Primeras impresiones de Google Analytics Intelligence

Pese a que ya hace unas cuantas semanas que podemos disfrutar de las nuevas funcionalidades que se han lanzado en Google Analytics, todavía no he tenido tiempo para poder jugar con ellas, así que he preferido compartir con vosotros un artículo que publicaron en Web Analytics Demystified sobre las posibilidades que ofrece Google Analytics intelligence

1. An approachable way to determine confidence intervals via their “Alert Sensitivity” slider. While the implementation doesn’t necessarily impart the level of detail some folks would like, the slider mitigates the prevalent concern that “people won’t understand confidence intervals.”
   Great visual cues for alerts, especially when statistically relevant changes are not obvious based on traffic patterns. Sometimes traffic patterns just look like hills and valleys, even when something important is happening — for example, the next figure shows two alerts at the lowest threshold setting on September 16th that, upon exploration, turned out to be great news (that I might have missed otherwise.)
2. Good visual cues regarding the statistical relevance of the insight being communicated. This is tough since Google is trying to present moderately complex information regarding the underlying calculations and how much emphasis you should be putting on the insight. By showing a relative scale for “significance” I think Google has more or less nailed it.
3. Google Analytics finally starts communicating about web analytics data in terms of “expectations” instead of absolutes. All of us (present company included) have a tendency to get wrapped up in whole numbers, hard counts, and complete data sets. But we also know that Internet-based data collection just isn’t that accurate, and so any push to get us to start thinking in terms of predicted ranges and estimates is a step in the right direction. For example, I love knowing that on a given day Google Analytics “expects” between 311 and 388 people to come to my site from the UK!
4. Lots more, including the ability to pivot the views and look from a “metric-centric” and “dimension-centric” perspective, the ability to aggregate on day, week, and month, and the ability to add your own custom alerts based on changes in traffic patterns. Perhaps ironically this last functionality (”Custom Alerts”) is how we’ve all historically thought about “Intelligence” in reporting, and while useful seems somewhat weak compared to Google’s stats-based implementation.