Although this transition has taken place over the last 12 years, the most important distinction has been in regards to establishing clear objectives with tangible metrics and hypotheses.
At first, this was a struggle, as this was not a step regularly performed during the strategy and research phase of campaign development. At best it was a something considered towards the end of an on-going campaign to determine its effectiveness. As you can imagine, it was difficult arriving at a conclusion, because the goal was never clearly defined.
Subsequently, the metrics and the corresponding data points and collection methods were often missing or improperly executed, which led to a lot of head scratching and desk thumping at reporting time.
In contrast, data analytics’ begins with the end in mind, or at least it should ;). And when developing campaigns and/or data analysis projects, they start with a series of questions to help structure the program, so that the result upon completion is properly framed; for good or bad!