Industry executives and experts share their predictions for 2024. Read them in this 16th annual VMblog.com series exclusive.
2024 Data Trends: How Ready Are You?
By Derek
Slager, co-founder & CTO at Amperity
A lot has
changed in the tech landscape in the past 12 months. Data collection practices shifted
as new privacy legislation emerged, and as Google announced its plans to
disable cookies in 2024. AI has emerged as an essential companion for
streamlining business operations with new tools and resources disrupting the
market. These trends are sure to raise challenges-and opportunities-in the new
year. Here are the top three customer data management practices for IT leaders
to incorporate into their 2024 planning.
Pivot to a first-party data approach.
Third-party
cookies are becoming less valuable by the day, especially with Google's plans
to disable third-party cookies for 1% of Chrome users early in the new year. The behemoth also shared its intentions to continue
phasing out cookies for more Chrome users over time. Historically, companies have relied on third-party data
to build comprehensive customer profiles, but without it, they will need to
rethink their customer data strategy.
Using
third-party data was always an ongoing risk since companies don't own or manage
the process of data collection outside their own channels. Now that third-party
cookies are officially being phased out, brands must turn to first-party data
to understand their customers. Using first-party data ensures IT leaders can
gather customer insights using their own collection methods that are aligned
with best practices for privacy and accuracy. The end of the third-party data
era is near and IT teams that haven't begun transitioning to a first-party
approach are already behind.
Embrace a scalable customer data strategy.
Managing
customer data is no easy feat. Data is often formatted differently and comes
from various sources, making it hard to unify and organize. Another
complicating factor is that data is generated rapidly, often at a pace that
makes it challenging to keep track of with accuracy. Data also must adhere to
regulatory stipulations outlined in legislation such as the California Consumer
Privacy Act. On top of it all, companies must reconcile data to make sure
customer information is complete and accurate-which is easier said than done.
One of
the most common barriers to a scalable data strategy is the company's overall
data approach. When IT teams don't have a solid plan for processing and
organizing data, it becomes challenging to harness the information to its
fullest potential. Or, they might not have a reliable system to manage the
volume of incoming metrics-making the chore of "cleaning" it even more
cumbersome.
Inaccurate
and unorganized data is a huge business risk. Without reliable data,
organizations could end up launching marketing initiatives or making business
decisions driven by incorrect insights. For example, a company might spend
hundreds of thousands of dollars on an ad campaign that reaches the wrong
demographic or doesn't include a message that resonates with their ideal
customer. Adaptable, scalable systems and strategies that manage customer data
are essential to delivering effective marketing and business strategies,
especially as access to third-party data becomes increasingly limited.
AI will upskill workers and create demand for
new skills.
Like
other industries, the tech world is facing a shortage of skilled workers. In a recent survey, Deloitte found that "nearly 90% of
leaders said that recruiting and retaining talent were a moderate or major
challenge."
As the
industry reels from hiring struggles, companies that need to adapt to knowledge
gaps can use AI to augment software development and other work. AI can drive
more efficiency and effectiveness for certain tasks, such as integration and
coding, enabling workers to handle new projects for which they don't have
specific skills. Going back to the challenges of handling customer data, AI
tools can also ease the strain on IT teams by collecting, managing and
analyzing it-allowing companies to make the most of their headcount.
However,
we're not yet at a point where AI can assist with heavy-duty tasks without
clear, detailed direction. To be most effective, users need to learn how to
interact with the tool-including how to formulate prompts that will generate
the desired results. In the future, "prompt engineering" will become a desired
IT skill, especially as related to marketing and analyst positions. As AI
becomes a larger part of daily work, companies should seek employees who know
how to make the most of these solutions to perform their jobs more efficiently.
Navigating the road ahead.
Although
it's impossible to know exactly what 2024 will bring, IT leaders can glean
several important takeaways from the shifts that are already underway. With
major companies setting limits to protect user privacy, it's reasonable to
expect that more enterprises will follow suit. Workforce trends suggest that
hiring the right skill sets is going to be an ongoing issue as organizations
strive to augment their tech and IT talent. Companies can adapt to these
challenges by re-evaluating their customer data strategies and leveraging the
power of AI to fill knowledge gaps until they can hire the right candidates.
Both of these pivots will help IT teams lay the groundwork for success in the
year ahead.
##
ABOUT THE AUTHOR
Derek
co-founded Amperity to create a tool that would give marketers and analysts
access to accurate, consistent and comprehensive customer data. As CTO, he
leads the company's product, engineering, operations and information security
teams to deliver on Amperity's mission of helping people use data to serve
customers. Prior to Amperity, Derek was on the founding team at Appature and
held engineering leadership positions at various business and consumer-facing
startups, focusing on large-scale distributed systems and security.