Report: How Data Maturity Affects Your Bottom Line

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The most mature digital product analytics teams (those that best leverage digital analytics tools and processes) see 2.5 times more improved business results across all areas than the most mature teams. less sophisticated. When measuring improved revenue as a business outcome, the most mature (also called leaders) outperformed the less sophisticated (also called laggards) by a difference of nearly 28%.

An independent study from a recently published white paper by IDC and sponsored by Heap Analytics, “How Data Maturity and Product Analytics Improve Digital Experiences and Business Outcomes,” surveyed decision-makers in of digital experience to better understand the levels of maturity that currently exist. in the adoption and use of digital product analytics technology, culture and practices.

The document focuses on the impact of data maturity on business outcomes, as well as identifying best practices and opportunities for improvement. The study verified that increased data maturity, i.e. the way a company uses data and leverages it in its decision-making, led to increased revenue and profit, improved efficiency , higher NPS scores and lifetime customer value.

Data Maturity Best Practices

The report also revealed best practices from leaders in data maturity, including that 98% of leaders have a good to excellent understanding of customer journey pain points, while only 29% of laggards have reported having a good to excellent understanding in this area.

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When it comes to automation, 80.1% of leaders fully automate their data validation, data access rules, and data set management processes, while only 3.2% of organizations trolling fully automate these processes. 72.1% of laggards use manual processes or basic automation for data validation, data access, and data set management.

Furthermore, 84% of leading teams get answers within minutes or hours, compared to just 3% of laggards; and 89% agree that their organization celebrates learning from experimentation, while 77% of teams lagging behind believe that their organization does not celebrate experimentation.

Needs improvement

However, the study also revealed that there were areas for improvement for all companies. In the most startling results, 69% of all companies say decisions are often driven by HIPPO (highest paid person) without considering data.

A majority (81%) of large enterprises believe they could do more with the data available to them.

Areas of improvement for laggards include access to the right tools or formal training processes on data analytics. More than 65% of laggards lack access to tools such as session replay or tools to identify specific areas of friction in the user journey, and only 31% of companies behind have formal training processes in place, compared to 71% of leaders.

To unveil these results, IDC surveyed more than 600 digital product creators to determine their level of data maturity and their 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, Progressing, and Leading), and ranked the r...