In May PRSA Austin and AAF Austin hosted a dynamic panel on data and storytelling. Our panelists from the advertising and communication industry,  Chris Boyle, Senior Director, Data & Insights at Hero Digital and Talan Tyminski, Senior VP at Mach 1 Group, joined our guest speaker Tony Cheevers from Researchscape to discuss how to tell strong data backed stories using research and data.

The panel discussed the tools used to capture the data, where the data can be sourced and how surveys help to inform campaigns when there is data missing. 

Key Competencies for Data-Driven Storytelling/Campaign Building:

• Ability to derive strategic insights from data/Data interpretation skills
• Explaining complex data simply to reporters and stakeholders
• Utilizing public opinion polling research
• Ensure your organization is equipped with the tools to derive the data

Content marketers, publicists, and lead-generation specialists are increasingly turning to survey research to generate credible data to support their storytelling and more accurately target customers while providing metrics to their leadership team. Business leaders need feedback from their customers to make key decisions. 

We know that measurement and analytics are key for telling the story. What measurement and analytics are you using? The panel mentioned the importance of  sales data, social media data, open rates in your outbound marketing, website optimisation and more. We recap some of the highlights from the event below. 

Using research from surveys can help to shape or build a story or find the data points to tell that story, but shouldn’t be the sole purpose of a story. The research and data should be what supports your story. Data informs and validates why your campaign will be successful. It gives you the tools to segment an audience or shift when necessary. But to understand how and when to shift you must have the tools built to get the data.  Our panel shared some key tools that should be used:

• Importance of Tagging/Website Optimization — Tagging elements on your website can tell the story of what people are looking at/for to help form the response to your marketing or PR campaigns; not what you can do in the moment but using it as a learning experience and the data can build a playbook. 

• Segmentation and personalization — Building out personas using research tools; leverage google analytics to help you determine if a page or button is popular (needs to be tagged properly) and gives you insights on a customers journey on your website and allow you to customize your site.

• Customer acquisition journey — can you observe their journey to help get more info on telling the story/predict their behavior? This is where tagging, segmentation, surveys can help you as well as tools like GA4, SEO, and more. Challenging assumptions about customer demographics using surveys which can allow you to build Customer Personas. This is especially useful during a crisis. Auditing your audience's perceptions of a crisis using surveys can help determine your brand's response. 

• Story validation— When building strong stories, developing and testing headlines, ensuring story coherence and relevance, implementing UTM (Universal Tracking Metric) for better analytics and evaluation of the story will lead to more accurate measurement and evaluation for your KPIs. 

Lastly, the panel shared some skill sets important for professionals and students coming into the profession should have or build to be successful. They are numerous. Below is a general list shared by all the panelists. 

Data skills/software recommendation for new job candidates 

• Google Analytics (GA4)
• Google Ads
• SQL
• Python
• YouTube
• SEO/YOAST
• MOZ
• PR and MAR TECH STACKs (CRMs and Media Monitoring software)
• Wordpress, Website developer software
• Social planners ie Sprout, Sprinklr, Hootsuite, Buffer, etc. 
• Brandwatch for social listening 
• Know the lingo for the programs 
• YouTube 
• Certifications of any software even just online certs are always good 
• Google ads 
• SQL
• EXCEL
• Python
• Ability to interpret data - basically, why do we care about the data points?