What is Media RepTrak?
Media RepTrak is a business intelligence system that measures the effects of the digital conversation on corporate reputation while providing actionable insights that can be used to make better decisions regarding corporate strategies, communications, PR and marketing.
What is Natural Language Processing?
Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and manipulate human language.
What is Machine Learning?
Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention.
How does Media RepTrak leverage Artificial Intelligence?
Media RepTrak uses NLP to analyze digital text media and categorize the data into the seven business drivers of reputation and assign a tonality score to each piece of data. Using thousands of hand-coded documents, the system automatically recognizes the drivers and calculates the Media Pressure Score.
What is a Media Pressure Score?
Media Pressure Score is a measure of online reputation. It is the emotional attachment of the stakeholders (customers, employees, investors, regulators) to the organization as evidenced by their digital conversations.
More specifically, the Media Pressure Score is a calculation that includes the volume and net sentiment of the conversation over trust, admiration, respect, and esteem in relation to the organization and is a leading indicator of reputation. The directionality of media pressure indicates the directionality of reputation in the future.
How does Media RepTrak fit into the suite of Reputation Institute’s products?
Reputation Institute has been collecting perception data for our customers for almost 20 years. With the addition of Media RepTrak, not only can we examine the digital conversation as it pertains to reputation in the present, we can examine the effects of that conversation on past perception analysis.
We can make the connection of what is being said in the media to how stakeholders will perceive an organization in the future. With that treasure trove of data, we can begin to explore more predictive analytics – and address conversations that will have a direct impact on a company’s bottom line before there is a negative impact.
How have companies found solutions with Media RepTrak?
Global Energy: A global energy company needed to identify reputational risks around the globe but struggled to cut through the noise of the vast amounts of data they were collecting. Media RepTrak uncovered insights around what drivers had the highest impact on overall reputation and which topics were shaping those key business areas.
Negative stories around an already weak perception on Citizenship were identified as a risk in need of mitigation and the recommendation was to promote and expand positive stories around innovation and performance.
Insurance: A large insurance company was concerned with the volume of conversations surrounding advertising on politically-charged news shows. Media RepTrak identified that the effects of that negative conversation were not significantly impacting the overall reputation. In fact, conversations around blog posts promoting a healthy lifestyle, while a lower volume, had a much stronger positive correlation towards Performance and Citizenship.
Energy: Read this Case Study to learn how a global energy company swiftly cut through the digital noise to identify reputational risks and opportunities
What's next for Media RepTrak?
We are excited to formally launch Media RepTrak in global English to existing and new customers as an expansion to their Perception RepTrak deliverables.
What does our roadmap look like? We are actively coding data in French and Italian to build the Machine Learning capabilities in those languages. We will begin the work on Spanish and Brazilian Portuguese next. And our Methodology team is hard at work integrating the media and perception data to create the standard of predicting reputation.
Learn more about Media RepTrak