Shift Communications
JANUARY 30, 2017
We’ve used the expression data-driven PR for quite some time now, but haven’t clearly defined it. What does data-driven PR mean? How do you know whether your public relations efforts are data-driven or not? To be data-driven is to make decisions with data first and foremost.
Deirdre Breakenridge
NOVEMBER 16, 2016
In a recent post , I suggested leveraging Nielsen’s research in order to create data-driven marketing and communications plans. That’s the front-end work every successful campaign entails, but the data cycle doesn’t end there. This is the challenge my friends at AirPR are solving, one data dashboard at a time.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Shift Communications
DECEMBER 26, 2016
As one of the only public relations agencies that is a Google Analytics Certified Partner, we are always looking to see how we can use Google’s tools and programs to strengthen both our PR and marketing teams’ efforts. Marketing Analyst. Casey Egan.
Onclusive
MAY 10, 2017
For example, at AirPR it’s all about PR attribution; we show PR professionals exactly how much site traffic results from a specific article or blog post, and how those visitors are interacting and engaging on their websites. In the end, working in PR can be as challenging as it is rewarding.
Shift Communications
SEPTEMBER 25, 2017
The second scenario where predictive analytics often fails is with black swans – events that are significant and impactful, but could not be foretold from existing data. While much business and marketing data is cyclical, seasonal, and predictable, we still encounter these events from time to time. Stay tuned!
Shift Communications
DECEMBER 4, 2017
As AI technology improves, reaching individuals at scale will be possible, and PR practitioners must adapt their integrated strategies to maximize success. Part 4: Search Marketing. Advanced PR Practitioners Embrace AI Fully. This trend will only accelerate as search engines become ever more intelligent. Christopher S.
Shift Communications
NOVEMBER 17, 2017
We’ll walk through how to use the indicated machine learning tools to project important the data series forward, highlighting important time frames. Furthermore, learn how to weed out the bad data, identify black swans, consider confounding variables and account for insufficient engineering. Marketing Analyst.
Expert insights. Personalized for you.
60 
Let's personalize your content