CES 2019 Social Data Analysis + Why it Can Pay to Get Banned
By Gemma JoyceJan 14th
Published May 30th 2014
The marketing of brands, products, and services cost an incredible amount of money – $1 trillion a year, to be exact. Campaign tracking is vital to ensure a strong understanding of how successful or useful a marketing campaign has been.
As marketers in the digital age, we now have the ability to use the power of the Internet and online conversation to measure a campaign’s impact.
Listening to organic online responses to different marketing activities, campaign tracking can help marketers compare how well each of their campaigns resonate with their audience in a way that they’ve never been able to before.
A campaign can be dissected into multiple areas of interest:
In our recent webinar “How to Use Social Media Monitoring for Campaign Tracking” we took a look how you can use Brandwatch Analytics to answer these types of questions and get a richer understanding of the impact of your marketing campaigns by using categories, rules and sentiment analysis.
To illustrate the use of these capabilities, we can examine the clothing company H&M, and the five global campaigns it released, each centered around the use of celebrities as models.
With big names like David Beckham, Beyonce and Lana Del Rey, the brand will likely want to how effective each of these sponsorships was.
To do this, we can employ something at Brandwatch we call a category. A category will structure your Query data into multiple areas of conversation. So, we would create five separate categories for each of the five celebrities.
Once we have built this framework, we can further dissect the data by creating subcategories for each category. All subcategories should be relevant to your overarching category.
Once you have identified the conversation topics that you want to further explore, you can then create and assign a Rule to each subcategory. A Rule is going to instruct Brandwatch to separately segment that topic from the entirety of your data set, giving you quick access to those mentions.
Building a Rule is much like building a Query. It uses the same type of logic by using keywords and operators – meaning you can create a Rule as simple or complex as you’d like.
If we want to understand the influence that Beyonce has on our audience in inspiring a commercial intent, we can create a rule using “intent to purchase” language, like below:
By applying this Rule to our general data set, we can now see specific mentions like this:
We now have the total number of mentions created by each celebrity in the campaign, in addition to the amount of consumer purchase intent that was driven by each.
We know that conversation volume is certainly a useful metric in understanding a campaign’s performance. However, big doesn’t always mean better.
In the example used in the webinar, we saw that H&M model David Beckham drove more mentions than Beyonce, but Beyonce generated more positive mentions than David.
Through the use of categories, rules and sentiment, we now have a much richer and complex understanding of a campaign’s performance.
Advanced social analytics platforms that allow this level of segmentation gives us the power to pull the relevant mentions from the general chatter. With some clever use of the platform, we can go beyond simply finding which celebrity drove the most mentions, to which drove the most business and the most positive sentiment.
If you’d like to see how Brandwatch can help your campaign tracking, get in touch for a free live demo.