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Evaluating Marketing Campaign Performance with Sentiment Analysis
Marketing campaigns are designed to drive one or more specific actions by the public. In the private sector, they are typically intended to promote a brand, product, or service. In the public sector, they are often aimed at raising awareness or educating the public (e.g., promoting healthy eating habits, vaccinations, smoking cessation).
Marketing campaigns may take many different shapes depending on the targeted audience, ranging from TV or radio commercials to printed media ads, digital ads, sponsored content, promotional videos, or others.
But whatever goal or shape a marketing campaign may take, it is most important for marketers to be able to:
- Measure its effectiveness and ROI: how much buzz did it generate? How many people liked it or disliked it?
- Capture insights from the public response: what specifically did people like or dislike?
- Did the campaign lead to more sales?
All of this is highly valuable information not only to evaluate and refine the current marketing campaign but also to inform future campaigns. It is also critical to detect any unexpected response early to be able to correct course, should the campaign turn out to cause an unintended negative reaction.
How Does Sentiment Analysis Help Evaluate Marketing Campaigns?
Sentiment Analysis, also known as opinion mining, is about detecting likes, dislikes, emotions, and opinions and is often applied to social media, reviews, blogs, forum posts, chats, and similar sources. Sentiment Analysis has many applications, both for industry and government, and is especially well suited for measuring marketing campaign performance quantitatively and qualitatively. Here is how:
- Buzz. At the very basic level, Sentiment Analysis identifies the various mentions of a brand or concept and makes it possible to track those over time. Marketers can monitor the number of mentions of a product, brand, promotional hashtag, or slogan before and after a campaign to gauge how much and for how long the campaign and its content resonate with the public. But buzz alone is not a reliable or sufficient measure of a campaign’s success. In fact, a high level of buzz could be a sign of trouble rather than success, as when an ad becomes unintentionally controversial or the object of widespread criticism.
- Likes and Dislikes. Sentiment Analysis detects positive and negative sentiment around a brand or concept. At a very basic level, it identifies positive and negative language. At an advanced level, through Entity- and Aspect-based Sentiment Analysis, it pinpoints the specific aspects that those positive and negative sentiments are about. For instance, the public may love the soundtrack of a commercial or the look of a new car model, but they may think that the dialogue in a commercial is boring or, worse, sexist or racist.
- Intent. Advanced Sentiment Analysis detects language suggesting intent and sentiment-based actions like intent to buy, positive or negative recommendations, and boycott.
- Large Data Sample. Advanced Sentiment Analysis can scale to Big Data size, making it possible to process massive amounts of data in real time. Naturally, the larger the amount of data and the faster it can be processed, the more reliable, useful, and timely the insights will be to refine the current campaign and prepare future campaigns.
- Analytics. Advanced Sentiment Analysis normalizes the extracted information thus enabling data aggregation and quantification to provide the overall view from a large collection of content. A dashboard presents multiple views of the sentiment information through various types of interactive graphs and charts. Sentiment data can be sliced and diced as desired, for instance by positive and negative aspects, and, if desired, the user can drill down to the source text for inspection and further analysis. Other useful charts show sentiment evolution over time through a sentiment timeline. Using location metadata and automated geocoding of mentioned place entities, sentiment can be plotted on a map to show, for instance, hot spots of support or disapproval.
To learn more about how NetOwl’s advanced Sentiment Analysis can be used to evaluate your marketing campaign quantitatively and qualitatively, contact us today.