The recent innovation in artificial intelligence will fundamentally change the PR pros’ toolbox. Here we discuss how predictive analytics, sentiment analysis, and reporting will soon get an even bigger boost, allowing PR to concentrate on the work they do best.
There’s no reason to fear yet… except for these Boston Dynamics robots.
In reality, you don’t need to wait long to see how AI can improve your personal life. From calling a rideshare to arrive in minutes or getting an answer from Siri, AI is already saving us all time and money while making our days more convenient.
But what about when it comes to our work?
When it comes to transforming industries, AI has (so far) received a bad rap for its potential to replace humans and take away jobs. And in some industries, this may very well be the reality. But in public relations and communications, our prediction is that it will be actually the opposite—that AI will pair with you to make you far more data-driven, streamline your workflows so you can focus on what you do best, and help you amplify your message at a scale far beyond what is imaginable.
Let’s take a look at three ways AI will enhance public relations, with a few you can already start using to make your work faster and more effective:
We all know that the way we currently reach out to influencers (both social and news media) en masse leaves a lot to be desired. It’s a two-sided problem: PR professionals don’t have enough time to curate hyper-relevant lists or tailor their messaging to each influencer directly, so influencers often get hit with a barrage of generic pitches that they end up just ignoring.
Imagine a world where using an AI technique called natural language processing, we can analyze the messaging of the PR professional’s pitch to find out that it is a new product launch about golfing targeted at millennials. In the meantime, we can also analyze previous articles written by social and news influencers to find those who write often about product launches, golf, or millennial consumer tastes. We can automatically curate a list of these specific influencers to coordinate a much more relevant match and, thus, a much higher likelihood that the influencer will be interested in covering this story. Over time, as you maintain relationships with these influencers, the AI can even sort out which influencers have higher open and response rates to your pitches and suggest them for future, even more effective campaigns.
For an overview of how you can already use natural language and pitch analytics to automate pitch personalization, watch our webinar on media outreach best practices.
It’s no secret that our information world is becoming more and more visual; it’s rare these days to find important news or social posts that don’t contain images or video. In fact, think about the number of times your brand, product, or service may appear in an online photo without the article or post explicitly tagging you!
Cutting-edge image recognition technology cannot only automatically detect objects, scenes, and faces in images, but actually name the people, brands, and products within. Take this photo, for example:
Image recognition can ensure that in addition to monitoring text mentions on social media and news, you are capturing visual conversations about your brand. This is particularly helpful for visual mediums like Instagram and Pinterest, where consumers may be posting photos about highly positive or negative experiences with your company that you currently may not be aware of!
Today more and more PR pros are looking to make data-driven decisions based on campaign performance, social listening, and competitive benchmarking. However, building reports on these activities can require wading through data from a variety of sources, building spreadsheets, and turning charts into easily digestible graphs. Media intelligence tools are already here to automate these process. But what about the analysis and lessons learned. By detecting patterns and changes over time, AI already lets us translate trends into words, as in Meltwater’s new Insight Reports Builder (in just 15 minutes, we can give you a personalised tour!)
A key tool for understanding brand perception in any modern PR report involves looking at audience sentiment. Sentiment analysis, already an important part of any PR professional’s media intelligence toolbox, lets you gauge how customers are feeling about your product, service, or brand as a whole. However, traditional methods of sentiment analysis either rely on a ton of tedious manual work or inaccurately gauge an article based on its cumulative sentiment (think of it as essentially summing up all the positive and negative words in a document).
Not everything is as positive as Leslie Knope.
Luckily, new advancements in natural language processing will make sentiment analysis more accurate and actionable. We can now drill down to each specific person, product, place, or company in an article and analyze the surrounding sentence for how this writer feels particularly about this entity.
Consider a simple sentence like this:
“That Subway commercial was annoying and too long, but the Doritos ad was amazing.”
Older techniques would consider this sentence negative, as there is one positive word (“amazing”) and two negative phrases (“annoying” and “too long”). But if you managed communications at Doritos, a negative tag on this sentence (if buried within one of many long articles) would’ve made you potentially miss a great endorsement and throw off your reporting. The next generation of sentiment analysis would discern that this sentence is actually positive in relation to Doritos (and a win for your team!).
As you can see artificial intelligence is an extremely helpful enhancement, not a mysterious looming threat. When we let the machines do the heavy lifting—the counting, the categorizing, the detecting—it frees us up to do even more of the strategic and creative work we signed up to do in the first place. Let’s look forward to the amazing developments to come in this field in 2018 and beyond.