Data has become an essential commodity for most modern businesses and institutions.
Figures published in 2022 suggest as many as 97% of surveyed organizations are currently investing in data initiatives, with 92% realizing measurable business benefits in response to big data usage.
The development of big data architecture enables teams to not only collect valuable information pertaining to key clients, markets and processes, but also organize and analyze this data more efficiently.
By improving data accessibility and ensuring assets are appropriately shared across all aspects of an organization, staff are able to dramatically improve the quality of core services.
By leveraging big data analytics, online businesses position themselves to better understand customer behaviors in relation to wider market trends and forecast developments, aiding teams in tailoring essential services to anticipate client demands.
To explore this idea in greater detail, we must first answer the question: what is big data and how is it impacting online industries?
What Is Big Data?
Big data refers to the information that businesses collect, store and analyze to inform essential operations.
Big data typically includes large volumes of both structured and unstructured data, usually derived from multiple sources, containing complex and high-value business information.
Big data is distinct from traditional data in that this information is generally too voluminous and complicated to be processed using traditional software systems.
Instead, teams must develop specialized data architectures designed to autonomously organize and analyze data efficiently.
Common examples of big data sources include:
- Business transaction systems
- Customer databases
- Social media activity
- Online customer behavior
- Mobile applications
- Geolocation data
The Three Vs Of Big Data
When designing architectures intended to analyze data and extract valuable information from complicated data sets, business leaders must consider the “three Vs” of big data:
- Volume – This involves the amount of unstructured and complicated data that must be stored and organized within big data architectures, including sources like social media feeds, web page clickstreams and mobile app data, often equalling multiple petabytes
- Velocity – This refers to the speed at which data is received and analyzed, the aim is to develop systems capable of processing data in real-time, enabling businesses to act on new information as quickly as possible to gain an advantage in competitive markets
- Variety – This concerns the different types of data available for analysis, big data often deals with unstructured data types like audio, text and video files, each of which can require varying levels of preprocessing before teams can gain insights via data analysis
How Does Big Data Impact Online Businesses?
Well-implemented data analytics functions allow businesses to gain valuable insights into target audiences and their client’s preferences.
As customers interact with online tools via actions like searching for products, sharing social media posts and completing purchases, unique data is created. When analyzed, this data provides valuable insights into expected customer behaviors.
The higher the volume of reliable consumer data that businesses can successfully analyze, the clearer the image of the business’ target customer will be.
This process enables teams to tailor advertising campaigns, product marketing strategies and product development tasks to more accurately meet the desires of specific target audiences.
As big data architectures and related analysis processes become more accessible and easier to implement, more businesses across a greater number of industries are able to take advantage of these benefits.
This is reflected in reports revealing 59% of organizations are invested in improving data-literacy, with 92% accelerating the pace of big data investments in recent years.
Security technology trends also suggest big data adoption rates may continue to increase in the coming years.
Research indicates 86% of large companies consider client data to be central to successful media strategies, with 85% of organizations considering data to be one of their most valuable assets.
This may help to explain why global cyber attacks have increased by almost 40% recently, leading many leaders to prioritize data security and cybersecurity improvements.
The Benefits Of Big Data Analysis For Online Businesses
On a macro scale, big data analysis enables online businesses to connect with their audiences in a more meaningful way, with this connection typically contributing to increased sales and improved engagement.
However, to truly understand the value of big data, it’s important to define exactly how analyzed data can be used to provide measurable benefits to organizations.
Personalization Of Services
Collecting and analyzing user data enables businesses to personalize customer experiences, a benefit that almost 90% of surveyed consumers prioritize when shopping online.
Once an online business has implemented big data analysis tools used to autonomously monitor user behavior, personalized experiences can be easily created to meet the needs of specific customers.
Personalized emails can be sent to customers containing tailored discounts and offers based on previous shopping behavior.
In addition, targeted advertisements and cross-selling strategies can be developed and used to inform customers of new products that they’re likely to purchase.
Enhanced Customer Journeys
Big data analytics tools can be used to track customer journeys across various sites.
Teams can identify every interaction a customer has with a specific brand or type of product, including items that have been viewed and those that have been purchased.
By analyzing this data, businesses gain a deeper understanding of clients, with this information used to inform marketing strategies.
Demand Forecasting
The success of online businesses will often rely on well-optimized inventory management, with businesses required to strike a balance between ordering enough stock to meet demand and avoiding costs related to overstocking.
Big data analysis allows teams to accurately forecast demand based on past sales data and buyer activity, improving the efficiency of this process.
Buyer Sentiment Analysis
Online businesses can utilize data analytics tools combined with AI and machine learning programs to accurately analyze buyer sentiment.
Customer reviews may be processed to learn how audiences respond to certain products, analyzing the language used to determine whether opinions are positive or negative. The results can help to improve future product developments.
Improved Customer Service
Big data analytics can help to improve customer service in several ways.
Teams can track average response times to ensure queries are addressed promptly across all services, as well as monitor active deliveries to ensure products arrive on time.
Big data can also be used to identify potential issues regarding supply chains, allowing teams to implement fixes quickly.
Big data analytics tools also enable businesses to accurately analyze and organize customer feedback surveys, text chats and call transcripts, helping teams to identify common issues and better address customer concerns.
Staff can also access detailed customer history records to aid teams in answering customer queries much more efficiently during support conversations.
Summary
Big data continues to transform online industries by providing teams with accurate, actionable customer information used to measurably improve the quality of core services.
Big data analysis allows teams to better understand their audience’s needs, ultimately allowing businesses to tailor key marketing and fulfillment services to meet the requirements of specific customers.
By personalizing customer experiences, connecting consumers with new products they’re likely to enjoy and optimizing inventory management, businesses can gain desirable advantages in competitive markets, illustrating the importance of big data in the growth of online industries.
