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Important Data Analysis Tips That Every PR Manager Should Follow

Important Data Analysis Tips That Every PR Manager Should Follow

In a data-driven world, working with raw data is an essential process for every business, and so is for PR. Selecting, structuring and analyzing data helps journalists, PR managers, and the audience to gain valuable business insights, spot trends, and provide a better argumentative groundwork for pitches and articles. Let’s dive deeper into the matter. 

Intersection of Data and PR

Why is it so important for PR pros to work with data and actually know how to do it properly? Well, think of advantages data can give you and your client:

  • Data can easily highlight your client’s brand, demonstrate the uniqueness of it,  and make it stand out from all the competitors. 
  • Data establishes a sense of trust in the eyes of the audience when shown in dynamics and when provided with demonstrated research. 
  • Data is always a bait for a journalist — it helps tell your brand’s story and attract attention from the media. Moreover,  using statistics and facts can make almost any pitching more argumentative and memorable.

However, the wrong interpretation of data can severely damage the reputation of a PR manager and journalists — not to mention your client, and spread misinformation to the audience. Here are important steps that all PR managers should know when it comes to working with numbers and data:

1. Data Selection: Study Your Client and The Market

Here’s where PR managers address the elephant in the room by studying the client’s business and selecting data based on current and previous indicators. It’s important to ask relevant questions, such as: Where does this data come from? What were the indicators in previous months? How does this data help your client stand out from competitors and highlight  their value?  PR managers should be able to explain this information as it’s the main resource passed on to journalists to work on a factual pitch. 

For example, if it’s a cryptocurrency exchange service, it’s important to study its business and the current market thoroughly: what are some of its benefits compared to other exchanges? How’s the trading volume? How many transactions are taking place? What currencies does it support? Which regions are served?

2. Data Structuring: Organizing Your Client’s Data

Once the data is collected, structuring it is the next step to analyze it correctly to provide the journalist with the most relevant data. Using a spreadsheet or data structuring software systems are helpful as information can be organized by region, types of transactions and volume, previous indicators, and more. This will help to draft the information according to the target audience and your goals.

3. Data Analysis: What Gives Value to This Data?

Once structured, it’s useless to throw data just for the sake of it. PR managers should ponder what the collected data means for journalists and the target audience — and comparison would help with it. The audience wants to know if there’s an increase or decrease in numbers and statistics and how it affects businesses, markets, and organizations. Data comparison helps to provide a more comprehensive perspective and increase the value of the information.The important thing to remember here: data by itself does not disclose the full picture. It just helps to distill what you can do with your client’s brand based on raw data, identifying key market patterns and imputing valuable insights into the client’s pitch to promote its brand. Therefore, data should be integrated into a story that helps to promote your client’s brand, and be synchronized with other types of content you produce.

Closing Words: The Importance of Data Analyzing for PR Managers

To sum up, data is a very important type of information that can boost the quality of PR materials. However, the misuse of it and the incorrect interpretation brings certain risks, such as drawing wrong conclusions, manipulation of information and even PR crises.Therefore, PR pros should educate themselves on working with data and numbers, and moreover,  apply this knowledge into everyday practice. We can do it by following the basic steps of working with data — collecting, structuring, and analyzing data.