The State of MarTech Amidst Big Data Surge
- Written by TechXO Team
- Category: Martech
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The Marketing Technology sector is in constant flux. The industry is always looking out for the next breakthrough in technology. Most companies have understood the power and the vital role of data in businesses and they reckoned it as a holy grail, not until Customer Data Platforms entered the picture and broke the intangible barrier the last five years. It is not the data that excites the industry. It is the insights from data make sense.
In marketing and sales, big data is nothing new. The hard facts and its intricacy are casting its impact little by little. Several marketing technology companies that use marketing technologies, big data contributes significantly to the analytics and insights team to deliver a decision-making framework and consultation services. The Interactive Advertising Bureau (IAB) and Winterberry Group discovered that US-based companies spent over $5 billion on data management and integration products, going beyond in the maturing era of big data and business intelligence in 2018.
Leading MarTech and AdTech professionals expressed their challenges and failures in an interview with MartechSeries. They have talked about how they wrestle intricate business paradigms that appears from the client. These frequent challenges are lost at the basic level of audience identification, segmentation, and targeting.
MarTech marketers these days might use data in any way or the other to segment audiences based on their various behaviors across online and offline platforms like a website, mobile, live video, social media, events and conferences, brick-and-mortar stores, and connected devices. The list is continuously growing more devices. The increase of big data is eventually forcefully pressuring how a MarTech company handles it.
A fundamental Big Data-MarTech integration would need insights and analytics teams to do certain tasks like building multi-channel customer profiles across millions of first-party and third-party data and linking to CRM or DMPs. The team also needs to perform highlighting and filtering marketing attribution insights to show the effects of marketing and media strategies on various levels of the funnel or flywheel. It is also the team’s job to turn unstructured data into structured, non-repeatable pipelines, and the best use case solution when choosing between Hadoop On-Premise and Cloud.
In Marketing Technology, we will focus on the 4S of Big Data applications such as speed, scale, sustainability, and security
Marketing Technology clients depend on data management and analytics platforms to find real-time solutions to their queries. Speed is achieved, with faster computing and ease of Big Data analytics. Scale and Sustainability are interdependent. The scale and sustainability have been largely automated and are backed with AI and Machine Learning,
The most crucial part of MarTech- Big Data structure is its security.
We take the risk sliding into the ‘Black Hole’ of Big Data applications within the marketing technology and advertising technology as the complexity of Big Data in MarTech conversations increase. Security experts like to call the next stage of Big Data in MarTech as the ‘Black Box’ solutions, where you only look for it when the operations fail or crash.
That is where big data strategy is so vital for any MarTech expert. From recognizing the present and future revenue opportunities to managing risks and disaster recovery, there is a lot of information available in Black Box solutions.
As Big Data ages, we will discover improved machinations of processes between the Cloud service providers, data integration, data warehouse, and business analysts. MarTech-Big Data integration only aims for automation of data preparation, governance, analysis, and visualization that give limitless ways to unlock real business insight across the entire MarTech and customer value chain.
Big data teams in MarTech companies could be the one to uncover the answers to the questions regarding different levels of complexity.