Data-driven marketing is the new era in martech
Ever Since man learned to sell, marketing was born and has been here for thousands of years, the only thing that changes are the methods of marketing. Marketing strategies and processes have developed over the years based on the requirements of the people. Today’s tech. world is experiencing the era of marketing technology also known as Martech.
Marketing technology is still in the process of development, so it is continuously upgrading with an aim to deliver more precise results of marketing campaigns. Marketing technology stack is nothing but a collection of marketing technologies which enable marketers in making efficient marketing strategies. Integration of big data with marketing technology stack is among the new trends of martech, and it has resulted in a heeding update of martech stack. Today, 78% of marketers have an embedded data-driven marketing process.
Let’s dive deeper and understand how big data is integrated into martech stack?
Data-driven marketing is not new, it has been there from decades. In the past, data was stored in different forms, such as files, books, etc. which we can say were database at that time but today it is stored digitally. Traces of database marketing have been found in the 1980s when marketing was undergoing modernization. Data has always empowered marketers in delivering superior results from their marketing campaigns.
You might be wondering what is big data, it is nothing but the collection of data that is huge in size and still growing exponentially with time. Big data is becoming a powerful tool for marketing and sales professionals. Data science coupled with machine learning has helped in delivering a better understanding of the market, refined strategies and improvised decision-making process. Data plays an essential role in the process of predicting the behavior of users that is useful to offer personalized products and services. Presently, Marketing automation tools are undergoing Artificial intelligence (AI) and machine learning (ML) based upgradations and AI & ML feeds on data. Big Data plays an important role in the companies that leverage marketing technologies by helping their teams with genuine analytics and insights that supports their decision-making system and consultation services.
Marketing Technology customers depend on data management and analytics platforms to find real-time solutions to their queries. With faster computing and ease of Big Data analytics, speed is achieved. Scale and Sustainability are inter-related, and dependent on the size and revenue model – in addition to in-house expertise in dealing with and managing Big Data applications. Powered by AI and Machine Learning, scale and sustainability have been largely automated.
The aim of any martech big data integration is to automate data preparation, governance, analysis, and visualization that provides countless avenues to unlock real marketing insight across the entire organization and customer value chain.
Today, big data is looked upon as a big opportunity. Sophisticated analytics solutions for big data gives new approaches to addressing some of the key marketing objectives and delivering impressive outcomes. These solutions can revamp traditional marketing roles and improve how to execute essential marketing functions. Marketers are collecting the data produced from a variety of live customer touch-points to illustrate a detailed image of each customer’s behavior. Analyzing this large amount of data in motion enables marketers to calibrate customer segmentation models and apply the insights to create customer engagement strategies and improve the value of customer interactions.
Numerous big data applications are indicating the tremendous potential for driving marketing impact in customer management. Let’s have a look at some of the benefits of integrating big data with the marketing technology stack.
Benefits of big data marketing technology stack
- Personalization of online Shopping
Shopping industry underwent change almost two decades back when online shopping was introduced. Today, shopping industry is witnessing further advancement by delivering personalized experience through collecting and processing a vast amount of data. These data which are used to deliver a personalized experience to the customers are gathered from user browsing, purchasing behavior, user preferences, product attributes, geographic location of purchases, inventory levels, active promotions, and campaigns and anything else that can be digitally recorded. Providing personalized experience increases the chance of conversion, saves the time of customers and also increases customer satisfaction.
- Monetizing big data for targeted dynamic advertisement
Data monetization generates opportunities for organizations with significant data volumes to leverage untapped or under-tapped data and develop new sources of revenue. Mobile network operators, which sit on large amounts of customer data, have a unique opportunity to monetize the data they are gathering about their customers. Given their direct relationships with customers, they are probably going to have the most accurate and complete information about the customer. They can generate analytics-driven behavioral insights based on mobile engagement, demographic information, and location, creating a 360-degree view of the consumer. Outdoor advertisement companies can have access to insights about the habits of the audiences they want to reach and the locations at which they can best reach them. Data has enabled advertisers to turn every billboard into a targeted entity that reaches the right audience in the right place at the right time.
- Machine-to-machine analytics to improve product life-cycle management
There has been an enormous development in sensor technology that goes in machines, mobile devices, automobiles, utility grids, and enterprise networks. This has promoted to the age of machine-to-machine data at an unprecedented rate and in real-time. Organizations can utilize the data emitted by sensors from a wide variety of applications to analyze and improve the efficiency of manufacturing processes, predict failures of products and identify the favorable time to boost new products to the customer. The data can also provide insights for customer support, product development, and sales teams who can use the information for future targeting of audience. Companies are using advanced statistical modeling techniques to analyze the sensor data and provide real-time insights on event connections, root cause analysis, forecast potential risks and visualize possible scenarios.
- More relevant content
Data has been used to create content as it provides insights about the interest of the audience. When the content is created to keep the target audience engaged, it automatically becomes quality content as it fulfills the requirements of the viewers and also increases the rate of conversions. Analysis of data also enables in providing personalized content for email marketing and other such types of marketing, which further empowers marketer’s in developing effective marketing strategies.
- Better understanding your target audience
After selecting the right target audience, it is important to understand the audience you are targeting. As data enables marketers with the insights of the customers, it becomes easier for marketers to understand their audience and then plan their marketing strategies. This also saves the time of marketing professionals, as now they don’t need to do research or survey to segment their customers. Understanding the audience enables the organizations to develop and offer products and services according to the requirements of the customers.
Marketers are still harnessing the application of big data with marketing technology stack, to further enable the marketing sector with efficient and effective strategies at ease. Big data vows to revolutionize marketing as a discipline, providing the ability to better understand customers, in real-time, on a vast scale. The opportunities from big data are vast and will largely depend on the vision and leadership provided by the leaders in the organization.
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