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Which is Better, Data Analytics or Digital Marketing?
Data analytics and digital marketing are the two major trends in the business world. Companies are shifting their gear from experience-based decision-making to understanding the consumers on the basis of the data that they have collected and are also now shifting their marketing communications from traditional channels to digital marketing channels. With digital marketing, it has become easy for companies to collect data regarding consumer behavior and their preferences, and with data, it has become easy for companies to present consumers with marketing communications that will hit the right nerve. With data analytics and technology, it is now possible for companies to run different advertisements in the same neighborhood for different family demographics. For example, companies can run different advertisements for a household that has one single individual who is very sustainability-conscious and another household that has a full-grown family and is looking out for convenience.
In this article, we will be gaining deeper insights into the concepts of both digital marketing and data analytics and doing an analysis to determine which is better: data analytics or digital marketing.
Comparison Between Digital Marketing and Data Analytics
Finding the sweet spot between digital marketing and data analytics is like comparing apples and oranges. These methods help in running different aspects of the business. Digital marketing helps us digitally market the product, while data analytics provides us with data insights on various business actions and parameters. Instead of focusing on which is better, an individual should focus on how to integrate these two techniques to produce the best results for the company. The company can combine these two techniques to −
To make the target audience narrower and more relevant.
To increase the conversion ratio of the company. The conversion ratio is the product of the number of units sold and the number of ads shown to achieve sales.
It can also help us advertise better. Through the amalgamation of data analytics and digital marketing, companies can easily narrow down their consumers and hit the right nerve.
Companies can collect feedback on their advertisements, use data analytics to understand them better, or find patterns and then use digital marketing to improve upon them.
Companies with data analytics can easily understand which marketing channels (Instagram, Twitter, Pinterest, Snapchat, Facebook, their website, search engine marketing, PPC, or others) are working for them and what type of content is working as well.
In-depth Concept of Digital Marketing
Any marketing initiative taken by the company on digital platforms or the internet to promote or advertise its product, service, or brand name is known as digital marketing or online marketing. Companies today are leveraging the fact that consumers have access to high-speed internet and smartphones. The various wings of digital marketing are −
Social media marketing − it is marketing done through various social media platforms like Facebook, Instagram, LinkedIn, Hike, WhatsApp, Telegram, YouTube, and others.
Affiliate marketing − it is marketing done by famous people on social media platforms or in the digital world and by experts in a particular field. Here, the influencers or affiliate marketers try to convince the consumer to purchase a particular product and brand.
Search Engine Marketing or Paid Marketing − Techniques: Here, the company pays the browsing website to promote its content on the top of the SERP so that it can have more consumers and high website traffic.
Search Engine Optimization − Here the marketers focus on improving the ranking of the page or the website on the browsing site through various tips and tricks. It is an organic form of marketing.
Email Marketing − In this type of marketing, businesses send e-mails to customers about products, services, price offers, discounts, or warm greetings on special occasions and holidays.
Content marketing – it is a type of marketing in which the company's product has an impact and persuades content to sell the company's products and services. This wing also has an important role to play in other forms of marketing because the company needs content to advertise its products.
In-depth Concept of Data Analytics
Data analytics, in simple terms, means making sense of huge numbers and figures. Data analytics helps companies understand patterns, relationships, and trends from a huge set of numbers and data. Data analytics is not done manually, but sophisticated tools and technologies are used to bisect the data and draw interpretations from them. Data analysis will help the companies in −
Improving their processes, products, or services.
understanding their consumers and their needs better.
Will help the company make data-driven and insightful decisions.
This will help the company understand the market.
will also help the company in making future growth-related decisions and others.
Data Analytics can be done in the Following Easy and Simple Steps
Data collection − this is the process by which the company starts collecting data. The. The data could be varied and very extensive. For example, in the online world, the company could collect data starting from the phone that the consumer is using: how much time is he spending on each website, while scrolling through the website, what the average time took on each part, what competitors’ products is the consumer looking out for, when is the consumer collecting information, what triggered the consumer to collect information, is the information he is adding in meeting his actual preferences, and others.
Data storage − after understanding the amount of data that a company can capture in the digital world, it becomes essential for companies to have a proper storage system where they can store gigabytes and terabytes of data. This is very important because anyone can mess up with the data, and companies might need a reference point at any point in time. They should have at least two copies of the files in the cloud.
Data processing − This is the stage where the company starts operating on the data. It can be done in the following ways −
Centralized processing − This was used in the past, but here the company is not storing the data in different areas and asking the data analyzers to start working on the central data. It is a cheap and easy method, but not advisable.
Distributed processing – it is where the data is stored and processed on different servers.
Batch processing − Sometimes the company collects the data in batches; for example, the side effects of the medicine can affect humans, so the data is collected in batches and processed in batches only.
Real-time processing − Here, instead of waiting for the data collection process to complete, the consumer starts working on the data as and when they get it. It is good for the dynamic and fast-paced working environment that we are in but has huge costs involved as well.
Data cleansing − after the company has decided how they are going to process the data; it is time that they clean its data. This might sound like something very easy to do, but when you have been provided with trillions of entries, everything just stops making sense. Here, the company will be deleting all the duplicate entries and any spaces between that might act as a hurdle in analysis, making the data uniform, removing the data that is not needed for analysis, and others. This step will ensure that when the analyst starts running codes on it, they work and errors do not come up.
Data analysis − This is the stage that we have all been waiting for. This stage provides us with meaningful insights that are going to change our world. Data analysis can be done in the following manner
Descriptive analysis − This helps the company understand what has happened in the past and what is happening currently.
Diagnostic analysis − This is the type of analysis in which the analyst answers questions like, "What made that figure go down?" or "Why did such a thing happen in the past year?" For example, if today's sales are down by 10%, the diagnostic analysis will help the company understand the various factors that contributed to the decline. It is also known as data mining, correlation analysis, drill-down, data discovery, and others.
Predictive analysis − This helps us know what could go wrong on the basis of historical data or past data. Various tools and techniques, like machine learning, pattern matching, forecasting, and predictive modeling, are used to analyze data.
Predictive analysis − This helps us understand the various solutions for the problems could be that we have identified in the predictive analysis.
Digital marketing and data analytics are crucial factors for running a business in today's volatile, uncertain, ambiguous, and complex business world. These two techniques will help the business survive as well as thrive with the consumers.
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