Establishing realistic baseline metrics

[kexej28769@nongnue]

The original theory — that there is a threshold for pitch count when comparing the relationship between pitch count and all other performance metrics — is confirmed by the data. The sample with a lower pitch count (less than 70) saw a positive relationship with the KPIs we wanted to reduce (e.g., churn rate, total days) and a negative relationship with the KPIs we wanted to increase (e.g., engagement rate, link count). The sample with a higher pitch count (greater than 71) saw the opposite — a negative relationship with the KPIs we wanted to reduce and a positive relationship with the KPIs we wanted to increase. Essentially, when campaigns with fewer than 70 pitches sent were isolated, scores improved in almost every metric.

When this analysis is applied to each of the 74 brazil number data from Q3, you’ll see roughly the same results, with Total Domain Authority again being the same. Campaigns with up to 70 pitches are associated with better KPIs when compared to campaigns with more than 71 pitches.

Vague or unrealistic expectations and goals will sabotage the success of any team and any project. When it comes to the effort put into each campaign, a purposeful, streamlined approach allows your team to work smarter, not harder.

So, what does that baseline range look like, and how do you calculate it?


A simple question helps answer what the baseline should be in this example: What was the average of each KPI for campaigns with fewer than 70 pitches?

We collected all 70 campaigns closed from our digital PR team’s pipelines in the second and third quarters of 2018 that had a pitch count below 70 and averaged each metric. Then, we calculated the standard deviation from the mean, which describes the spread of the data, to establish a range for each KPI — and that became our primary threshold.