Big Data: Making It “BIG” For E-Commerce Trends
We know there is a lot of internet buzz and social hype regarding the future of Big Data in E-commerce, but what exactly is it?
So, before analyzing the E-commerce trends for 2019, firstly let’s take a look at the five important things you should be knowing about Big Data.
1. What Is It?
Simply put, Big Data refers to large data sets that are computationally reviewed to reveal patterns and trends relevant to a certain aspect of the data. There is no minimum amount of data required for it to be categorized as Big Data, as long as there are enough hooks for solid conclusions.
Have a better understanding of different facets of the Big Data through 8V’s:
2. How To Access Big Data?
Big Data is available in a never-ending number of places and is showing no sign of stopping. Nowadays, a simple Google search enables you to find a data repository for just about everything. Many of us are not aware of how much data is already available for access and analysis.
But, if you want to try your hands, there are following six ways you can use Big Data In E-commerce and access this data:
Before anything happens, minimum data is needed. This can be achieved in a number of ways, but usually through an API call to a company’s web service.
The biggest challenge with managing Big Data is “How to Sort It”?
It will solely depend upon the budget and expertise of the individual responsible for setting up the data storage as most providers need some coding knowledge to implement. A reliable provider should always allow you a safe, straight-forward place to store and query your data.
Like it or not, data sets come in various shapes and sizes. Before you can whim about how to store data, make sure the data is in a clean and acceptable format.
Have you heard about “Data Mining”?
“NO”? Don’t worry I got you covered. Data Mining is the process of discovering insights within a database. The objective of this is to surmise and make decisions based on the data currency held.
After all the data has been collected, it needs to be analyzed to look for some interesting patterns and trends. A good data analyst will find something out of the ordinary or something that’s not yet reported by any other analyst.
Possibly, data visualization is the imperative of Big Data. This is the part that ensures all the work is done prior and outcome is a visualization that ideally everyone can understand.
This can be done with programming languages like d3.js, Plot.ly, or software such as Tableau.
3. Is It A Growing Industry?
With the mounting access to Big Data, the rising volume in Big Data for e-commerce market and careers is no more a surprise element.
As per statista, the global big data and business analytics market is predicted to grow 103 Billion U.S dollars by 2027, literally more than double the market valued in 2018 with a compound all around growth rate of 13.2%.
In addition, with a share of 45%, the software segment would become the large big data market segment by 2027, opening a huge number of opportunities in the field.
4. What’s The Market Value Related To Big Data?
You must be thinking is there any market value related with Big Data?
In short, the answer is “Yes”. The general access and interest in the big data is on the rise. The Google trend chart shows the increase in the popularity of the search term for the “Big Data” between 2004 and the present day.
5. What Are The Big Data Applications?
There are some of the following domains where Big Data Applications has been revolutionizing the conventions:
- Driver-less Cars: Google’s driverless car collects about one Gigabyte of data per second. These experiments require more and more data for their successful execution.
- Entertainment: Amazon and Netflix is an example utilizing Big Data to make show and movies recommendation for their users.
- Education: Aligning with Big Data powered technology as a learning tool instead of a traditional lecture approach has enabled the learning of the students as well as help the teachers to keep a track of their performance.
- E-commerce Market: Big Data technology has made a path in the E-commerce market as well. As now, it is a part of small and big E-commerce seller’s business processes, enabling them to achieve their goals more efficiently and quickly.
While there are heaps of benefit in adopting Big Data technology, there are some demurs too. Let’s look at some of the hurdles that E-commerce is facing on the path of adoption.
- Velocity: Managing data as it comes at an unprecedented speed is an alarming concern for e-commerce sellers. Rapid analysis and on-time actions are crucial to tap its full benefits.
- Volume: As the name suggests, Big Data integration includes the collection of huge volumes of relevant data from myriad sources. E-commerce sellers get statistics related to customer behavior, social media, demographics, and many more on the list.
The challenge is not about collecting the data rather analyzing and utilizing it appropriately.
- Complexity: It can be difficult to associate, match, correlate, and interpret data that pour in from different sources.
- Variety: Big Data comes in different forms, from the traditional unstructured numeric database to structured documents, videos, texts, emails and more. Re-sellers needs to pay attention to make the right business decision and allow for possible data inconsistencies such as seasonal and peak loads.
Daunting as the journey may seem, there is a light at the end of the tunnel. And, after overcoming the challenges and using Big Data in E-commerce to their advantage, the re-sellers can achieve phenomenal success.
E-commerce giants like Souq (The New Amazon) have invested a behemoth amount in technology to create a more personalized user experience. Big Data analytics in E-commerce has emerged as a boon for such retailers in many distinctive ways:
1. Demand Predictions
Demand forecast has become crucial than ever before, and the reasons are obvious.
Inconstancy in demand and supply have become more frequent.
Inventory stocking has always been a demur for E-commerce players. They under-stock and miss out on an opportunity of selling. They over-stock and risk not being to sell them all.
So, how does Big Data act as a Savior here?
E-commerce re-sellers use predictive analytics to analyze all historical sales data, seasonal fluctuations, other trends. They include all factors that can leave an impression on demand, such as holiday, festivals, climatic changes, political trends, fashion fads, etc. And obviously, forecast demands.
Let’s take an example for the winter season, if winters are expected around the corner, the customer will rush to buy their winter accessories at the earliest. If an online seller has considered the weather forecast, he can earn more profit by selling more winter wear and gain an edge over his competitors.
As an add-on, retailers can track the traffic on their website with real-time and forecast the conversion rate at any instant.
Yes, it can predict trends too. It can analyze what’s buzzing on the internet and social media channels. The data scientist can analyze online ads to look at what other companies are trying to market.
They can review feedbacks on a product on the internet and see whether they are positive, neutral, or negative. Accordingly, they can predict if the demand for a particular product will rise, fall, or stay constant.
For example, a cosmetic firm launches a product like fairness cream in the market. The retailers employ data scientists to carry an exclusive analysis of the reviews for the product on different social platforms and find out if they are positive, negative, or neutral.
2. Personalized User Experience
As you know, the E-commerce space is fiercely competitive. This competition gives birth to the need for creating a highly personalized shopping experience for their customers.
In fact, 87% of shoppers believe they are driven to shop more when online stores personalize their shopping experience.
Still, have some doubts about how personalized shopping experience works, let us understand through the following example.
- A shopper went to an e-commerce site, adds a pair of shoes and a jean to his shopping cart. He, however, does not complete the transaction and abandons the cart due to some reason. He is a regular customer of the site and purchases from this site frequently, so the system understands that the customer is valuable.
Now, the system reacts immediately and offers him a discount coupon on the purchase of the jean and prompts him to complete the transaction.
Even, if the user leaves the site, he will be able to see ads regarding his purchase or search history on other webpages.
3. “Play For Keep” Pricing
Dynamic pricing is a new way to attract customers by offering products at more flexible values. Many prominent E-commerce retailers are now practicing dynamic pricing.
Flexible pricing benefits E-commerce sites in different ways:
- They gain an edge over their competitors.
- They can earn high revenue without losing out on profit margins.
- They can revert faster to fluctuations in demand and supply situation.
- They can easily manage their pricing models.
- They provide a more personalized user experience.
Dynamic pricing when accompanied by machine learning algorithms, consider several elements to optimize price for a product in real-time. Some key variables are as follow:
- Customer Data: behavior data, device data, and location data.
- Prices offered by competitors.
- Demand for the product.
- Product supply.
- Profit margins.
- Time of the day.
Souq (The New Amazon) has been the pioneer in the dynamic pricing dimensions. It reportedly changes it’s product price 2.5 Million times a day which means the price of any product changes after every 10 minutes.
4. Skyrocketed Customer Service
Far from providing a personalized experience, Big Data Analytics aids E-commerce re-sellers keep a track and analyze customer feedback across all channels.
They receive customer feedbacks through different mediums like feedback surveys, SMS, call transcripts, and chats. They can evaluate the feedbacks through analytic algorithms to gain a comprehensive view for customer sentiment and improvise accordingly.
For instance, if an e-commerce brand finds that many of its customers are adding products to their shopping cart but are not checking out, the brand can scrutinize the data collated via different feedback channels to find the loophole behind their doing so.
E-commerce is booming and revolves around building a better user experience. All thanks to the advancement in Big Data technology, E-commerce retailers can now track figures in real-time, predict trends, forecast demand and create a highly personalized customer experience.
At this stage, if you also want to increase your service and manifold your profit, all you need is the right web development company. Given the ease with which e-commerce is operating now, hire a web developer now and don’t let the coming decades sharp decline in traditional brick-and-mortar stores have an impact on your business.
