. You can build some part of your app using native code and rest of the part with React Native app.

Isn’t that an awesome feature?

An added benefit is if you already know Javascript and React, then you will quickly be able to grasp the concepts of React Native and become a React Native developer in a very short span of time.

Still not sure why you should take the plunge and learn React Native?

Honestly, in today’s time, React Native is one the hottest technologies and is used by influential brands such as Facebook, Tesla, Instagram, Skype, Bloomberg, Walmart, Uber, and Pinterest, to name a few. If you are looking to grow in your software profession, then React is a skill worth investing in.

Here are some of the best React tutorials that will help you hone your skills:

1) React 16.6 – The Complete React Native Training

The course is comprehensive with around 33 hours of material with Maximilian as the instructor. He is a great instructor and explains every concept in-depth which makes this program very effective for beginners. This course comes with up to 160 downloadable external resources that can help students learn React development effectively.

Maximilian Schwarzmuller is a very proficient teacher who has taught over 200,000 students professionally. This course is offered on Udemy and has real-time practical projects to apply the course learnings.

Following are the key features of the course :

• It is a course for beginners and covers topics from basic to advanced level.
• Along with in-depth concepts of React, additional libraries used with React are also taught such as Redux.
• Prior Front-End framework is not necessary.
• Maximilian is one of the top instructors on Udemy, so that’s another plus.
• It is also suitable for developers who want to learn React development with intermediate to advanced level of experience.
• This course holds a considerable level of popularity among the beginners.

What will you learn in this course?

• The basic concepts of React like syntax and base features
• The ways to output lists and conditional content
• Redux: from Basics to Advanced level
• High-level component features of React
• Deployment of React Apps
• Introduction to Unit Testing
• Forms and Form validation in React
• Styling components
• Authentication using React

Find more details about the React course here.

2. Modern React with Redux

Modern React with Redux is created by Stephen Girder, an expert in React and builds front-end applications for top corporations. This course is a great choice for beginners who want to learn React development. It is hosted on Udemy and is rated 4.5 stars out of 5 stars and has about 39 hours of video lectures. This course is updated from time to time and is suited for both beginners as well as experienced professionals. This course focuses on design principles and enables students to get deep insights on how apps are designed using React.

Following are the key features of the course:

• Delivers the basic concepts of React
• Covers React’s custom markup language i.e. JSX
• Provides coding exercises to help you apply what you have learned
• You will learn about ES2015 syntax in the course
• Custom diagrams to gather a better understanding of React and Redux

What will you learn in this course?

• The basic understanding of React
• In-depth understanding of React at the source code level
• The way to build reusable components in React
• Varied techniques of deployment
• Varied methods to build UIs
• The knowledge of the in-demand  styling libraries
• How to integrate React with other APIs like Geolocation APIs?
• How to handle forms in Redux?
• Asynchronous actions with React and Redux.

Find more details about the Modern React with Redux course here

3. React.js: Getting Started

This course is hosted on Pluralsight with the instructor Sameer Buna who has an immense level of experience in web and mobile app development. This is a training course for beginners which starts with basics of React and advances to teach students how to build an in-browser interactive game with React.

Following are the key features of this course:

• The course focuses on the UI abstracted from DOM
• It instructs on how to use the one-way data flow of React
• Delivers intel on how to build an in-browser game which will provide experience for developing projects.
• Teaches how to put React components to use from a practical perspective.

What will you learn in this course?

• How to build an in-browser game
• How to use reusable components
• How to work with JSX and event handlers
• The way to use state properties of components
• How to work with real data using GitHub API
• How to take input from the user
• Communicating between different components
• To use React’s one-way data-flow
• How to manage the application state

Find more details about the React.js course here

4. Front-End Web Development with React

This course is hosted at Coursera by the Hong Kong University of Science and Technology with Jogesh Muppala as the instructor and is a part of Front-End development specialization. Though it’s a package, this course can be used to understand the basic concepts of React. No advanced level experience with front-end development using JavaScript and Bootstrap is necessary to be a student of this course.

Following are the key features of the course:

• You will get an understanding of the varied React features which include components and forms
• You will be introduced to Reactstrap for development with Bootstrap
• Advanced understanding of the Redux and the Flux architecture is delivered.
• Learn to use Fetch for client-server communication

What will you learn in this course?

• Flow architecture and introduction to Redux
• Client-Server communication
• React Routers and Single Page Applications
• How to design responsive applications using React and Bootstrap
• A quick tour to React animation
• Use Reactstrap for web design
• Combining reducers
• How to design the architecture for a React-Redux application
• Using the Fetch and REST API
• Testing and deploying React applications

For more details on front-end development with React, go here.

Parting thoughts

Never stop learning. Be an opportunist and make gold when the time is right. Today, the IT market is abundantly seeking for React professionals. Now is the time to scale your career and equip yourself with skills that recruiters are in need of. Give the above courses a spin. May the force be with you!

If you would like to join us as a React developer or want to build an application using React technologies, then go here

GoodWorkLabs is a key sponsor at STARup 2019

We are super happy and excited to announce that GoodWorkLabs is one of the key sponsors for the STARup 2019 event, India’s biggest and best networking summit.

GoodWorkLabs along with our CEO Vishwas Mudagal is partnering with STARup to bring out new talent in the startup zone.

Our CEO, Vishwas Mudagal is going to be speaking at the STARup event and his new book – The Last Avatar, book #1 of the Age of Kalki Trilogy will be unveiled at the event. The Last Avatar is an epic mix of Mythology and Science Fiction and is a modern take on the Kalki Avatar. Set in the future, the book consists of a universe of characters, secret societies, and powerful villains.

GoodWorkLabs is one of the community partners at the STARup event and the T20 awards. We are super excited to be sponsoring India’s biggest networking summit.

About the event:

STARup is a gathering of over 2,000 entrepreneurs, investors, corporate representatives, and government officials and influencers from the Indian, Asian and European startup ecosystems. It is the ultimate networking experience, ensuring you meet the right people, in the right business atmosphere through effective curation.

Event details:

Date: January 19th, Saturday

Time of Vishwas’s Session: 12.00 pm to 12.30 pm

Venue: Sardar Patel Technology Business Incubator,6 Dadabhai Nagar Rd, Old D N Nagar, Munshi Nagar, Andheri West, Mumbai, Maharashtra 400053

For more details of the event, go here

Image Scanning & Processing with Machine Learning models

One of our Fortune 500 clients in the logistics industry wanted to extract various product-related information by scanning images through a machine learning model. This scanned information had to then be supplied to a custom web application for further utilization and analysis.

The Objective

The image scanning and detection had to happen on the below aspects

• Identifying the object in the image
• Localization of the object
• Measuring the width and height of the objects in the image

The GoodWorkLabs Machine Learning Solution:

Our data scientists used the Faster-RCNN algorithm to solve the problem statement. We followed the below procedure to achieve the desired results.

• We ran the image through a CNN to get a Feature Map, a matrix representation of the image between a neural network layer
• We ran the activation map through a separate network called the Region Proposal Network(RPN), which identified the bounding boxes (interesting regions) for those objects. This output (regions) was then passed on to the next stage.
• Each and every output of the bounding boxes was analyzed and the most appropriate bounding box coordinates was accepted.

Faster-RCNN works quicker because we pass the activation map through a few more layers to find the bounding box (interesting regions). This forward pass continuously takes place and during this training phase, the ML model continues to learn. Errors (if any) are captured at this stage and with continuous learning, the model becomes efficient in predicting the classes and bounding box coordinates.

For calculating the height and width of each object we continued to iterate every object in the image and calculated values using OpenCV.

Image reference: https://arxiv.org/pdf/1506.01497.pdf

Data:

To perform this image scanning process, we had a well-annotated object in each of the images in the dataset. We had around 1000 labels for each object.

How did we train our ML Model:

• We downloaded pre-trained models and weights. The current code support is VGG16 
• We also got access to pre-trained models which were provided by pytorch-vgg 
• In the next step, we trained our model from fine-tuning to a pre-trained Faster R-CNN model. We followed this approach because a pre-trained Faster R-CNN contains a lot of good lower level features, which can be used generally.
• We trained the model for 150 epochs.

GPU utilization:

The models were then exported to Microsoft Azure’s GPU for better performance. The expected inference time for a given image is ~0.2 seconds.

Technology Stack:

The technology stack used to implement this image scanning ML model was Python, Pytorch, OpenCV, Microsoft Azure.

The GoodWorkLabs AI and ML solution:

Are you looking for a partner who can build advanced AI/ML technologies for your business and make every interaction of your business intelligent? You are at the right place.

We love data and we are problem solvers. Our expert team of data scientists dives deep into solving and automating complex business problems. From Automobile to Fintech, Logistics, Retail, and Healthcare, GoodWorkLabs can help you build a custom solution catered for your business.

Leave us a short message with your requirements.

High-performing Travel Recommendation Engine built with AI/ML models

One of our Fortune 500 clients had a community-based travel app that helped create trips for its users. Through this app, users could explore the community, take trips to nearby places, and also browse through their previous trips in the travel history.

Objective:

Our data scientists at GoodWorkLabs were entrusted with the task to make the above mentioned mobile app engaging, intelligent, and personalized. We had to create recommendation systems as an advanced feature by using Machine Learning models.

We realized that recommendations could be made to users based on nearby attractions, restaurants, hotels, etc. The nature of these recommendations had to be as below:

• Users will be recommended with places they would like to visit based on their previous travel history.
• Users will be recommended with nearby tourist attractions when they visit a particular place.
• Users will be recommended places based on their preferences and tastes.
• Users will also receive recommendations from similar travelers who share the same interests.

Recommendations by using Machine Learning models

To build an effective recommendation system, we trained the algorithm to analyze key data points as below:

• On-boarding information: To capture user data at the sign-up stage of the web application
• User profile: To suggest recommendations by analyzing data from the user’s previous visits on the profile 
• Popularity: To suggest recommendations based on user ratings that were collected in the form of reviews
• Like minds: To analyze data and match it against the likes of different users and populate recommendations accordingly.

App screens that populated ML recommendations

We programmed specific screens on the mobile app to display the recommendations. Below were the mobile screens on which ML recommendations were displayed:

1. Attractions
2. Trips
3. Restaurants
4. Nearby Cities
5. Ad-hoc Plans
6. Search (when users search for places to visit)

Types of Recommendation systems:

1. Content-Based recommendation

Based on the details keyed in by the user at the signup stage and in the whole travel process, the content based recommendation system analyzed each item and user profile. All this data was stored and the system was optimized for continuous and smart learning.

2. Collaborative filtering/ recommendation

In this recommendation system, the system looked for similar data inputs keyed in by different users. This was then continuously compared against other data. Whenever there was a match, the system recorded the instance and populated a set of recommendations that were common to that set. In this recommendation system, user interactions played an important role.

At GoodWorkLabs, we suggested a hybrid model of both the above-mentioned approaches for optimal performance of the recommendation system.

Tech Stack:

The tech stack we implemented in building these Machine Learning models were Python, Tensorflow, Sklearn, iOS CoreML, Elasticsearch.

The GoodWorkLabs AI and ML solution:

Are you looking for a partner who can build advanced AI/ML technologies for your business and make every interaction of your business intelligent? You are at the right place.

We love data and we are problem solvers. Our expert team of data scientists dives deep into solving and automating complex business problems. From Automobile to Fintech, Logistics, Retail, and Healthcare, GoodWorkLabs can help you build a custom solution catered for your business.

Leave us a short message with your requirements.

AI Racing Assistant to Enhance Driver Experience

One of our Fortune 500 clients in the automobile industry wanted to analyze and improve their racetrack experience. The racing car is equipped with more than 100 sensors and these were programmed to capture all activities of the car such as steering wheel angle, acceleration, engine running state, etc. 

The Objective:

The GoodWorkLabs AI team was given the task to identify the optimal path of the vehicle by analyzing the complete racing track with other tracks and also the overall racing experience.

AI/ML Implementation & Solutions:

We first analyzed the track using sensor data and then implemented state-of-the-art Deep Q-learning with Tensorflow.

Our Deep Q Neural Network took a stack of n frames as input. These pass through the network, and output a vector of Q-values for each action possible in the given state. We then take the biggest Q-value of this vector to find our best action.

In the beginning, the agent does not perform well. But with time and continuous learning, it began to associate frames (states) with best actions. Pre-processing was a very important step as we wanted to reduce the complexity of our states and reduce the computation time needed for training.

For that to happen, we greyscale each of our states. Color does not add important information (in our case, we just had to find the optimal path). This is an important saving since we reduced our three color channels (RGB) to 1 (greyscale).

Tech Stack: 

The tech stack used to develop this model was Python, PyTorch.

Below are some visualizations of the optimal path identified by our AI model.

The GoodWorkLabs Artificial Intelligence and Machine Learning solution:

Are you looking for a partner who can build advanced AI/ML technologies for your business and make every interaction of your business intelligent? You are at the right place.

We love data and we are problem solvers. Our expert team of data scientists dives deep into solving and automating complex business problems. From Automobile to Fintech, Logistics, Retail, and Healthcare, GoodWorkLabs can help you build a customized solution to cater to your business.

Leave us a short message with your requirements.

Artificial Intelligence in Investment Banking

Despite deep roots of origin, Capital Markets have evolved with the help of technology and still holds an appetite for innovation and improvement. Capital market firms such as investment bankers have been testing AI for implementation since the precursor technologies.

Before AI got some mainstream attention in the form of self-driving cars and robots, capital market firms have been leveraging machines for their daily operations such as algorithmic trading, quantitative analysis, and market predictions. These facts show how forward the capital market is in the tech race by capitalizing on emerging ideas and leveraging them for value generation for clients.

Though most firms use AI for becoming cost efficient, the potential of AI in the capital markets is beyond imagination and can create value across the organization.

What makes AI stand out from other technologies

Below are the features that make artificial intelligence a desired technology for businesses today.

1) Sense: AI can collect, recognize, sort, and analyze structured and unstructured data in the form of text, audio, and images.

2) Comprehend: Artificial intelligence can then derive meaning, knowledge, or insights by using that data.

3) Act: The comprehension gained is later used to perform a defined process, function or activity.

4) Learn: AI takes real-world experiences into account and evolves over time, thus enabling it to resemble a human brain and handles multiple tasks at once.

High-degree of customized AI interactions.

With hyper-personalization, curation of real-time information, and conversational interfaces, AI delivers enhanced interaction in the form of superior experience to clients. The advent of AI made it possible to cater to a high degree of customization in a cost-effective manner along with flexibility. AI analyzes the clients’ behavior and provides information instantly.

Currently, capital market firms are after storing, categorizing, and analyzing sales and trading conversations to better forecast client needs and enhance the effectiveness of interactions. This is achieved by the introduction of digital assistants handling the sales and services interactions.

Digital assistants are a cost-effective way to deliver a sophisticated and improved experience to the users. It eliminates the need to fill forms, navigate online portals, and the need for additional human resources. The involvement of digital assistants can also greatly improve the client’s acquisition and retention rate.

Intelligent products

AI can help you move up the value chain, access new ecosystems, and introduce innovations in the market faster than ever. AI enables the monetization of new services and products and also makes existing service offerings profitable in new geographical markets.

Enhanced trust

With AI at disposal, trust is enhanced in terms of governance. Compliance, risk, finance, legal and audit are necessary for vigilant oversight. AI provides a cost-effective approach to governance with important insights.

Transparency and traceability should be on top priority for capital market firms who are thinking of building and using AI solutions. Also, most capital market firms that are currently using AI are focusing on automating things that they currently do. But the real value lies when the scope of AI is used to enhance human judgment, to expand products and services, to improve client interactions, and to build trust and confidence among the stakeholders.

Potential of AI in capital markets

The massive potential that AI holds can be encashed in risk management, stress testing, conversational user interface, and algorithmic trading. Also, in recent times, the attention has shifted to client service in the form of next-best-offer and next-best-action decision making.

1) Intelligent automation:

The advancement in technology has made the layering of cognitive capabilities on automation technologies possible, thus enabling self-learning and increasing autonomy.

2) Enhanced interaction:

Curation of real-time information, hyper-personalization, and conversational interfaces have enabled the delivery of superior client experiences.

3) Intelligent products:

New products and services can be launched with the aid of AI along with tapping into new business markets and business models.

4) Enhanced judgment:

Human intelligence can be augmented with AI capabilities and decision making can also be improved.

5) Enhanced trust:

With AI, the whole organization can be kept intact and trust can be flourished outside the organization in how AI is used.

The future belongs to AI

Now is the time when the value of AI should be understood by capital market firms in order to build a base camp for it to flourish now and in the times to come. AI has more potential than just achieving efficiency in the daily tasks and cost-cutting.

The real question is, how you choose to deploy it? 

Fuel your AI engine by redefining your ecosystem and distinctly identifying your source data, internal as well as external. Datasets have a major role to play in the AI world, so be vigilant about which data can be shared and can be monetized.

Set guidelines for your AI

Capital markets out of the many industry lines are the most regulated. As the application of AI will grow in this industry, a new set of regulations will be imposed. With all these constraints, how you choose to use technology and adhere to the regulations will always be a point of discussion. Strong guidelines will help you in the long run. Guidelines that define your data use ethics, information sharing policies, maintain transparency, and privacy.

Final Words

AI is all set to help you improve your business practices and augment your forthcoming ventures. Capital market firms are still in the pipeline to understand the complete worth of AI and all that is at stake. With well-defined guidelines and an appropriate dataset, AI can yield constant and better results on an auto mode. The future is full possibilities and the present is in your hands. Now, it is your call how you choose to direct your future!

Let’s connect to discuss further on how AI can add great value to your business process. Drop us a quick message with your requirements and we will be happy to get on a quick AI consultation call.