As a PR agency
focused on technology, we have seen the rise of analytics. Unlocking insights hidden within those bits and bytes is now everyone’s business — regardless of job function or industry.
PR is no exception. In fact, for our closest peer — the marketing department —analytics is already deeply engrained. PR itself is seeing a steady increase in analytics-related activities within the function.
Yet, by and large, PR is still driven by non-analytical cues. We see this changing, though. Below are four ways how this change is coming to fruition.
Sensitive about sentiment
We know the benefits of social listening. It allows us to follow moods and sentiments in populations and offers us clues to how well our PR messaging efforts are performing. In a crisis, such insights are invaluable. They allow companies to steer and navigate past PR potholes and roadblocks.
Big analytics sentiment data allows you to go deeper into how sentiments are being shaped by key influencers and trigger points. These enable PR pros to target those points efficiently.
Sentiment analysis can also alert PR pros on potentially bad publicity—currently, many monitor using keywords. But analytics can allow PR pros to see patterns and identify adjacent keywords that may impact publicity efforts. It becomes crucial as 30% of company crises turn global within the hour, as Mentionlytics reported
Accurate earned media
Earned media is when the customer becomes the channel, says
Forrester. But the difficulty lies in measuring it accurately. It leads to unconvincing performance reports, often a contention point between the client and a PR agency.
Big data analytics can allow PR pros to get accurate measurements. For example, they can see how well blogs influence behaviors (like readers clicking on a product page) and how well third-party articles are driving awareness.
Essentially, what big data analytics does is link earned media with meaningful business outcomes, such as buyer behaviors or awareness. It also allows PR pros to optimize and finetune their PR strategies in real-time.
Historic data analytics
This is a new area, but quickly becoming important. With sophisticated analytics tools on hand and vast treasure troves of data to investigate, PR pros are in the position to analyze how and why past campaigns succeeded (and others failed).
This analysis is by no means an indicator of future performance. But as our financial peers (who coined the last sentence) will attest to, it offers an excellent step forward. This provides a level of assurance that C-level executives have long wanted.
Why is this important for PR pros now? Two reasons:
- The market is evolving quickly. The impact of PR initiatives that fail or succeed is now amplified. Understanding the fundamental triggers of the outcomes can allow us to quickly optimize or adjust a campaign. Often these triggers go unnoticed when PR pros move to other jobs, or companies change agencies. These triggers can sometimes begin in unexpected areas, like how a single Reddit user took on Wall Street hedge fund giants.
- It allows for the hyper-personalizing of PR messages. Before this, crafting multiple messages was laborious. So, you end up with one that tries to interest different audiences, like casting a wide fishing net. What gets caught is often difficult to predict. Hyperpersonalization helps to target different audiences or personas. Analytics can help to identify what those messages are by analyzing what influences or drives these audiences or personas.
A digital twin is a concept of creating a second digital entity (person, company, market) that embodies all the original personalities and/or characteristics. So, in the digital world, you have a twin.
For PR pros, digital twins allow them to test messaging on a digital twin audience or market. They can see the risks and create a more effective message house that targets all the different persons and audiences before they go-to-market (GTM) with their message house. Essentially, it offers valuable hind sights before an initiative.
In a fast-moving, digitally-crowded marketplace, digital twins are vital. PR pros can control their initiatives and get more strategic (instead of being tactical and reactive). Data science teams can even create AI models based on these to highlight patterns and map them to other data (like macroeconomic data) to understand shifting moods.
Data analytics is happening
Analytics in PR is not new. What I describe has already been done in some form. For example, the Cambridge Analytica fiasco
is heavy use of sentiment analysis and hyperpersonalization of messaging. As the saga showed, it can do harm in the wrong hands lasting a decade.
The hidden truth, however, is that analytics is here to stay. PR pros resistant to data analytics will only find themselves falling behind as the world dances to a data-driven beat.