What Role Does E-Commerce Play in the Post-Pandemic Retail Future?
Today’s retail data is exploding at a tremendous speed. Retailers are relying on data analysis, to turn insights into profitable margins by developing data-driven plans. Owing to the growing volume of data, data scientists are higher in demand.
Some employees working in the e-commerce and retail industries are quite dissatisfied with their jobs. And wish to shift their profession without changing their domain. If you’re one of them, then you’re in the right place. If you love working with data and have some technical abilities, then Data science can be the ideal choice for your career.
In this article, we will look at the impact of Data Science and Artificial Intelligence in the retail and e-commerce industry, the challenges that come while implementing it, career scopes, and how you can get started as a data science professional in the same.
_People are still changing how they shop in early 2021, according to a survey from EY, which has been polling customers since the epidemic started. That’s about 80% of the people Digital Library. 60 percent of people no longer go to stores in person, and 43 percent are shopping more online for things they would have bought in stores before the pandemic. In Covid-19, many people don’t care where they are as long as they can connect to the web. People spent about $10 billion on e-commerce investments, acquisitions, and partnerships from May to Jul 2020 (by Kathy Gramling). This is about how much money they spent. A lot of money was spent on logistics to make last-mile options like ghost kitchens and shadow storefronts possible. There was also a lot of money spent on AI and blockchain to make more things. Let us discuss data science in e-commerce, retail, and supply chain domain.
But do you know even after such massive demand so many retail and e-comm employees are losing their jobs?
On the other hand, there is also an intelligent community of professionals to reach the top of success. And you can also be a part of that community. _To know how, please continue reading this blog.
The final mile is crucial to e-commerce success: 21% said they would not forgive stores and brands if service was delayed because of Covid-19. It’s getting harder and harder for businesses to get last-mile delivery capacity because more people are shopping online. After Black Friday in 2020, many of us had to wait weeks for things to show up on our doorsteps. Delivery is now an important part of the whole experience. As a fulfillment center, the shop is used a lot. According to the Index, 37% of US customers plan to purchase online and pick up in-store more often in the future (online library). While using a shop as a fulfillment center may be a good idea, it needs systems and business divisions to work together to make the promise come true. Retailers’ ability to create a consistent experience must expand as services grow.
Retailers need to be ready to build better, deeper relationships with their customers, both online and in-person, no matter how people act.
For Retailers
- Emerging Markets Will Be Critical
In the future of eCommerce, India, China, Brazil, Russia, and South Africa are projected to play a key role. This may not be a surprise, but let’s look a little deeper into this. By 2022, it is expected that about 3 billion people from developing countries will be able to use the internet. That’s a lot of people who could be customers. There’s also a good chance that people who already live in these areas will make up 20% of total retail sales in 2022. A lot of people could buy this.
- The Online vs. Physical Debate
It’s not possible to talk about the future of e-commerce without talking about the conflict between physical and online shopping. In the long run, people buy things online more than they buy things in stores. It doesn’t mean that physical stores aren’t very important for internet businesses at all. People think brick-and-mortar stores aren’t as important anymore because they don’t have as many things as their online businesses, which usually have a lot more. Take a look at Nike, which has already opened stores in both New York and Shanghai. They’re called “Houses of Innovation,” or “Experiential Shops.” Overall, we believe that unique experiences will be the future of physical retail sites. These are once-in-a-lifetime events that cannot be duplicated.
For Marketers, the Future of Ecommerce
- The importance of device use will increase.
If you want to buy something from an e-commerce site, you usually have to use a computer to do it. It’s now on the other side. If you work for an eCommerce Data Science company, you have to make your website for mobile users before you make it for people who use their computers. This may seem to be an unusual shift, but it makes sense, particularly when you realize that 45 percent of all commerce choices were made on mobile devices last year. For comparison, it translates to $284 billion in sales. Buyers now want a seamless purchasing experience across all devices.
- Video is becoming more popular.
In the future, the video will play a big role in e-commerce. E-commerce businesses will need to improve their videography skills. Research says that 60% of people would rather watch a video about a product than read about it in a text. After watching a brand’s social videos, 64% of people buy something. Facebook, Instagram, and Snapchat may be to blame for these changes in buying habits. All of these apps have made changes that make video content more important.
How is data science affecting the retail industry?
Data science is changing how people shop and how businesses order and ship things, say some retailers who are going in a different direction. Businesses can buy and ship things more cheaply because they don’t have to pay a lot for them. A lot of people have better experiences because of it. In the future, some algorithms can help retailers learn more about their customers and figure out how many people will buy in the future, too. It all helps the bottom line.
A Data Scientist’s Role in the Retail Industry
Every year, the number, diversity, and usefulness of retail data increase dramatically. When retailers make decisions based on data, they use data science to make money. This is how businesses are using data science in retail to stay competitive, improve customer service, and make more money and sales. And, as technology advances, data science in the retail business will have much more to give!
What Role Does Data Science Play in eCommerce?
- Customer Lifetime Value:
It is a prediction of how much money a single customer will make for a company over time. It is based on what the shopper has bought and done on a certain eCommerce site in the past.
- Customer service has improved:
Customer service is crucial for every eCommerce company owner. Business owners can use data science to make their websites better by getting feedback from people who use them and giving them stars and reviews. To figure out why people didn’t like them in the first place, you can sort them and do a Sentiment Analysis to figure out how they felt. E-commerce businesses can quickly look through all of the reviews and focus on improving and increasing customer happiness, with the issues raised by angry customers getting the most attention. This makes it easy for businesses.
- Predictive Analytics:
If you run an eCommerce site, you need to be able to figure out what people want before they do. This means that each person who goes to the site does things differently. They also have different preferences. Use Predictive Analytics to see everything about how customers use the site and what they buy. This makes it easier for them to make decisions. Consequently, Data Science e-commerce businesses may be able to better serve their customers and set a price range for their items.
The benefits of using and analyzing data science in eCommerce are endless, and understanding how customers use and interact with your website is critical to your success, so don’t forget to use it. If you want better customer service and a more personalized experience, you’ll need to get more information from people. You can also make more money, improve the prices of your products, and decide where to open a new store.
Data Scientists Who specialize in Supply Chain Data
This means that more and more businesses see the benefits of using data science to manage their supply chains. This means that there is a growing need for data scientists who are qualified. Companies are paying data scientists a lot of money because there is a lot of demand for their services. It says that data scientists in the United States make an average of between $105,750 and $180,250 per year. Earnings are affected by factors like where you live, how much experience you have, and what kind of business you work in. According to statistics from other organizations, supply chain data scientists make an average of $82,100 per year, with some making as much as $156,000.
Supply Chain Management Using Data Science
- Overall, this is a great time for supply chain experts and data scientists to work on important academic research and come up with ideas and solutions that will have a long-term impact on the world.
- Employers are looking for skilled data scientists who can apply their knowledge to the problems their companies are having with their supply chains, as well as to academic research in the field.
- One of the best ways to get the skills you need to become a data scientist or start a new job is to get more education, like Learnbay’s data science course.
- Students learn how to process, model, evaluate, and draw conclusions from data through these programs, which will help them when they start their businesses in the future.
What do Supply Chain Data Scientists get paid?
People who work in Supply Chain data sciencemake on average 14.3 lakhs a year, according to the 56 profiles. They make between 5.0 lakhs and 28.2 lakhs per year. Those in the top 10% earn more than £18.4 lakhs a year.
Why are Data Scientists getting paid at a higher level?
Image Source: Supply Chain 24/7
Packages and Companies:
- Amazon: Rs 5 lakh to Rs 45.57 lakh | Rs 15.56 lakh (average)
- Flipkart: Rs 14.5 lakh to Rs 42 lakh | Rs 24.2 lakh (average)
- Walmart: Rs 14.5 lakh to Rs 33.5 lakh | Rs 24.6 lakh (average)
- IBM: Rs 1 lakh to Rs 44.62 lakh | Rs 10.91 lakh (average)
- Deloitte: Rs 5.52 lakh to Rs 27 lakh | Rs 12.41 lakh (average)
What Qualifications/Skills do you need to work as a Supply Chain Data Scientist?
- A bachelor’s degree in engineering, computer science, applied math, statistics, or a quantitative field is needed to work in this field. It is better if you have a master’s or certified degree than not.
- A minimum of three to five years of experience using Data Science, Machine Learning, or AI to solve Supply Chain or Manufacturing problems is needed.
- Supply Chain, Manufacturing, Warehousing, Distribution, and Logistics domain knowledge and familiarity.
- Python experience creating and implementing Machine Learning and artificial intelligence algorithms.
- Common statistical and Data Science packages and libraries as well as optimization tools are well known to him.
- Advanced statistical methods and ideas are needed to do this (regression, decision trees, ensemble models, time series, forecasting, neural networks, network routing, linear programming, and optimization).
- Expertise in SQL and experience with relational and non-relational databases, SQL query writing tools, and SQL debugging skills are needed.
- Ability to operate in a fast-paced, quickly growing start-up environment.
What Are The Responsibilities of a Data Scientist in the Supply Chain?
- To solve problems in Supply Chain, Manufacturing, Inventory Management, and Distribution, design, build and test Machine Learning models and algorithms.
- Build features and functionality for ThroughPut’s ELI Flow platform with help from Product and Engineering.
- Collaborate with Dev Ops and Quality Assurance to put models into a production environment that can grow with the business.
- Participate in client-facing Sales Engineering conversations and help with data-related analysis and troubleshooting.
- People who work in data science, Machine Learning, artificial intelligence, and supply chain management should stay up to date on the most recent tools and methods. They should also come up with new, unique solutions.
Data Science in E-commerce Retail and Supply Chain Domain
You may be wondering how Learnbay can help you with specializations like retail, eCommerce, and supply chain domains after reading all of the above.
It’s all about domain specializations at Learnbay, and one of them is Retail, Ecommerce, and Supply Chain.
Let’s take a look at what you’ll receive if you study with Learnbay:
Learnbay is noted for its wide range of data scientific subjects. This is why it offers some of the top data science courses in Bangalore. But the best thing about it is that it has hybrid learning and IBM-approved courses, so you can take lessons both online and offline.
So, let’s have a look at what Learnbay’s Supply Chain domain has to offer.
- This class is an option. It teaches students how to look at data and draw important conclusions that could help businesses get a better edge in the market.
- There are many examples of the RSCA process. Sentiment Analysis is one of them. Google Analytics is another. Natural Language Processing, Recommendation Systems, Deep Learning Concepts, and Text Analysis are also examples. Operations Research is used in supply chain management in a separate class.
- The Supply Chain Operation Reference (SCOR) framework also has models and metrics like ROE, ROA, APT, INVT, and PPET. These models and metrics are part of the framework, as well.
- Simulators and time series forecasting are also important in supply chain management, and the people who come to the meeting will like that.
- The purpose of this E-Commerce, Retail, and Supply Chain curriculum is to introduce participants to the fundamentals, components, business models, and other aspects of running an electronic commerce firm.
- You will have a better grasp of the issue than anybody else in your firm if you have domain expertise.
- Learn the finest practices in your respective professions and become well-versed in them. Be mindful of potential problems that you and your firm may face in the future. Most importantly, a well-known Domain Specialist increases the market value of a firm.
Projects in the Retail, eCommerce, and Supply Chain Domain in which you will be working:
Retail Domain
- Usage-based warranty analytics: Next, after you figure out how many items you need, it’s important to figure out the right reorder level. This will make sure that production doesn’t stop because there aren’t enough items in stock and that working capital doesn’t run out because of inaccurate orders.
- Customer Sentiment Analysis: It is the most important part of sentiment analysis to look at data from inside a text to get a sense of the point of view and other important characteristics, like modality and mood.
- Optimization of the price: The optimization methods have a big advantage when it comes to finding the best price for both the customer and the retailer.
E-Commerce Domain
- Fraud Detection: Fraud in the e-commerce business is one of the most difficult to find because it can cost a lot of money.
- Recommendation System: This technology aids firms in anticipating customer behavior.
Dataset for eCommerce Customers
Image Source: Kaggle Dataset
Supply Chain Domain
- Algorithm for routing the transportation network: This is because shipping costs have gone up recently because there aren’t enough containers to go around. Container loading optimization is now very important.
- Identification of the Reorder Level: Next, after you figure out how many items you need, it’s important to figure out the right reorder level. This will make sure that production doesn’t stop because there aren’t enough items in stock and that working capital doesn’t run out because of inaccurate orders.
- Planning a network: To have a strong supply chain and a profitable business, you need to make sure that all of your inventory and production facilities are properly connected.
Conclusion
Now that we’re done with the article on data science in e-commerce, retail, and supply chain domain, I hope it has helped you understand how important it is to know your field. Another point we wanted to emphasize was the possibility of this in the future, as well as in the present. Take a look at theData Science & AI Certification| Domain Specialization For Professionals course to learn more about the Data Science course or visit Learnbay’s Facebook, Youtube, Linkedin, Twitter. accounts for updates.
Bibliography
https://spyro-soft.com/blog/the-future-of-e-commerce
https://www.mygreatlearning.com/blog/applications-of-data-science-in-e-commerce-industry/
https://www.northeastern.edu/graduate/blog/data-science-supply-chain-management/
https://analyticsindiamag.com/8-companies-offering-the-highest-salaries-to-data-scientists-in-india/
