Marketers talk a good game when it comes to their data strategies but it seems most are simply kidding themselves about how mature their operations are, with the majority of teams still relying on outdated data and analytics practices.
That is according to a new study by Adverity, entitled “Marketing Analytics State of Play 2022: Data Capabilities and Aspirations”, which is based on interviews with nearly 1,000 marketers and data analysts across the UK, US, and Germany.
The findings suggest that marketing teams are still living in the past when it comes to data and analytics and far too often rely heavily on manual data processes to get insights from data.
For instance, more than two-thirds (68%) of professionals who strongly identify as analytically mature say their marketing reports are typically built on spreadsheets. Likewise, more than three-quarters (77%) of this group say they have yet to achieve a single, unified view of marketing performance.
And, while almost two-thirds plan to implement predictive modelling this year, and 56% plan to implement marketing mix modelling, these strategies require accurate, integrated data, and neither can be achieved in a meaningful way without a certain level of analytical maturity.
Marketers and analysts also have widely varying views on what technology they need, and even what they already have access to; three-fifths (60%) of analysts say they can run predictive analytics, but only 42% of marketers agree.
The report warns that a cultural shift must take place so that advanced tech does not gather dust, either because manual data integration undermines quality and eats up the time of the analyst, or because marketers do not have an advanced enough understanding to use the tech at hand to get value from their data.
One of the biggest trends in recent years has been the rise of the data scientist, however, it seems that many organisations are failing to use their skills, instead filling up their time with mundane work like manually pulling together data from different sources.
Not only does this undermine data quality, the report argues, but it also means that analysts are not able to use the advanced skills they were hired for. To be truly data-driven, businesses need to prioritise foundational data tools which automate integration before they sink time and money into more advanced tech like predictive analytics.
The study goes on to warn that unless marketers and analysts can take a more realistic view of their current capabilities and address the gaps in their foundation, it is unlikely that they will move the needle on predictive analytics.
The report concludes: “Today, being analytically mature goes far beyond spreadsheets and manual number crunching. Marketing forces at the top of the data maturity curve are making decisions based on predictive insights, often powered by advanced AI.
“For these teams, automated data integration and a single unified view of marketing data are a given. However, more than three-quarters of marketers and analysts who say they’re data mature still haven’t taken this first step towards data maturity.
“Marketing teams need to take a critical look at their current capabilities. Before they consider advanced tech like predictive analytics, they must fill the gaps at their most basic level.”
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