How data analytics can help grow your business APRIL 06, 202213 MIN READ
How data analytics can help grow your business

In this article, we will discuss all things about data. What data analytics is, the importance of having a data strategy, and how data analytics can help grow your e-commerce business.

We will also review some inspiring companies that have been revolutionized by being data-driven.

Let’s start by discussing what data analytics is for a business.

What is data analytics for business?

Businesses may use data to better understand their customers, optimize their advertising efforts, tailor their content, and boost their profits. The benefits of data are numerous, but these cannot be accessed without the right data analytics tools and methods. While raw data holds a lot of information, data analytics can help analyze that data, turning it into information that can grow your business.

The phrase "data analytics" refers to the process of analyzing datasets in order to derive conclusions from the information contained within them. Data analytic techniques allow you to take raw data and extract important insights by uncovering patterns within the data.1

Nowadays, many data analytics approaches rely on specialized systems and software that combine machine learning algorithms, automation, and other features.

In data science research, data analysts apply a variety of data analytics methodologies to extract useful information, which is then used by companies to guide their judgments. Data analyses may assist businesses in better understanding their clients, evaluating their advertising efforts, personalizing content, developing content strategies, developing new products, and more.

For businesses, the data utilized can be composed of historical data or new information gathered for a specific project. Companies may also collect it directly from their customers and site visitors, or acquire it from other businesses. The data collected by a corporation on its own customers is referred to as first-party data; data obtained from a recognized data collection entity is referred to as second-party data, and aggregated data purchased from a marketplace is referred to as third-party data. The data a company uses can include an audience's demographics, interests, and actions, among other things.

However, successful data analytics operations entail a lot more than the collection of data and decision-making based on probable insights. An overarching data strategy is a key component of any successful analytical effort.

Data Analytics

What is a data analytics strategy for business?

A data strategy encompasses and directs several aspects of data inside a company, including how information is collected, stored, used, and maintained. A strong data analytics strategy will guarantee that incoming data is of high quality, that it is uniform, and that it provides an overall view of operational and commercial strategy and execution without adding silos or bias. Businesses can guarantee that their analytics are dependable and relevant by delivering value across the whole data process with a successful strategy.

Whether an established business or a new startup with a great business idea, if an organization is looking to test products in an international market and expand their business, they should use data analytics and market opportunity analysis tools to make informed, strategic decisions. In terms of international trade, this is crucial.

Let’s take a look at some inspiring companies that have been revolutionized by data analytics.

Which companies have been revolutionized by data analytics?

Companies are increasingly depending on the power of data to make game-changing decisions — from tackling evolving customers' needs to introducing new innovative products.

According to IDC (International Data Corporation), companies spent over $60.7 billion on big data and analytics software in 2018, and these trends are projected to continue despite the current climate of global lockdowns due to the pandemic.2

Effective data use goes beyond simply choosing a solid business intelligence solution; it’s also about enterprises developing a data-driven culture as a whole. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data-driven decisions that will drive your business forward.

Let’s look at some examples of inspiring companies who have used data analytics to their benefit.

1. Netflix

Netflix wisely used the power of data to conduct predictive analytics to determine what its viewers would be interested in watching. By analyzing over 30 million daily “plays,” as well as over 4 million subscriber ratings and 3 million searches, they were able to make successful bets on producing widely-acclaimed hits such as “House of Cards” and “Arrested Development.”2

2. Google

Employees are the backbone of any company, and maintaining their morale is critical to the company's ability to thrive, expand, and innovate — especially in a world where remote working is becoming the norm.

Organizations will be able to better understand their workforce, manage their talent pipeline more efficiently, and retain high-performing personnel using data analytics.

To better understand how to “build a better boss,” Google's people analytics teams looked deep into their data and evaluated employee performance reports and feedback surveys, among other data sources. This assisted in the creation of a list of data-driven insights into what workers valued, and led to an improvement of 75% in the management quality of their lowest-performing managers.2

3. Coca-Cola

Digital ads cost more than $283 billion in 2018, and this amount is expected to rise to $517 billion by 2023. However, according to a survey carried out by Rakuten, marketers spent roughly 26% of their marketing expenditure on the wrong strategies or channels.2

Using data and analytics, marketing teams will be able to provide the correct advertising to the right audience, helping companies to maximize their ad campaign’s ROI. Coca-Cola, for example, has over 105 million Facebook followers and 2.7 million Instagram followers, they, therefore, have a wealth of data to examine, ranging from brand mentions to photos shared by fans.2

Coca-Cola smartly uses data analytics and image recognition technology to target customers based on the photographs they publish on social media, providing them with insights into the people who are consuming their drinks, where they are from, and how (and why) their brand is being mentioned.

When compared to other forms of targeted advertising, the personalized ads served in this manner had a 4x higher click-through rate.

How can data analytics help your e-commerce business?

Data Analytics

Now that you know what data analytics is, it is important to establish why it matters. Analytics are critical because they enable you to make more informed decisions that generate the best possible results for your e-commerce business. To illustrate this effect, we are going to take a look at some of the main benefits of data analytics for B2B e-commerce in further depth.

1. Mitigating risk & fraud

In business, there are risks everywhere. Customer or employee theft, uncollected receivables, staff safety, and legal responsibility are just a few of them. Data analytics can help an organization in identifying risks and finding the right preventative steps.

2. Enhance security

Internal and external threats can lead to the misuse of all physical, financial, and intellectual assets, which is why security and fraud analytics are important. Different deterrent methods involve procedures that allow firms to swiftly recognize potentially fraudulent behavior and predict future activity, as well as identify and trace perpetrators.

3. Streamline operations

Poor operations management can and will result in a myriad of costly challenges, including a considerable risk of negatively impacting customer experience and, as a result, brand loyalty. Using analytics to design, regulate, and streamline company operations in the creation of products or services leads to enhanced efficiency and effectiveness in meeting customer expectations and achieving operational excellence.

4. Personalization & service

Companies are still battling with quantitative data, such as Excel files or SQL databases. This is something they must be particularly responsive to in order to deal with the volatility caused by today's clients who interact with digital technology. Advanced analytics is the only way to respond in real-time, which is essential to making the customer feel personally appreciated. Big data allows for interactions to be tailored to the customer's personality by predicting their opinions and taking into account various aspects, such as real-time location, to help deliver personalization in a multi-channel service environment.

Whether you have a wholesale e-commerce business or another business type, the above benefits should give you some insight into the importance of data analytics and how it can help your business.

How to implement data analytics for your business

You want to leverage data and business analytics to uncover meaningful insights that will help your company grow, but you can't just throw data into a business intelligence platform and expect it to work. Following best practices ensures you're making intelligent, data-driven business decisions, whether you're analyzing customer data to improve marketing segmentation and capital allocation, gathering data from disparate sources and programs to create predictive models, or sorting through cyber security data to make your infrastructure more secure. Let's look at how to implement data analytics for your business.

1. Decide on key metrics

As a business analyst, it's critical to decide on the metrics that are relevant to your organization before starting a business intelligence project. Conversion rates and customer spending data, for example, are important factors to consider when reviewing advertising and customer data to discover your best customer acquisition data. Irrelevant business data should be removed from visualizations to allow executives to focus on essential indicators when making choices that might influence the direction of a division or organization. Consider the following questions when deciding which indicators to prioritize:

      • What is the ultimate goal of the information gathered?
      • How would this data assist me in achieving my business objectives?
      • Am I data mining or using predictive analysis?

2. Avoid common data modeling mistakes

If you want to get useful insights from all the data you've collected, you'll need a technique to model the data appropriately. This means avoiding frequent errors, such as disregarding small data sources, neglecting to account for how calculated fields may influence your model, and using sloppy naming conventions. If you don't account for these potential errors, you might wind up with data models that are costly and unclear.

Take the time to outline your analytics goals, especially if you're combining data from many sources. It will be much simpler to model complicated data if you ensure computed fields are consistent, create suitable dimensional hierarchies that allow users to drill down into the data, and follow other data modeling best practices.

3. Create correct dashboards

For non-technical users, data visualization is at the heart of how we engage with data. Choosing visuals that demonstrate the link between the highlighted material and the broader context, as well as ensuring that key stakeholders can comprehend the essential points with a single glance, can go a long way toward enhancing your dashboard design.

Displaying complex analytics is a demanding task that requires decisions on the hierarchy of the collected information, dashboard design, and other factors. Your visuals will be more relevant, logically structured, and streamlined as a result of proper planning, meaning that your users will not feel overwhelmed.

4. Choose the correct tool

There are several alternatives to consider when assessing business intelligence tools. On the surface, they may appear to be identical in many respects, but in reality, they are vastly different. Many technologies are solely focused on visualization, lack the capacity to manage big datasets pulled from multiple sources, or are simply incomprehensible, which puts additional strain on IT workers.

This brings us to the next point, where we look at Alibaba Cloud’s unified data analytics platform, which brings reliability, performance, and consistent user experience to every stage of the data lifecycle.

Introducing data analytics has an extensive suite of tools built for B2B sales. From marketing and prospecting to shipping, take advantage of these tools and services to help you expand your sales online.

With industry analytics, you can further understand the state of your market category and which products are performing best. This can all be found easily through basic industry analytics, such as demand analyses, trends analyses, price comparisons, and more.


How to sell on

Are you prepared to take your business worldwide? Whether it’s Global buy or Global sell, with an seller account, your company can tap into new markets and contact clients all over the globe. Being the largest business-to-business marketplace across the whole of Asia, it connects international online sellers with manufacturers and suppliers.

You can manage your growth with analytics tools, customer data, a custom digital storefront, targeted advertising, and much more. It might also be wise to check out an industry report to understand the market size and top buying countries for your chosen product category.

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