- Big data has a lot of diverse information that comes with never-ending volumes and high velocity.
- Big data can be easily collected from surveys, comments on social media, websites questionaries, and check-ins.
- Big data is collected in computers and is processed in specifically designed analytics software.
- Every business can use big data to target customers by personifying advertisements.
- Digital marketing has become easier than ever by using big data mixed with some complex business analytics
Introduction to big data:
Big Data is the future of the marketing world and it is transforming the world with its newly explored advantage in the digital world by storm. In recent years, Big Data has completely changed the way with which companies look at the digital world and how they store data. Big data paves the way for the precise utilization of enormous amounts of data for business analytics in the easiest way possible. Studies show that we produce 2.5 quintillion bytes of data. The amount of data produced will only increase with each passing day. Even a small enterprise generates data each day, including being the emails, Sales data, or customer information. All this information only helps in improving the service you provide and enhancing the business.
So, what is big data?
Big data is a combination of huge and extremely hard to manage volumes of data – structured, semi-structured, and unstructured data collected by organizations in a way that it can be used for gathering information, insights and can be used in machine learning projects, predictive modeling, and many such advanced business analytics applications that help improve strategic decisions making in businesses. These analytics can be helpful in areas like Internet surfing, healthcare, fintech, business analytics, advertising, government data scientific research, biology to name a few. Sources of collecting big data vary from publicly shared reviews, comments on social networks, data collected from personal electronics through apps, check-ins on the internet, surveys to sensors and smart devices across the digital world. This data is usually stored in computers and is analyzed using advanced business analytics software. Many ‘software as a service (SaaS) specializes in managing and handling such complex data.
Big data includes three V’s- Volume, Velocity, Variety
Volume- Big data as the name suggests is about huge volume.2.5 quintillions of data are generated each day and the number doubles every 40 months or approximately 3.5 years. This allows companies to work and sort with a huge amount of data in each data set. Just to give an idea, Walmart collects approximately 2.5 petabytes of data from its customers every hour from customer transactions. These big companies have Petabytes of data stored in their servers and it helps to direct the company for future planning and actions.
Velocity- It is the rate at which data is received stored and processed to obtain useful information. The faster the velocity better it will be for data analytics companies. Big data enables data streams directly into memory as opposed to being written on discs. This allows internet-based smart products to operate in real-time and obtain quick evaluation and action for specific sets of data. Being more agile than the competitors gives companies a great competitive advantage.
Variety- Variety translates to the huge variety of data available online. A variety of data like messages, texts, audio, images posted on social media, sensor readings, location data from mobile phones, and much more is available on the internet. This unstructured data needs to be stored and processed critically to obtain useful information that can be used by companies for their marketing campaigns. Previously storing and decoding this kind of data was expensive but big data and business analytics tools have made it simpler and less expensive.
Data analysts usually dig into the relationship between different kinds of data such as demographics and purchase data to find out what kind of products sell in which demographic areas. And if a correlation is found how can companies push their products in those demographic areas to improve sales reach the target audience. The goal of big data is to improve the speed at which products reach specified markets and reduce resources and time required for market penetration and gain customer satisfaction. This is the area of Big Data and Marketing crossways for business analytics. To know many more interesting facts head on to our Instagram page : [https://instagram.com/marketing360.in?utm_medium=copy_link.]
Big Data in Marketing?
Companies like Facebook and google use big data for revenue generation by placing targeted advertisements to users on social media and other internet users. This is an integration of Big Data with marketing. The amount of personal data available through big data enables companies to know the needs, likings, interests, hobbies of specific users, which then helps them analyze the kind of products they need to advertise to the user. This in turn enables them to produce and show personalized advertisements to specific users. This process called data mining is used by companies to turn raw data into useful information that helps them to find patterns and regularities in huge data sizes and absorb more information about their customers to develop more effective marketing strategies, improve sales and reduce advertisement costs.
This process includes five basic steps. Firstly, data is collected and stored in data warehouses. Then the stored data is systematically managed and broken down. Next Business analysts access the data and decide how to divide it into sectors. Then business analytics applications sort the data according to the users and lastly, the end-user data is provided in easy charts or graphical formats.
Consider an example of a retail bookstore. Traditional physical stores could track which book has been sold and which is not. For selling the unsold books the owner could use tie-ups with his loyalty programs and use them to sell those books to individual customers and that would be it. But now with online shopping, the customers have a deeper knowledge about the products they want to buy. But data has now enabled sellers to know what their customers have bought in the past, what they are looking at, and what kind of books interest them. Using this information sellers can now influence users to buy what they want to read by using user-specific promotions and reviews. This business analytics software enables help sellers to understand whether a customer has responded or ignored a specific recommendation. This helps the seller understand what the customer is about to read next by using predictive algorithms. This information was not available to retail sellers let alone recommending books. This has helped online bookselling businesses like Amazon achieve such exponential growth.
From where is data collected?
Data like age location, purchase history, preferences, financial conditions, positions of the competitors, etc. can become important information for business analytics and taking important and well-informed decisions for the future and attracting more customers.
- Loyalty Programs- Companies arrange loyalty programs enabling customers to collect points with every purchase and they can be redeemed by shopping for specific items or specific values. This helps customers to keep their profile on the portal which contains their preferences and habits, this is used for retargeting.
- Surveys- This helps the company retain its customer names, contact information, and location. These details are also obtained while customers make an online purchase on a website. The locations of these customers are tracked along with their contact details which are then later used to personalize content for customers and promotions. A survey is the easiest way to gather information from customers with their consent and answers.
- Social media- Companies can collect data from social media through applications like Instagram, Facebook Twitter. The data is traced from the activities you are involved in. The photos you like, pages you follow are traced and your preference can be easily known. Tracking emails, cookies, and satellite images is also used to gather data.
- Data Companies- Big companies who have lots of customer data become suppliers for other companies for such data. Data companies sort big data in such a way that it is easy for business analytics operations. Many such third-party companies sell such data in structured as well as unstructured and make a lot of profit.
How does it work?
Big data in the field of marketing includes analyzing and using huge amounts of digital information to improve operations such as
- Getting all-around information about their customers- ‘Know your customer’ or KYC was initially a tool of banks to get an insight of their customers and prevent frauds, but it has now become a tool for big data through cloud computing. It is available even to small and medium businesses to gain customer engagement by knowing about how customers react to your products and their advertising. This overall helps in improving existing products and increasing their revenue per customer.
- Improve brand awareness- Companies using big data enjoy a greater increase in brand awareness by 20% versus 7.4 % when compared to those who don’t. Big data allows companies to create personalized content which is customer-specific. A company can use big data to get any product noticed to its probable customers without doing huge ad campaigns like giant companies.
- Improve customer acquisition – It is another benefit that big data brings to marketing. Companies using big data outperform other companies by 23% in customer acquisition. Big data allows marketers to use real-time data in cloud computing environments with the ability to process and analyze data and can take immediate actions quickly and accurately. This is achieved by using GPS, IoT sensors, and webpage clicks.
- Price Optimization- Big data enables companies to acquire details about the prices of competitors and inflation over a specific time. This also enables companies to determine the purchasing power of users and the brands they like ad use so that they can subtly stick to that without incurring losses. Also, what kinds of discounts competitors are providing can be determined and further business strategies can be decided by the company.
How have companies used Big Data in the past
The first example that comes to one’s mind after hearing big data is Netflix. Netflix has been prolific in its attempts to use big data to improve the crucial factors of its service. Their data-driven recommendation platform is the most prevalent use of big data to the users. This has increased the company’s connection with its customers and also saved them a lot of money and influenced what type of content hits the servers.
Amazon – Similarly Amazon uses big data to operate and personalize and customer satisfaction. But amazon uses a comprehensive approach. They have a huge customer base and different services which require different processes. Amazon has benefitted greatly from its big data usage as it’s driving huge amounts of sales. Their machine learning software also synchronizes with all the data to maximize the efficacy of things like ratings and reviews for customers.
Airbnb – It is one of the best success stories as far as big data is concerned. Airbnb has structured most of its processes around gathering key insights from data. They used data to increase their marketing efficiency which left them to grow their presence and the concept very quickly. Big data let them understand all the insights about their best and worst-performing geographical areas and what needs to be improved based on customer reviews.
What should I consider before starting my big data journey?
Solving key business issues by converting data into insights to influence business actions and driving critical business outcomes is the main aim of big data. Companies get overwhelmed by various challenges when it comes to using big data so starting their journey by asking important questions is necessary to maximize ROI is necessary.
- What should our analytics roadmap look like for achieving our marketing objectives?
- What business outcomes would we like to see by using big data influence?
- What services do we need to develop by using big data to gain a competitive advantage?
- What technology options would we like to enable your big data journey?
- How can we develop appropriate skills and resources in-house to start on the big data journey?
Big data brings forth big opportunities and will largely depend on the vision and leadership provided by senior leaders in the organization. Leaders will have to enable the experimental culture and learning by driving important pilots and points of contact using big data. Small success will pave the way for the large-scale adoption of big data analytics and approaches in marketing and will make it more innovative and impactful to the customers. Big data will gain a lot of traction in upcoming years and will lead to an explosion of digital marketing. Click here to read more amazing articles on marketing concepts and news.