PRCA Measurement Conference questions answered by AI

Yesterday I spoke at the PRCA Measurement Conference as part of AMEC’s Measurement Month. I was part of a panel on Navigating the Future of Measurement and Insights moderated by Jonny Bentwood, Global Head of Data and Analytics, Golin. My fellow panelists were Mathew Denby of CC Group and Sarah Waddington of Wadds Inc.

To help kick start the debate Jonny shared some questions in advance. Jonny warned he was going to keep a count of how many times we mentioned AI, so I tried to avoid it. However, as yesterday was the first birthday of ChatGPT I thought it might be interesting to see what ChatGPT’s answers to the same questions were. All of the answers below are exactly what ChatGPT Plus using GPT 4 generated and haven’t been edited at all. I started the series of questions by telling ChatGPT I was on an expert panel to discuss Navigating the Future of Measurement and Insights at the PRCA Measurement Conference about the measurement and evaluation of communications.

What is the must have AI tool in your stack, how much does it cost and what is the use case?

“One essential AI tool for PR and communication measurement is a media monitoring and analytics platform. Such a tool employs advanced AI to track brand mentions across various channels, including online news, social media, print, and broadcast. It analyzes sentiment, reach, and the impact of your communication efforts. The cost of these platforms varies depending on the features and scale but expect to invest from a few hundred to several thousand dollars monthly. The use case for this tool is to measure the effectiveness of PR campaigns, understand audience sentiment, and refine communication strategies based on data-driven insights.”

How can current technologies help show the outcome of PR?

Current technologies can significantly enhance the measurement and visualization of PR outcomes. Here’s how:

  1. Analytics and Measurement Tools: These tools can track media mentions, analyze website traffic, and monitor social media engagement. They provide comprehensive dashboards that illustrate the reach and impact of PR campaigns.
  2. Social Listening Platforms: By tracking mentions across social networks, forums, and online communities, these platforms provide real-time feedback on public sentiment and the effectiveness of PR messaging.
  3. AI and Machine Learning: AI can analyze large volumes of data to identify patterns, predict trends, and provide insights into consumer behavior. This can help PR professionals tailor their strategies for maximum impact.
  4. Digital Attribution Models: Through attribution modeling, PR professionals can determine how various communications and touchpoints contribute to desired outcomes like conversions or brand awareness.
  5. Visual Analytics: Tools like Tableau or Power BI can take complex data and turn it into easy-to-understand visualizations, showing the direct results of PR activities.
  6. Content Performance Platforms: These platforms can analyze which pieces of content are performing best in terms of engagement, reach, and conversion, helping to optimize PR content strategy.

By leveraging these technologies, PR professionals can provide quantifiable evidence of their campaigns’ success, making it easier to justify budgets and refine strategies for future initiatives.

How can search be used to help insight?

Search technologies can be a powerful aid in gaining insights for a variety of applications:

  1. Market Research: By using search engines and specific search strategies, businesses can gather information on market trends, consumer behavior, and competitive landscapes.
  2. Consumer Insights: Search data can reveal what consumers are interested in or concerned about, based on the popularity of search terms. This can guide product development and marketing strategies.
  3. SEO and Content Strategy: Insights from search can inform SEO efforts, helping to understand how people are finding content and what keywords are driving traffic.
  4. Predictive Analysis: Analyzing search trends over time can help predict future behavior and trends, allowing businesses to stay ahead of the curve.
  5. Sentiment Analysis: Through searching and analyzing online discussions, reviews, and social media, companies can gauge public sentiment towards their brand or products.
  6. Crisis Management: Search tools can help in monitoring for potential PR crises by flagging negative content or spikes in search activity related to the company or industry.

In essence, search can be used to uncover a wealth of data that, when properly analyzed, translates into actionable business insights.

How can we use analytics to help during an issue/crisis?

Analytics can play a crucial role in crisis management in the following ways:

  1. Early Detection: Analytics can help in the early detection of a crisis by monitoring spikes in negative sentiment or increased volume of brand mentions online.
  2. Real-Time Monitoring: During a crisis, real-time analytics provide insights into how the issue is evolving and how it’s being received by the public. This allows for quick and informed decision-making.
  3. Sentiment Analysis: Analyzing the sentiment of social media posts, news articles, and other online content can help understand public perception and the severity of the crisis.
  4. Influencer Identification: Analytics can identify key influencers and opinion leaders who are shaping the conversation around the crisis. Engaging with these individuals can help manage the narrative.
  5. Impact Assessment: Post-crisis, analytics can assess the impact of the crisis on brand reputation and consumer behavior, which is vital for recovery strategies.
  6. Strategic Communication: Data from analytics can inform the communication strategy, helping to tailor messages that are most likely to resonate with the audience and mitigate the crisis.

Using analytics, organizations can gain a comprehensive view of the crisis, enabling them to respond effectively and minimize damage to their reputation.

Using analytics, organizations can gain a comprehensive view of the crisis, enabling them to respond effectively and minimize damage to their reputation.

What is available for predictive analytics?

For predictive analytics, there is a wide range of tools and platforms available, which can be used across various industries to forecast trends, consumer behavior, and business outcomes. Here are some of the offerings:

  1. Software Solutions: There are specialized software platforms like SAS Predictive Analytics, IBM SPSS Statistics, and Microsoft Azure Machine Learning, which offer advanced predictive modeling and data mining capabilities.
  2. Cloud Services: Cloud-based services like Amazon Machine Learning, Google AI Platform, and Oracle Data Science provide scalable predictive analytics solutions that can handle large datasets and complex algorithms.
  3. Open-Source Tools: Open-source programming languages like R and Python are widely used for predictive analytics. They have extensive libraries (e.g., scikit-learn, TensorFlow, and caret) that support various statistical and machine learning techniques.
  4. Data Visualization Tools: Tools such as Tableau, Qlik, and Power BI can integrate predictive analytics models to visualize future trends and outcomes.
  5. CRM with Predictive Analytics: Customer Relationship Management systems like Salesforce now incorporate predictive analytics to forecast customer behavior and sales trends.
  6. Specialized Industry Applications: There are also industry-specific predictive analytics applications designed for sectors such as finance, healthcare, retail, and manufacturing.

The choice of tool depends on the specific use case, the volume of data, the complexity of models required, and the level of expertise available within the organization.

The analyst is often the purveyor of bad news, how do you deal with this?

Dealing with the delivery of bad news as an analyst involves a combination of clear communication, empathy, and constructive feedback:

  1. Be Clear and Direct: Present the facts clearly without ambiguity. Ensure that the data is accurate and the analysis is thorough before delivering the news.
  2. Provide Context: Explain the reasons behind the negative outcomes. Contextualizing the data helps stakeholders understand the bigger picture.
  3. Focus on Solutions: Instead of just presenting problems, offer potential solutions or strategies to mitigate the issues.
  4. Be Empathetic: Understand that bad news can have emotional impacts. Be empathetic in your delivery and prepared for the recipient’s reactions.
  5. Encourage Dialogue: Allow stakeholders to ask questions and express their concerns. A two-way conversation can help in finding a collaborative path forward.
  6. Follow-up: After the initial discussion, provide ongoing support to monitor the situation and assist with implementing any changes.

Remember, the role of an analyst is not just to report on what is happening but also to help guide decision-making for better outcomes.