Big data plays an important role in digital marketing. Each day information shared digitally increases significantly. In this digital era, "Data is king" and it is irreplaceable to every organization and business for their digital marketing strategies. With the help of big data, marketers can analyze every action of the consumer. It provides better marketing insights and it helps marketers to make more accurate and advanced marketing strategies.
Before going to the topic, let's understand what big data is?
Nowadays, organizations collect, store and analyze the massive amounts of data that is known as big data. Analyze the data and take out the useful insights from those data is known as big data analytics.
Volume – it refers to a large amount of data (Size of data)
Velocity – it refers to the speed at which the data is generated, stored, analyzed and utilized.
Variety – it refers to the different sources of data as well as different types of data that is structured, semi-structured and unstructured data. Nowadays data comes from different sources like social media, emails, apps, wearable devices, smartphones, and IOT connected appliances.
Veracity – it refers to the uncertainty of data. Veracity is the quality, accuracy, and trustworthiness of the data.
With the help of big data analysis, marketers can understand their target audience very well. In this heavy competition era, understand your target audience is very important for companies to stay ahead of the game.
From the beginning, the company can get a huge amount of data through interaction with the customers like, what they want from the brand, what they thinking about the brand, and when they bought via which channel,
With Sentiment analysis, a company can get better customer insights and that will help marketers for future campaigns. Sentiment analysis is a process that analyzes information about how the customer feels about a company, its brand, and its product or service. It is also known as opinion mining.
Analyze unstructured customer feedback through social media post, reviews, and customer care conversation allow companies to understand customer's feelings, opinions, and attitudes about a certain brand, product or service. It tells whether the underlying sentiment is positive, neutral, or negative. Sentiment analysis uses text analytics and natural language processing.
Engage the customers at the right moment with the right message is the biggest issue for marketers. Big data helps marketers to create targeted and personalized campaigns.
Nowadays, personalization is the key strategy for every marketer. Engage the customers at the right moment with the right message is the biggest issue for marketers. Big data helps marketers to create targeted and personalized campaigns.
Personalized marketing is creating and delivering messages to the individuals or the group of the audience through data analysis with the help of consumer's data such as geolocation, browsing history, clickstream behavior, and purchasing history. It is also known as one - to – one marketing
Analyze customer's buying behavior helps marketers to offer more relevant product recommendations for their customers. Amazon is an excellent example of a product recommendation. It gives a better suggestion based on your searches, interests, and previous purchase history.
When Amazon recommends a product it also uses market basket analysis for cross-selling. MBA is the most common technique among marketers to identify what products customers bought together. It helps to recommend a product based on the buying history and other people's buying history who bought the same item.
Personalized marketing allows marketers to reach a specific audience. If companies send the right email to the right person at the right time helps, companies to build a personal bond with their customers and that leads to increased sales. You can create an effective email campaign for your target audience based on their interest, demography, search history, and preferred content.
Information gathered from browsing history such as website visits and which deals or offers they consider are used to creating more targeted and effective Ad campaigns. Digital advertising means display company Ads on third-party websites to its site visitors that will help companies to gain more revenue. Google and Facebook is the best example of digital advertising.
Personalized targeting help companies to improve customer experience, increase brand loyalty, and boost sales as well.
With the help of Big data analysis, companies can know more about their customers such as what they buy? how frequently they buy a certain product? And which payment method they prefer? It will help to make the right offer at the right time that leads to increased sales.
Big data also helps to predict the demand for a product. With the help of Predictive and Prescriptive analytics company can improve their demand forecasting exactly. Does this allow companies can determine How much they produce? Which product? When it produces? and which location?
Predictive analytics – what can happen? – It is about the future.
Prescriptive analytics – what should we do? – It provides advice based on predictions.
Demand forecasting reduces the risk of stockouts. It allows companies to control their production costs as well.
Big data analysis allows companies to identify the best price for products based on competitors' price, seasonal price, cost of goods, and other variables. Marketers can also identify the price according to the demand. Price optimization can maximize sales and revenue.
Marketers should answer some questions to increase campaign effectiveness as to Whom to contact? When to contact? How to contact? and what to offer?
Predictive analytics forecast the future based on current data and historical facts. With the help of Predictive analytics, marketers can determine which customer or customer segments to target and the right content for each customer. It also helps to discover the right channels and the right timings for the campaign. That will help to increase the response rates.
Predictive analytics with Data visualization helps to improve the efficiency of a marketing campaign.
Data visualization is the process of presentation of information or data in visual formats such as graphs, charts, tables, diagrams, and maps. It helps to understand huge data sets more easily and fast because humans are visual by nature.
Budget optimization is one of the biggest challenges for digital marketers. Does a customer directly go to your website and make a purchase? Rarely. In this digital age, before making a purchase decision consumers use social media channels for peer reviews and they also consume a lot of digital content for research and comparison.
Marketers use many ways to reach out to their customers like blogs, Emails, Social media channels, affiliate networks, and Adwords. Marketers need to determine which channel or touchpoint is highly contributing to conversion, revenue, ROI, and what channels are creating more sales opportunities. They should ignore the channel which has a poor click-through rate. That will help marketers to manage their budget smartly and that is possible with the Attribution model.
Google defines, an attribution model as a rule or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths.
With the help of the Attribution model, marketers can understand what induces the customers to buy? and how buyers interact with different channels throughout their purchasing journey. It also helps to identify the contribution of each channel in CTR and conversion. So you can better invest in channels that have a high conversion rate.
Data analytics also be used for measuring campaign performance and the effectiveness of each campaign. Accurate campaign results help marketers for future campaign strategies.
Through data analytics, companies can increase their profitability. Apart from that big data is also used to identify the right and related keywords to your website and that helps to drive more traffic to your website. With the help of big data analytics, you can discover the customer needs that help you to create quality content so that you can increase your audience engagement.
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