Social media platforms are no longer considered as just tools to market your products; it has evolved into something that is much more comprehensive. With over 1.94 billion monthly users on Facebook, 500 million monthly users on Instagram and over 300 million monthly users on Twitter, it provides businesses the opportunity to get to know what a huge set audience thinks about your brand, your service or product and even what they feel about your competitors. These social listening platforms not only give your business access to honest feedback about consumers experience with your brand, but also provides you with answers to everything from what your customers feel about your brand to helping you determine root causes.
What is social listening and what are the business questions it answers?
One of the primary questions that social media data can answer is – What do the general audience think about your brand? By measuring the sentiment associated with your brand and how satisfied people are with your products and services, it is possible for you to understand customer emotions better and formulate an informed strategy that is proactive and works for your business in the long run.
Social Media data also lets you measure consumers’ reaction to a specific event or occasion that is related to your business. For instance, your business has released a teaser of a new product online. Feedback on the same is immediately available to you. By analysing the negative as well as the positive comments, it is possible for you to get early warnings on how your product will be received and what more consumers are expecting for your product. The number of organic views, shares and engagement you get also provides you with a leading indicator of how well your product is being received.
Not many people know that one of the benefits of social listening is that the data provides businesses with a great way to measure purchase intent as well. People on social media love talking about a new “cool” product that they love the look of or heard great reviews of and their intent to buy it. Capturing these conversations using keywords and analysing them can help you quantify and measure purchase intent. You can also measure the size of your product’s potential market by measuring the number of people looking to buy products like yours.
What are the data sources you should be looking at?
So, where can you find answers? Social media channels like Facebook, Twitter and Instagram are some of the most apparent sources of data that can help you track metrics such as brand mentions, hashtag usage and even share of voice comparison with respect to your competitors’ mentions. Facebook and Twitter can help you get good qualitative data as well such as – consumers perspective of your brand, example – key emotions and words associated with you brand. The data gained through social listening platforms can be used quantitatively as well to measure sentiment. Some of the other forums that are mostly overlooked but can provide your business with a treasure trove of data are Reddit, blogs and even news forums. Using specific and tight keywords can help you cultivate these forums as a vital source of actionable insights for your business decisions.
How to convert data into answers/measures
Now that you have your data sources setup and have a bunch of data at your disposal, how do you convert them into numbers that makes sense to your business? The major types of analysis you can perform can be broken down into three types – volumetric analysis, sentiment analysis and topic/theme analysis.
Volumetric analysis is measuring your performance on social media platforms in terms of numbers. For instance, measuring your brand mentions over a period. This can be taken a step forward by analysing and understanding what has been the conversation drivers that have caused any unnatural spikes in conversations around your brand.
Sentiment analysis is one of the key metrics that you can get out of analysing social media data, but it is one of the most challenging metrics to measure as well. Sentiment analysis is measuring quantitatively how a wide set audience feels about your brand. There are several machine learning and classification algorithms out there, which are widely available. These algorithms mostly use the bag of words concept to score and classify your data into positive or negative. But a useful tip to keep in mind during sentiment analysis is that detecting sentiment with taking context into consideration can prove quite tricky.
Theme analysis is another way in which you can understand what people are talking about your brand. By using algorithms like n-gram and other topic clustering algorithms you can recognize issues, trends and other themes and sub-themes that can be leveraged to help improve your business.
Use case: Social listening examples to drive informed decision making
Additionally, social media data gained through social listening platforms can prove invaluable in helping businesses make informed decisions for the future as well. For instance, one of our clients – a technology giant wanted LatentView Analytics to explore and identify future investment opportunities in a particular sphere they were interested in. Because of the huge amount of data involved we identified that text mining techniques and machine learning algorithms were required to sort through the unstructured data and uncover insights and answers that the client required, from social media.
In turn, we used NLP techniques specifically – Word2Vec to group tweets, titles of blogs and news articles. Following which we used n-grams to further identify the dominant themes in each of the clusters. This helped us identify trending topics in the particular sphere that the client was looking to identify opportunities in. Additionally, we could also provide them insights into other similar areas that their consumers were interested in, if any of their competitors already have products in the same sphere and consumers perception of it. This social listening case study demonstrates the importance and benefits of social listening for brands.
Why benchmarking is important
Now that you have a bunch of answers, how do you know which are right answers? This is where benchmarking plays a vital role. Many times, you notice your data behaving in a certain way, but in order to give it context and understand it better you need to see the data with respect to how the industry or your competitors have fared.
Benchmarking can also be done with respect to your own historical performance, for instance, by comparing the number of social mentions you have garnered this month with the past six months average or your performance year on year, lets you measure your exact improvement in your performance. And since this also lets you take into consideration various other factors such as seasonality etc. it tells you if the improvement you see in your social mentions are significant or not.
Conclusion: why you need to set up your own social listening tools
Now that you are convinced of the virtues of social listening, your best bet is to set up your own social listening tool or platform that gathers social media data relevant to your business. Though there are generic tools available in the market that lets you collect data such as count of social media mentions etc., having a dedicated social listening tool that collects customised data keeping in mind the variables and metrics that are pertinent to your business and industry will save you a lot of money and effort as well in the long run. With cutting-edge solutions being developed for social media analytics, businesses have highly capable social listening platforms at their disposal to do this effectively.
Get a 360-degree view of the consumer
Analytics can help deliver more deep-dive insights and provide an understanding of the customer journey at a more granular level. Capturing such detailed information at this level has been possible due to the digital transformation in the past few years which was not possible before. LatentView helps you gain an advantage when it comes to the customer journey. To know more about LatentView Analytics’ end-to-end custom analytics solutions, please write into: email@example.com