It’s hard to deny the importance of e-commerce today. In the times when anyone can start selling anything from sneakers to custom tours in Iceland, the whole market changes. New online shops rise on Facebook, Instagram, and YouTube. Young entrepreneurs launch highly successful startups, and old-fashioned businesses invest millions in digital evolution research.
In Q2 2019, eMarketer published its e-commerce report. According to it, online retail sales worldwide will reach $5.6 in 2022. By that time, the share of e-commerce in general trading will be at 20%, compared to slightly more than 10% in 2017. Despite the growth rates decrease, this industry rises gradually and inevitably.
E-commerce businesses have several key distinctions like digital interaction channels, customer orientation, and high competition. But the most prominent feature of the modern e-commerce world is data. It allows online shops to outperform brick-and-mortar opponents easily. That’s why we’re going to talk about data in e-commerce today.
Getting to grips with technologies
Let’s forget about trading and look at another sphere. Why traditional banks lose their loyal customers nowadays? A simple answer is because many new players appear. Various FinTech startups deliver digital solutions that are more beneficial for users. The main reason for this trend lies in the tech progress. Courageous startup owners study new technologies, implement them, and deliver new values: speed, convenience, profitability.
The situation is typical for almost all industries, not the banking sphere only. Particularly, e-commerce businesses disrupt markets because they also integrate innovations. It doesn’t matter if you are a startup entrepreneur who wants to make better decisions or a top manager of an international corporation who aims at new strategies, data is the key. It’s vital to use it correctly through business intelligence. But it’s also essential to understand it.
Guaranteed software project success with a free 30-minute strategy session!
Come on. Everybody heard this term. Most likely, some experts even understand it clearly. But the majority of regular managers, analysts, and businessmen get confused when talking about Big Data (BD). No wonder! For instance, Forbes lists 12 definitions of the term from reputable sources like Oxford Dictionary or McKinsey.
To save time, let’s find the common parts in all these defections of Big Data:
- Large size. The packages are really huge. Traditionally, they count in thousands of terabytes called petabytes or even thousands of petabytes – exabytes.
- Multiple sources. Often, Big Data is collected from various points and stored in one database. This removes silo by simplifying analysis/processing.
- No small levels. BD insights are meaningless on a small scale. Instead, they are required for strategic planning, trend spotting, and pattern defining.
- Requires new software. Probably, it’s the most essential part. Big Data barely can be processed with traditional systems. It involves business intelligence tools.
You may be surprised, but BD isn’t for large enterprises with custom analytical departments only. Even small online firms can benefit from it. On the one hand, it’s easy to rent cloud processing power to analyze large bases. As well, outsourcing firms are always ready to find dedicated Big Data experts for your projects. DICEUS is among these partners, of course.
Business intelligence (BI) develops together with BD. As general data packages usually come in unstructured and raw format, experts should transform them into readable info. It’s required to get adequate insights. BI utilizes reports, dashboards, and charts to organize data, making it ready for analysis.
It’s important to know that business intelligence integrates two approaches:
- Decision making. BI helps enterprises to make more informed business decisions that lead to better customer experience and higher income.
- Reporting. The previous approach is possible, thanks to the correct data organization. Intelligence tools allow employees to cleanse and analyze information.
By combining these parts, BI doesn’t tell companies what to do neither it limits options to simple report making. Instead, it enables a new way for employees to work with precise data to make their own conclusions or predictions. For example, an online shop can see which pages customers prefer the most. On this basis, it will be easier to launch a new marketing campaign.
Well, so BD & BI pair in e-commerce is pretty simple. It represents the combination of market strategies and software applications focused on smart analysis of large data packages related to online shopping. Big Data helps to portray your customers, find buying patterns, create better products, and sell them. The final objective is to maximize revenue, of course.
Don’t forget to make your business secure as it’s a vital part of any growth strategy. You can find tips on making online stores safe in our blog.
The need in data-driven analysis
Big data for customer journey
What’s cool, new technologies work fine during all stages of the online purchase journey. In e-commerce, this path includes only four significant steps connected. The journey is cyclic, so the last step leads to the first one, too.
KPMG unveils the next stages with some market insights:
- Awareness – when a client meets your offer for the first time.
- Consideration – when a client researches on your company/offers.
- Conversion – when a client decides what, where, and when to purchase.
- Evaluation – when a client analyzes his/her experience and leaves feedback.
Each part is essential. Moreover, each one benefits from data-driven decisions. Awareness-related moves feel the highest impact as brands can analyze giant databases to deliver excellently targeted ads, reach clients via various channels, and show only relevant content. Thanks to Big Data, consideration and conversion stages also affect the customers’ decisions as companies can predict behavioral patterns. Satisfaction leads to positive reviews during the final step, as a result.
Further, we will check how exactly BI and BD can help in building loyal audiences, selling your products/services, and retaining clients.
Competence and competition
The main challenge in Big Data utilization for companies lies in the amount. It’s not about the size of packages, however. Modern software can process much information quickly, but the catch is in the quality. Too many variables generate lots of data, including false or useless parts. Thus, it becomes essential to focus on two points:
- A circle of competence.
- Knowledge about market ecosystems.
In 1996, Warren Buffet told Berkshire Hathaway shareholders that investors need to master one critical ability – to evaluate selected businesses. He focused on the word “selected”. Today, as well as in the 1990s, there are many companies, so investors should understand their competence circles. Moreover, the sizes don’t matter. Instead, it’s crucial to know boundaries.
This takes us to the second point. Severe competition forces companies to evolve continuously to deliver only top-quality products/services. Respectively, an unobstructed vision on competitors, consumers, and partners is required, too. Big Data packed with BI tools can help in forming your circle of competence as well as getting information about markets.
6 ways BD and BI reshape modern e-commerce
With the essential things in mind, let’s proceed to real use cases. The list below consists of six primary ways to improve your e-commerce business by leveraging Big Data tools.
1. Deliver personalized experience
Earlier, customers had to navigate through hundreds of smartphones, gloves, and books to find relevant offers. Not all sites even had search options. With the rise of Big Data, e-commerce shops can generate tailored content to simplify the customer journey. By using information about the site visitors, their personal details and online behavior, businesses can show only the most relevant offers. Personal recommendations via different channels work fine, too.
2. Enhance customer support
Apart from relevant offers of products/services, buyers want to get tailored support. In this case, Big Data is crucial as it allows us to collect an insane amount of information about each individual. By processing this data through BI units, businesses can transfer it to support centers where operators will have a clearer picture of the audience. This richness enables faster response, personalized attention, and quick solutions to any possible issues.
3. Picture user personas
This point is inextricably linked with the previous one. Today, online customers are much more dynamic than earlier. They explore different sites from several devices, look for promos, check reviews, etc. Packages of raw data allow companies to understand how people surf the Internet. Modern software tracks these journeys, records them, and generates data-rich customer profiles. Later, business intelligence systems help to find trends using this data.
4. Protect and optimize payments
Here, BD and BI help in two connected yet distinct ways:
- Protect finances. Big Data analysis unveils suspicious and fraudulent patterns like a few consecutive purchases at different places with one card or several payments via different channels from one IP address. By understanding these pictures, e-commerce shops can block frauds to protect the clients’ money and data.
- Tailor payments. Apart from defense, BD opens a new way to the optimization of transactions. Let’s say, you can spot that users prefer paying with PayPal, so your shop will prioritize this method. As well, it’s possible to add more payment options such as COD., “bill me later” or cryptocurrencies.
Combined, these points lead to even higher customer satisfaction. Your clients understand when you try to meet their needs by simplifying or improving financial aspects.
5. Run R&D projects
Based on different research papers, a failure rate of new products from various industries lays between 70% and 95%! It means that this beautiful online clothing store with branded hoodies will disappear in a year with a 95% chance. Business intelligence and Big Data can help to avoid this. Actually, it’s enough to build or hire a research team focused on BD/BI. Through proof of concept projects, you will be able to reach the 360-degree outlook of your industry and deliver the demanded products/services.
Want to learn more about proof of concept? Check out the guide with strong POC hints from the Diceus team.
6. Tune prices dynamically
Finally, let’s return to prices once more. Traditional retail and even e-commerce companies follow legacy pricing strategies with stable rates and regular discounts. Today, this approach becomes obsolete. Instead, Uber-style management with dynamic price changes based on the customers’ behavior rises. Deloitte predicts that data-driven prices can generate from 200% to 350% ROI growth within one year! To launch this strategy, it’s enough to run a BI project that will show how to change prices, use discounts, and respond to market changes.
Use data today to win tomorrow
Let’s be honest. Big Data and BI aren’t extremely hyped or innovative ideas. They weren’t presented in annual hype cycle studies by Gartner in 2017 and 2019. They aren’t shown in 2019, as well. Researchers now focus on more advanced data-driven and AI-based trends such as edge analytics processed locally on small devices or augmented intelligence that combines the creative power of humans and the speed of machines.
Although BD isn’t an innovation, it can generate exorbitant profits in 2020. Modern businesses are familiar with Big Data, while customers know about information privacy. We’re entering the era of mutual benefits available thanks to data. If you want to catch this wave, don’t hesitate to consult with professionals. In DICEUS, our market analysts and developers know how to boost e-commerce businesses with tailored BD/BI solutions. Let’s talk!
Guaranteed software project success with a free 30-minute strategy session!