Good, better and the best ! (Part I)
There seems to be nothing like a year of right or wrong data, it’s either accurate for a day, month or a week else we are on the right road to make it more accurate.
Quick thoughts on data credibility
1. Keep your implementation and tagging tight and right, regular QA cycles. There should be no gaps between the Tech and data teams specifically when code goes into production. “You reap what you sow”
2. Stop Comparing, most of the times it starts itching when people try to match numbers from one tool to other. Ask yourself few question.
- Why did we introduce the second tool
- What can we do better with each of the tools
Hopefully we are not spending greens on number of tools just to match our data but to derive more powerful and insightful analysis.
3. Different tools have different algorithms, thats what data scientists do, right? Trust me, lot of mathematicians, statisticians and computer programmers are spending their time to create these instruments, and luckily they all don’t think the same.
4. Be very specific about the metrics names and do not try to match them with other tools, the most simple ones Pageviews, Unique Visitors or Visits.