What Can Big Data Do For Ecommerce

To make the right decision fast, a business owner should have a deep expertise in different fields. Especially when it comes to insights about their target audience. For this reason, using Big Data is one of the leading trends in information technology for last 5 years, which yield its positions only to artificial intelligence and machine learning recently.

What is Big Data?

There are several definitions of this term in several authoritative sources. The most common is the “3Vs” definition:
· volume;
· variety;
· velocity
In other words, Big Data means a large volume of multifarious information which is being generated at high speed. Such volume is often too large to fit into standard Excel sheets. So, you will need extra computational resources to process the data arrays.
Big Data implies that you accumulate information from different sources: web browsers, smartphones, external resources, and so on. These can be users behaviour on the website, history viewing, frequency of purchases or customer’s preferences.Then, this data is aggregated, processed and used to create algorithms for forecasting future behaviour.
Actually, the Internet consists of huge data volumes: at least 2.5 billion gigabytes of new information is produced in the world daily. In fact, when you are doing market research by gathering social media data or monitoring search query trends in your niche – you are already using Big Data on a regular basis.

Now we will look into a few ways to do this better.

1. Join in the Internet of Things

The notion behind the Internet of Things (IoT) is in making all things around “smart” by connecting them to the Internet. Even though your smartwatch processor is considerably less powerful than that of a PC or smartphone, its capabilities largely surpass the productivity of an ordinary wristwatch. In addition, this is used to acquire data on physical state and owners habits (including buying pattern).
But despite tremendous opportunities for analyzing target audiences, the IoT does not exempt from obstacles in the way of online business developing.
However, the number of devices connected to the Internet is increasing at the same speed, as a rate of the data multiplication.That is why this is so important to understand Big Data in ecommerce. The Internet of Things has become the main data analysis niche for app developers in 2016.


According to the IDC report, 31.4% of companies have implemented the IoT principle into their business solutions already, while other 43% are planning to do this soon. An online business needs an efficient technology of analysing and collecting data from different platforms to keep up with the clients and increase sales.

2. Follow the trends

Google Trends is a simple and, most importantly, free service to start working with Big Data. It gathers information from search queries of users from around the world and represents these in diagrams.
This is a powerful tool for monitoring what your target audience is actually searching for and what their points of interests are. If you want to know more about the demands and offers in your business niche, the popularity assessment of search queries is the right way to this.

3. Analyze your user

In earlier times, this was rather hard to personalize an eStore for a specific user. In most cases, the information from a user’s profile was used for this. A special script adapted available products in stock, prices and delivery terms to a required region. Whereas, Big Data provides wider options for micro-targeting. The more volume of data about the prospects you own, the more carefully you can configure product search results to meet the needs of each and every customer.

Do not try to sell to everyone at once. Nowadays, the best strategy for business is to retain current customers rather than find a new ones. According to Ecommerce market studies, recurring sales account for up to 70% in a typical online store’s sales.
Big Data can reveal the information you never thought to monitor: from a fashion style to a specific time when people swap summer tires for winter ones. This is important to mention that these small, sometimes insignificant facts can tell a lot about your target audience and help forecast their future preferences. For instance, Amazon offers products based on viewing history and completed purchases. In most cases, this tactic brings success.

4. Grow your mobile

Mobile devices and social media generate a massive amount of data each day, and the speed of this generation is growing significantly. A study by GlobalWebIndex shows that in 2016 customers used 3 different devices to connect the Internet. In most cases, these were tablets or smartphones. This mobile-first approach gains more recognition – the analytics of large ecommerce entities clearly demonstrates the significant growth of conversion rates among purchases completed by mobile users.


Online stores usually employ tracking snippets – special code which tracks the actions in mobile apps. They help accumulate and analyse information about user behaviour, pulling personal data from social media (provided that users sign in to their accounts).
These tracking snippets can be realised as open-source utilities so that you can easily adapt these to your company’s goals. You can find these on the Datameer platform.

Moreover, the tracking snippets give you an extended analysis of traffic sources and conversions. Such data allows you to understand your customers’ preferences, predict their behaviour and redirect them to a page of a product they will like for sure.

5. Use ready-made solutions

The majority of large online stores acquire and analyse the data about their customers. There are ready-made solutions – programmable interfaces and BI platforms (e.g. OWOX) which can process large volumes of data. OWOX system works with Big Data and analyses all available information about your company and your key competitors.Large ecommerce projects often develop their own in-house platforms, but this is a long and costly process.
Such analytics systems are available in a turnkey form and can be adjusted for any type of business, so you can significantly save your development budget.

Conclusions

“Taming” of Big Data can serve a qualitative leap for your brand. Nevertheless, the main trend is not just to use Big Data, but to strengthen its role in doing business.

Big data should become the backbone of your marketing strategy. By acquiring skills in collecting and using this information in a consistent manner, you will improve conversion and average bill, and build relations with your clients, converting them to your brand advocates.

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