Report: How data maturity affects your bottom lineseptembre 3, 2022
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The most mature digital product analytics teams (those that best leverage digital analytics tools and processes) have 2.5 times greater improvement of business outcomes across the board than the least sophisticated teams. When measuring revenue improvement as a business outcome, the most mature (also called leaders) exceeded the least sophisticated (also called laggards) by a difference of almost 28%.
Independent research from a newly released IDC white paper, sponsored by Heap Analytics, “How Data Maturity and Product Analytics Improve Digital Experiences and Business Outcomes” surveyed digital experience decision-makers to gain a deeper understanding of the maturity levels that currently exist in the adoption and use of digital product analytics technology, culture and practices.
The paper focuses on data maturity’s impact on business outcomes, as well as determining best practices and opportunities for improvement. The research verified that increased data maturity — meaning how well a company uses data and leverages it in its decision-making — resulted in increased revenues and profits, better efficiency, higher NPS scores and lifetime customer value.
Data maturity best practices
The report also revealed the best practices of data maturity leaders, including the fact that 98% of leaders have a good to excellent understanding of customer journey friction points, while only 29% of laggards reported they have a good-to-excellent understanding in this area.
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In regard to automation, 80.1% of leaders fully automate their data validation, data access policies, and dataset management processes, while only 3.2% of lagging organizations fully automate these processes. 72.1% of lagging organizations are using manual processes or basic automation for data validation, data access, and dataset management.
In addition, 84% of leading teams get answers in minutes or hours compared to only 3% of laggards; and 89% agree their organization celebrates learning from experimentation, while 77% of lagging teams feel their organization doesn’t celebrate experimentation.
However, the study also found that there were areas for improvements for all companies. In the most surprising findings, 69% of all companies say that decisions are often driven by the HIPPO (Highest Paid Person) without regard for data.
A majority (81%) of leading companies believe that they could do more with the data that is made available to them.
Areas of improvement for lagging companies include access to the correct tools or formal training processes on data analytics. More than 65% of lagging companies lack access to tools like session replay or tools to identify specific areas of friction in the user journey, and only 31% of lagging organizations have formal training processes in place, compared with 71% of leaders.
To unveil these findings, IDC surveyed more than 600 digital product builders to determine their data maturity levels and use of digital analytics technology, as well as their culture and practices. IDC then analyzed the survey responses and identified four maturity groups (lagging, progressing, advancing and leaders), and ranked the responses from lowest to highest maturity level.
Read the full report from Heap.
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