Hi everyone,
I’ve been working on implementing big data analytics in my organization, and while the initial results look promising, I’m struggling to determine how to effectively measure its return on investment (ROI).
I understand that tracking metrics is essential, but I’m unsure which ones hold the most weight. Should I focus more on operational efficiency, cost savings, revenue growth, or customer insights? Are there industry-standard metrics or frameworks that can help quantify the value analytics bring to the table?
Also, how do you account for intangible benefits like improved decision-making or enhanced customer experiences? These seem valuable but hard to measure in clear terms.
I’d love to hear from anyone who has experience in evaluating big data analytics projects. What metrics have you found most helpful, and how do you ensure you’re capturing the full picture of analytics ROI?
Looking forward to your insights and advice!
Thanks in advance!
Jonathan Jone
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To measure the ROI of Big Data Analytics, track metrics like cost savings, revenue growth, customer satisfaction, and operational efficiency. Key indicators include improved decision-making, customer retention, and trend prediction.
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