So you want to create an event tracker? You've come to the right place!

Event trackers can be used to monitor conversation around a scheduled event like a conference eg. COP27 or around a broader cultural event eg. "Black Lives Matter".

When tracking an event it is important to capture the build up of conversation in anticipation to the event, the real time spikes and the post event analysis.

Today we are going to use the the iconic Met Gala as our example, to guide you through our recommendations for event tracking in Pulsar TRAC!

It is first, and arguably, most important to identify terms you would like to use.

Think about the event name, hashtags and @handles. Keep in mind at this stage how big you expect the conversation to be, are you tracking a global cultural event which will consume a lot of data or a niche industry event? This should guide you with your selection of keywords and your approach to building your search.

As we are focusing on Met Gala, we want to think of the different ways people may talk about it. For this example:

Next we need to take these keywords and build them into our Boolean logic.

For those new to Boolean logic, this guide will be a helpful place to start:

Below in step 2, we walk you through the thinking for creating a Boolean search query for tracking the Met Gala.

Let's start with the keywords we have just identified. When inputting these into Boolean, be sure to note that when adding a phrase, it must be contained in speech marks. For example, "Met Gala", "Metropolitan Museum of Art Costume Institute Gala" and "Met Ball".

Use brackets to group keywords together based on their relevance to each other. In this case, group the variations of "Met Gala" together, like this:

Determine if there are any additional keywords you need to include alongside your current expression to narrow your query. To narrow your query you will use an AND operator. For example, is there only a specific element of the event you are interested in capturing eg. references to the "red carpet" or a specific designer or celebrity eg. Chanel or "Kim Kardashian". You may also only want to focus on a particular year for an annual event, so consider if you need to reference the year in your boolean or if that year has a particular hashtag. It might be that just tracking the name of the event over the specific time frame is enough to keep it focused on the particular year.

Add the AND operator between the two groups of keywords:

If there are any terms that you want to exclude from your search, use the AND NOT operator. For example I might not want mentions of protests on the red carpet at the Met Gala.

Group your current Boolean expression in a pair of brackets and add the AND NOT operator followed by the terms you want to exclude:

Using this query, TRAC will retrieve conversations that include variations of the Met Gala and also a mention of the red carpet. It will exclude pieces of content that include mentions of protests.

Within TRAC, you can further refine your query by applying advanced operators. For example, geographic locations or exclusions. You will want to consider adding these if you anticipate your event to capture a conversation larger than your data allowance.

You can do this with a combination of the following example operators:

Combining all the above, your expression will nice and refined and look like this:

Using this query, TRAC will retrieve conversations that include variations of the Met Gala and also a mention of the red carpet. It will exclude any mentions of protests. It will only collect posts in English and from the United Kingdom. Where we are tracking the conversation in real time from X, it will only capture 20% of the conversation via a random sample.

Once you have loaded in your data, it's time to analyse and extract insights. Take advantage of TRAC's visualisations, sentiment analysis, and topic clustering features to uncover patterns, trends, and sentiment surrounding the Met Gala. Identify popular designers, celebrity collaborations, or notable moments that generated significant buzz.

Analyse the overall sentiment surrounding the Met Gala to understand the public's perception.

Content Insights > Timeline > Sentiment Over Time

When looking at the full event time frame, analyse when the conversation started building, where the spikes were, what drove them and how long the conversation continues. Use the keyword filter to focus your volume analysis on specific elements of the event eg. track the popularity of fashion trends, designers, or celebrity appearances over time to identify emerging themes.

Content Insights > Timeline > Content Over Time

If you are looking at a global cultural event, map the geographic distribution of conversations to identify areas with the highest engagement. This visual is also overlaid with sentiment, so see if certain locations are driving negativity/positivity around the event. Click on the sentiment bubble to see the results!

Content Insights > Locations > City Breakdown

Identify influential users that generate significant buzz during the event. We recommend toggling the Influencers chart by the visibility metric as this measures the impact of a user rather than just by volume of posts they've contributed. Find out more below:

Audience Insights > Influencers

Set up alerts for volume changes, specific keywords spikes or sentiment shifts to stay informed of important developments around your event.

Decide how sensitive you want your alert to be by selecting either a percentage or total number of posts to trigger the alert. If you are keeping a close eye for crisis comms management, go sensitive and set by the hour.

Reports > KPI Alerts

A custom dashboard that provides an overview of your selected key metrics, sentiment, themes and a variety of custom charts (see examples in custom reporting), is the best way to summarise your event.

You can schedule your dashboard report to send on a regular basis. For example, you might need daily summary reports as the event plays out.

Reports > Create Dashboards > Choose a Template or Create Your Own > Click Email > Schedule it to report on a frequency of your choosing.

Visualise the volume of specific keyword mentions over time to identify spikes in conversation. Here we use the example of different celebrity mentions over time, showing Lady Gaga (blue), Lizzo (yellow) and Blake Lively (Red).

Add Chart > Custom Charts > Create From Scratch > Select Spline >

Name Segment > Open Filter > Add Keywords (In this case a Celebrity name) > Apply

Report on positive and negative sentiment to gauge the overall sentiment of your event. You could also add certain keywords to your filter to report on sentiment towards certain elements of the event. For example, were people overall positive about the venue or speakers?

Add Chart > Custom Charts > Use Template > Select Sentiment Split

To focus the sentiment chart to a specific theme, open Filter for each segment > Add Keywords > Apply

Generate a share of voice pie chart to visually represent where most conversation occurs related to your event. If your event recurs annually, this will help you to focus your strategy in the right places next time.

Add Chart > Custom Charts > Create From Scratch > Select Pie >

Name Segment > Open Filter > Target > Assign 1 Source Per Segment > Apply

Armed with the insights gained from TRAC, you can now take actionable steps. Utilise the data to inform future event planning, use alerts to keep close eyes on the event conversation in real time and report back on the learnings of the event. TRAC empowers you to make data-driven decisions and optimise your event tracking efforts.

Enjoy!