Public relations and communications professionals not only safeguard the reputation of brands, but they also have the important job of helping to shape the ever-evolving, external perception of brands. In order to show a brand where they need to go, PR professionals need to level-set the current state of brand perception. These initial benchmarks will help PR professionals (and the brand!) guide long-term strategy to make informed decisions about what is or is not working. In theory, this focus on measurements creates an outstanding system in which people create informed strategies, strive to achieve set goals and optimize based on results. Sounds familiar, right? Perhaps this is something you’re already doing in theory, but I’d argue the system you’re currently using is antiquated.
Yes, the current system is flawed because of what is being measured to inform strategies, set goals and optimize. PR and communications professionals have relied on a multitude of metrics throughout the years – social engagement rate, website referral traffic, quality scores, advertising equivalency scores and more. Two metrics, more than any others, have stood atop of the PR measurement mountaintop – Impressions and Share of Voice (SOV).
- Impressions are a measure of how many times an article/mention/collateral has truly been seen.
- The problem is: Many reports of impressions are not true impressions, but rather potential reach. Many people report on impressions, but they are actually using the circulation numbers for a paper, the unique monthly visitors for a website or the total Twitter followers for the user who published the tweet. These community size numbers are not actual eyes that have seen the post, they are simply the potential audience that would have seen the post based on the source’s community size. Declaring those measures as impressions is false and can be misleading.
- SOV is a measure that is intended to see how much conversational (media and posts) attention one brand has relative to a competitive set. The most common way of calculating SOV is to weigh the total number of articles/posts for one brand against the total number of articles/posts for all other brands in the competitive set.
- The problem is: Not every article or mention is created equal. A positive article in the New York Times should not be weighted the same as a negative Facebook post that goes to a community of 12 people, but in the model above they are viewed with the same value.
Brands are using these metrics to inform their reputational decisions because they are easy to get in an automated way and purport to paint an accurate picture, so the big problem with these measures is that decisions are being made based on misleading data.
The best way to course correct is to adopt new, contextual metrics that fulfill some of the same measurement needs, but do so with greater validity. An automated equation can still be created that includes the two primary measures above as well as other contextual cues depicting the value of each article or mention.
At FleishmanHillard we have started using the Value-Driven Share of Voice (VSOV). This single measure takes into account:
- Volume of posts
- Potential reach of each post (UVMs, Twitter followers, etc.)
- Whether the post was positive or negative
- If the post had message adoption from the marketing materials/language
The greatest weight is given to positive posts with higher potential reach and message adoption. Less weight, but still positive value is given to neutral posts even with low potential reach and no message adoption. Negative value is given to negative posts that have a detrimental impact on the brand’s reputation.
This metric was created for one simple purpose – contextual accuracy. By combining these variables together and looking at a more complete picture, brands are better able to make reputational decisions based on the scale of positive or negative impact.
In the end, measuring the results and impact of a PR or communications program is intensely important, but only accurate data will result in accurate decision making.