The Rise of Behavioral Data: Key Data Trends Reshaping MarTech and CX in 2022

Marketers across the globe are at an inflection point with how they use data. In 2021, an increase in machine learning, a shift away from using cookies and changes spurred by COVID-19 were just a few major factors forcing companies to seek new and improved methods of better understanding and engaging with customers.

But in 2022, organizations will need to up their game – not only to comply with new data privacy laws, but just as importantly, to optimize data efficiently. So, for data-driven marketers looking to succeed in the next few years, below are a few trends to consider.

Increasing demand will worsen the data talent shortage

The pandemic compelled marketers across the globe to rapidly increase and improve their digital offerings, contributing to a rampantly growing demand and shortage of skilled data talent, especially engineers. Just one type of discipline, the role of Big Data Engineer, will cost an average of $141,500 each year to retain; all the while, the global Big Data market is forecasted to grow to $103B USD by 2027.

While there is a talent shortage, the number of data roles and specializations will increase significantly, prompted by architectural shifts in the data stack. In 2022, expect to see job titles like data product manager, data governance manager and artificial intelligence operations manager to become much more common in large businesses.

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The role of the Chief Data Officer will expand

Rather than just possessing technical excellence in engineering and analytics, Chief Data Officers (CDOs) across the board will have to expand their HR, communication and leadership skills to transform organizational structures and develop a true data-driven culture within their companies.

Skills like negotiation and conflict resolution will be vital to help CDOs build bridges within different departments and make data more intrinsic in their organization. Without such skills, it will be difficult to compete with effective data native giants like Netflix, Amazon or Auto Trader.

Goodbye cookies, hello first party data

Google’s commitment to phasing out third-party cookies by 2023 and Apple’s App Tracking Transparency (ATT) framework in 2021 are two prominent forces driving companies to spend away from legacy advertising to more customer-focused approaches.

Due to the shift away from cookies, companies of all sizes are now looking for new plans to understand and engage with customers better. For many, this change means a reinvigorated focus on collecting first party data and building more direct data relationships with consumers via loyalty programs, risk reduction and intelligent products.

Striking a balance between privacy and personalization

In 2022 and beyond, successful marketers will shift focus from understanding customers better to understanding customers ‘well enough.’ One key driver of this trend is consumer dissatisfaction with big tech companies, like Facebook (or Meta), that have been capturing significantly more data with their products than is needed to provide good service. Consumers have had enough, and businesses worldwide will need to adapt to ensure data democratization and a proper balance between personalization and privacy protection.

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The growing use of more data tools will require better integration

The amount of different data tools used within organizations will continue to increase, with many using various platforms and solutions for different business areas, like testing, analytics and personalization. In addition to client-side tracking, organizations are also exploring more solutions on the server side and in the semantic layer, which exists between data stores and is crucial for data mapping.

With so many data solutions in use, more vendors are now collaborating to develop best-in-class tooling, enable the free flow of data between systems and reduce overall complexity. In this mission, more vendors are beginning to work together on single use cases, contributing to modern data stacks that enable businesses to reduce risk and integrate data better.

Decentralized data teams will help drive efficiency

The global artificial intelligence (AI) market will increase 40.2% from 2021 to 2028, while the machine learning (ML) market will grow 41.1% by 2030. This uptick is driving demand for data that is easy to understand and work with, which is in turn making data catalogues and other tools to help visualize and derive meaning from data more valuable.

To translate raw data into usable insights, many have formed centralized teams. This has all-too-frequently results in bottlenecks – delaying the data journey to decision makers who need quick access to insights.

To avoid bottlenecks, many companies are decentralizing their data strategies, with some responsibilities given to smaller and more agile teams who can focus on their own departmental needs. This strategy enables businesses to maximize efficiency and ensure data is accessed by the people who need it, when they need it.

Behavioral data use will mature

Behavioral data explains how end-users, customers or prospects interact with an organization’s digital estate. For instance, in retail, this could include a shoppers’ activity on a website, what items they look at and add to baskets and each individual step to the point of purchase and after.

One benefit of behavioral data is that it provides granular detail into interactions from a plethora of sources, such as web, mobile, email, SmartTVs and wearables. But overwhelmed by the sheer volume of data, marketers are shifting focus from simply collecting more, to collecting better and deeper behavioral data.

The shift to higher quality behavioral data has been partly brought on by privacy framework changes, as well as new event tracking solutions like Google Analytics V4. Another reason for the change is increasing data maturity, as more organizations realize that not every behavioral event is worthy of investment (in time, quality, and cost to capture). But regardless of the cause, the move will help organizations reduce churn, improve product analytics, provide more personalized customer service and more.

Prepping for the future of data management

Per Gartner, 78% of board of directors feel analytics will emerge as the top game-changing technology from COVID-19. To compete in years to come, organizations will likely need to adapt based on these trends. This evolution will not only help them today, but better prepare them for what is yet to come. So, if you haven’t prepped your data strategy yet to tackle the changing landscape, why wait?

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