âWith public sentiment, nothing can fail. Without it, nothing can succeed.â
Digital listening and measuring votersâ sentiments have long been a distinction of successful political campaigns.
Gone are the days when social media was used for entertainment purposes only.
Even the slightest of sentiments portrayed by the people on the internet are being incorporated by effective political campaigns while crafting a successful campaign strategy.
Voters may be shocked by the fact that the status they upload on their Facebook or Twitter profile is used by political campaigns to measure votersâ inclination toward a particular political candidate.
This process, called sentiment analysis or digital listening, is extremely crucial for getting to know your targeted voters.
- Is your campaign really bringing change in peopleâs minds?
- What are the voters thinking about you?
- Do voters open your promotional emails or just ignore them?
- How long do they stick to your emails before leaving?
- How are people reacting to your latest promotional video on social media?
- Do your potential voters respond to your robocalls?
All of these questions can only be answered through a well-incorporated digital listening strategy.
Digital Listening: Our Data-Driven MantraÂ
Here are some of the ways we measure and analyze the digital listening data of the voters.
- By reviewing the retweets, sharing, likes, and dislikes on your social media posts.
- Analyzing the latest hashtags trends for and against you.
- Measuring peopleâs attitude and their sentiments behind their comments on social media posts.
Digital listening outpaces the traditional methods of sentiment analysis by optimizing the process.Â
Traditionally, the sentiments of voters have been measured by door-to-door campaigns and phone calls.
But the technological revolution demands the incorporation of digitalization in measuring the same.
We incorporate data scrapers for this purpose. Our scrapers scrape all the possible engagement behaviors of voters to feed them into our exceedingly organized databases.
This data is then analyzed through specialized and highly customizable dashboards, predictive models, and algorithms to get maximum value out of it.