When using data to make decisions in marketing, there are many factors that must be taken into consideration. This is necessary to ensure the decisions are accurate, and that they properly address every piece of available information.
-Ensure Your Sample Size is Large Enough
Sample size is critical when analyzing data because too small of a sample can have very detrimental effects. When small sample sizes are used, outliers in the data have much more weight, and therefore offset the central tendency (average). In most situations, the greater the sample size, the more accurate the data will be at representing the total population.
-Make Sure Your Testing is Long Enough
Testing needs to cover an appropriate amount of time to address seasonality and other changes throughout the year (Black Friday, Christmas, New Years, etc.). This is mainly targeting sales data, where revenue would be greatly increased during holidays or changing seasons, but would not effectively represent the year.
-Use Appropriate Attribution Modeling
Attribution models basically decide where the credit should be given for a sale, conversion, site visit, etc. For instance, first click gives all the credit for the sale to the first interaction the customer had. Last click gives all the credit to the last place the customer clicked before the sale was made. Linear attribution gives an equal amount of credit to each interaction throughout the sale process.
-Make Sure Conclusions are Unbiased
Conclusions made based on the data collected need to be completely unbiased and free of errors. This will ensure the data can be used effectively, especially when the data is not what is expected.
