LONDON — Snowplow outlined its top predictions on how data will reshape businesses in 2022. Compiled from the knowledge of its team of highly skilled data science, engineering, and analytics experts, and its experience working with data teams worldwide, the company shares its thoughts on the key regulatory, technology, and consumer changes that will influence how data is captured and used within organizations.
- Limits on third-party cookies will renew focus on first party data. Companies will shift spend away from advertising to more customer-centric approaches, driven by the roll out of Apple’s App Tracking Transparency (ATT) framework in 2021, and Google's commitment to phasing out third-party cookies by 2023. One of the most impactful changes to the data privacy environment for years, businesses will be forced to put new plans in place to understand and engage with customers, including a renewed focus on collecting first party data and building more direct data relationships with customers via loyalty programs, intelligent products and risk reduction.
- The role of the chief data officer will expand. The role of the chief data officer (CDO) will evolve from focusing primarily on technology and data management, to encompass culture and HR. Tasked with revamping the organizational structure and developing a data-driven culture, CDOs will need to be competent in soft skills as well as having technical excellence in engineering and analytics. Leaders will be expected to demonstrate skills, such as communication, negotiation, and conflict resolution, to help build capability and make data intrinsic within organizations, enabling them to compete with data native champions, such as Amazon, Netflix, and Auto Trader.
- The battle for data talent will erupt. 2022 will see a growing squeeze on data talent, especially for data engineers. Prompted by COVID-19, which forced organizations to understand their customers better and deliver digital offerings rapidly, companies will battle to secure the services of the most highly-skilled data practitioners. At the same time, the number of data roles and specializations will increase significantly, driven by architectural changes in the data stack. Job titles, such as data product manager, data governance manager, data/information steward, machine learning operations manager, and artificial intelligence operations manager, will become commonplace within large organizations.
- Businesses will need to reestablish the balance between personalization and privacy. 2022 will see a change in emphasis from understanding customers better to understanding customers “well enough,” or at an appropriate level to the customer's expectation of what is necessary to provide the service. One of the key drivers of dissatisfaction with Facebook (or Meta) is that the level of data capture built into its products is much higher than that necessary to provide the service, and this same sentiment will be reflected across businesses worldwide. Companies will need to ensure data democratization and balance personalization with privacy protection.
- Data teams will need to decentralize to drive efficiency. As uptake of machine learning and artificial intelligence rises, demand for easy-to-understand, easy-to-work-with data will skyrocket in 2022. This will include a real ramp up in the need for data catalogs, visualization, and analysis tools to help derive and visualize meaning from data. Many organizations have formed centralized teams to tackle the problem, but this has created bottlenecks for others who need to access these insights. Companies will need to decentralize their data strategy and teams to maximize efficiency, and ensure it is accessed by the people who need it.
Growing volume of data tools will call for better integration. The number of data tools within organizations will grow, with many using different tools for different areas including data analytics, testing and personalization. Alongside client-side tracking, we’re also likely to see organizations explore more tools on the server-side, while the semantic layer, which sits between data stores and is crucial for data mapping, will be a key focus for 2022.
To help reduce complexity, we’ll see greater collaboration between vendors to develop best-in-class tooling and enable data to flow freely between systems. More vendors will work together on single-use cases to create modern data stacks that enable businesses to integrate data and reduce the risk of project failure.
Behavioral data will come of age. 2022 will be the year behavioral data starts to come of age. Overwhelmed by the sheer volume of data available, organizations will shift their focus from simply collecting more data to collecting better and deeper data. This will translate into increasing demand for high-quality behavioral data, with benefits to businesses that make proper use of it, ranging from personalized customer service to product analytics and churn reduction.
Consumption and use of behavioral data within organizations will become more intentional and less indiscriminate, partly prompted by privacy framework changes and the emergence of event tracking solutions like Google Analytics V4, and partly prompted by increasing data maturity as organizations realize that not every behavioral event is worthy of investment (in time, quality, and cost to capture).
“2021 was a key year for data strategy with the shift away from third-party cookies, uptake of machine learning, and COVID-19 all forcing companies to seek new ways of better understanding and engaging with customers in the digital age,” said Alex Dean, Co-founder and CEO, Snowplow. “In 2022, data privacy rules and regulations will continue to be key in shaping how customer data is used, but demand for easily accessible rich behavioral data, plus the staff and modern data stacks to make use of it, will take center stage.”