– Data should be clean and tied to a larger strategy for it to be effective.
– Strategy is crucial before, during, and after data collection.
– Bias should be minimized in testing to ensure clean data.Prioritize strategy and clean data collection to ensure effective decision-making and avoid the negative consequences of relying on dirty data.Some things about data I wish people understood. Too often, I hear people say they are “data-driven” or take a “data-driven approach,” yet the basis of their data isn’t clean, nor does it tie into a larger strategy 95% of the time. Here are 7 things I wish people knew about data:
1. Just because you can collect it doesn’t mean you should.
2. Dirty data is next to useless.
3. Strategy comes before collection, during collection, and after collection – without it, nothing else matters.
4. You should overpay for strategy and clean data collection. If you don’t, you’ll be paying for it in other parts of your business.
5. Understanding data is 50% what the data tells you and 50% what it doesn’t tell you.
6. If you’re testing something, you have to remove as much bias as possible; otherwise, the data will become dirty.
7. Every decision made should be backed by data or at least have the ability to be backed up by data.
#zeropartydata #marketing #ecommerce #customerjourneyhttps://www.linkedin.com/in/jivanco