Rise of Behavioral Data: Major Data Trends Shaping MarTech in 2022

    Rise of Behavioral Data Major Data Trends Shaping MarTech in 2022

    In 2022, businesses will need to step up their game to comply with new data privacy rules and optimize data efficiently.

    In 2021, an increase in ML adoption, a shift away from cookies, and changes prompted by COVID-19 were just a few of the primary drivers compelling businesses to explore new and improved means of consumer understanding and engagement.

    However, in 2022, businesses will need to step up their game — not simply to comply with new data privacy rules but also to optimize data efficiently. Thus, for data-driven marketers interested in achieving success over the next few years, a few trends are to consider are:

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    Increased demand will exacerbate the shortage of data talent

    The pandemic drove marketers worldwide to swiftly expand and improve their digital services, resulting in a burgeoning need for and lack of competent data professionals, particularly engineers. While there is a skills shortage, the number of data roles and specialties will grow dramatically as a result of data stack architecture changes. By end of 2022, large firms should expect job titles such as data product manager, data governance manager, and artificial intelligence operations manager to become considerably more prevalent.

    The Chief Data Officer’s role will be expanded

    Rather than focusing exclusively on engineering and analytics expertise, Chief Data Officers (CDOs) across the board will need to strengthen their human resources, communication, and leadership capabilities in order to transform organizational structures and foster a truly data-driven culture within their organizations. As a result of the death of cookies, businesses of all sizes are now seeking new ways to better understand and communicate with their customers. For many, this transformation entails a renewed emphasis on first-party data collection and the development of more direct data interactions with consumers via loyalty programs, risk mitigation, and intelligent goods.

    Balancing privacy and customization

    Successful marketers will refocus their efforts in 2022 and beyond on understanding clients ‘well enough.’ One main driver of this trend is consumer unhappiness with large technology corporations, which have been acquiring considerably more data than is necessary to deliver adequate service. Consumers have had enough, and organizations globally will need to adapt in order to maintain a healthy balance of personalization and privacy protection.

    Increased use of data tools will necessitate improved integration

    The number of distinct data tools used by enterprises will continue to grow, with many firms utilizing a variety of platforms and solutions for diverse business functions such as testing, analytics, and personalization. Along with client-side tracking, enterprises are investigating additional options on the server-side and in the semantic layer that resides between data storage and is critical for data mapping.

    With the proliferation of data solutions, more vendors are working to build best-in-class technology, permit unfettered data flow between systems, and minimize overall complexity. More suppliers are collaborating on single-use scenarios as part of this aim, contributing to contemporary data stacks that enable organizations to reduce risk and integrate data more effectively.

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    Decentralized data teams will contribute to increased efficiency

    The growth of the worldwide Artificial Intelligence (AI) and Machine Learning (ML) markets is increasing the demand for legible and workable data, which increases the value of data catalogs and other tools that assist in visualizing and deriving meaning from data. Many organizations have established dedicated teams to convert raw data into actionable insights. This frequently causes bottlenecks, delaying the data path to decision-makers who require immediate access to insights.

    Many businesses are decentralizing their data strategy, delegating some work to smaller, more agile teams that can focus only on their department’s needs. This method enables firms to maximize productivity and ensure that the right individuals access data at the right time.

    The utilization of behavioral data will mature

    Behavioral data enables a business to understand how its end-users, customers, and prospects interact with its digital estate.

    The shift to higher-quality behavioral data has been facilitated in part by changes to privacy frameworks and the introduction of new event monitoring systems. Another factor contributing to the shift is increased data maturity, as more firms recognize that not all behavioral events are investment-worthy (in time, quality, and cost to capture). However, regardless of the reason for the change, it will assist firms in reducing churn, improving product analytics, and providing more personalized customer support, among other benefits.