Beyond Social Listening: Social Media Data + Other Data Sources = More Insightful Reports

If you’ve visited our blog before, you’ll know that there are several ways that social listening can be leveraged to understand consumer habits, set benchmarks, and track conversations. But did you know that it is also possible combine other data sources with social data to come up with more robust insights?

At Circus Social, we have been integrating various types of data in our reports for our clients. Read on to know how we do it!

 

#1: Integrating Social Data with Google Search Data

Social chatter is a good indicator that people are interested about a certain topic – but what about topics they don’t necessarily talk about on social media? In some cases, search data can be a stronger proof of interest than buzz volume.

Let’s say you want to discover the top skin care concerns in Singapore. Since it is an embarrassing topic, people may not necessarily talk about acne or psoriasis on Twitter or Instagram. But they are likely to search for solutions for these problems on more ‘private’ search platforms, like Google.

So in this case, search data can indicate interest, but social data can explain qualitatively why people are interested in that particular topic – for example, reasons why acne is a problem for them, products they use to manage their acne, and many explanations.

Search gives you a trigger, Social gives you the reason for the trigger.

So, where exactly can you access Google search data? Trends in Google search volumes are openly available in the Google Trends website. This site analyzes the popularity of search queries in Google across various locations and languages. You can also get search data from the Keyword Planner tool if you have a Google Adwords account. Compared with Google Trends, this tool provides more accurate search volumes (especially if you have a paying account).

More insightful reports - easily done by combining different data sources & social media!
More insightful reports – easily done by combining different data sources & social media!

Popular Use Cases:

  1. Trend Spotting/Tracking – Search data is especially useful for identifying trends because it allows people to search for topics even before they start talking about them and can help indicate when interest for a topic started. Then, social data can be used to look at specific conversation themes about these trends.
  2. Brand Health Tracking – Especially when looked at in comparison with competitors, search data can tell you where your brand stands, specifically in terms of awareness. Social data is a good reference for brand associations and you can also complement this data with related search terms, which can be found in both Google Trends and Adwords Keyword Planner.
  3. Campaign Tracking – Other than looking at increase in social conversations, it helps to see if your campaign had an impact on how much people have searched about your brand on Google.

 

#2: Using Social Data to Complement Traditional Research Data

We have a number of Market Research Agency partners and they usually ask us to look at social media data to dig deeper into traditional research tracker findings.

Traditional research is often not able to fully explain the ‘whys’ behind findings and numbers a lot of times. Once a study concludes, traditional researchers just need to work with the data that they have. If they have additional questions that need to be answered, they would need to start another study. This is where digital research comes in – because it is possible to pull historical data using social listening tools.

In one of the projects that we did, the Retail Audit and Brand Health Tracker Data showed that a client’s competitor brand had an increase in Market Share and Consumption, despite a decrease in advertising spends. Their Brand Equity score increased including all specific imagery statements (i.e. Love/Taste). What could have caused the increase of this score?

Working together with the Market Research Agency, we were able to identify specific periods when scores increased and looked at social conversations during these periods. After deep-diving into these conversations, we found out that consumers created a new demand occasion for the product which became popular in that country.

More insightful reports - easily done by combining different data sources & social media!
More insightful reports – easily done by combining different data sources & social media!

Popular Use Cases:

  1. Brand Health/Equity Tracking – Market Research can be the basis of qualitative social media data analysis.
  2. Supplementing Qualitative Research – For one of our clients, we found out that online review sites were influential sources of information that affected consumer purchase behavior. Through social listening, we were able to identify which particular websites consumers visited and Qualitative Research explained why people preferred these websites.

 

#3: Combining Social Data with Sales Data

If traditional research has not been done, social data can often explain movements in sales volumes and provides more in-depth insights. Just take note though, there may be a lag between when people talk or search about a product and when they actually purchase it. Hence, it is best to analyze these data points over longer durations to really see the correlations between them.

More insightful reports - easily done by combining different data sources & social media!
More insightful reports – easily done by combining different data sources & social media!

Popular Use Cases:

  1. Campaign Tracking – Ideally, campaigns that you launch should have an impact on sales. Aside from the usual metrics analyzed for post-campaign evaluation reports such as reach, impressions, volume of social conversations, social engagements, etc., you may also look at the correlations between these data points and sales data.
  2. Consumer Purchase Behavior Analysis – For some brands, they may notice that sales volumes peak and drop at certain months of the year. These may not necessarily be because of campaigns especially if they are not implemented on a regular basis. Reasons for seasonality in purchase trends can be uncovered by looking at social data alongside sales data.

 

By no means are these the only data sources that can be integrated with social data (you can also look at website traffic data, digital media performance metrics, among others). The key is to track as much data points as you can and organize your data so you can easily discover correlations whenever you need them.

You’ll never know how much value you can get from your data if you don’t try playing around with it!

Circus Social can help you look at your social, search, sales & many other forms of data to uncover deeper insights – just like how we have helped our clients make sense of theirs!

Data Science at Circus Social

Circus Social is brimming with social intelligence. With a vibrant and vastly talented group of Data Engineers, Data Scientists, and Data Analysts on board – we live and breathe analytics.

More recently, our machine learning capabilities for the 20/Twenty platform have benefitted from a decentralized and distributed structure.

Data Science at Circus Social

Our clients are often faced with a variety of marketing challenges – and we try to work hand-in-hand to find the most efficient way of tackling them. These could include finding solutions to ‘hard-problems‘ like real-time document clustering or- predicting a virality score for posts on social media.

There are also new challenges that occur with changing lifestyles and social media behavior like, automatically grouping similar videos uploaded by users based on different attributes including context, language and emotions where we have to tap in to specializations of both the science and the engineering teams have been only possible with the contribution of both the science and the engineering teams.

While our data science team has created magic with data, predictive and modeling techniques, our engineering team has helped maintain several terabytes of data and created effective machine learning pipelines.

Data Science at Circus SocialThe team’s latest project has been to develop and deploy a real-time document clustering functionality – allowing our clients to find viral content, identify trends and proactively react to crisis situations. The three main phases of this project are feature extraction and selection, document representation and clustering.  After having experimented with a lot of clustering algorithms with speed and cluster quality as the primary metric for evaluation we settled for a hybrid approach that used both K-means and agglomerative hierarchical clustering. K-means, because of its run-time efficiency and agglomerative hierarchical clustering because of the cluster quality. While our initial motivation was to find similar conversations in a given geographical area, we have also started using it to recommend conversations and articles the user is most interested in.

Data Science at Circus Social

At Circus Social, promoting the best ideas not only pampers our love for an open culture but also helps drive an innovative culture that constantly challenges the status quo. As a social media analytics company, we have developed a similar wavelength for Data Science.

From where it all began in the early days of social listening-, to today’s culmination of intelligence, data science & machine learning-, we are truly excited at the possibilities of what the future of 20/Twenty holds for us, our team and our clients.

A Chance Meeting: Social Media Monitoring

I was at a Business School today to attend an event and met a few people from the industry. Here is an interesting conversation I had with somebody I met. Let’s call him Mr. X.

Mr. X – So what do you do?
Ram – I am an entrepreneur and run a software product company called Circus Social. We do social media monitoring and analytics; and have offices in Singapore and Bangalore.

Mr. X – What exactly is social media monitoring?
Ram – In simple terms, we fetch data, and a lot of it, from multiple social networks like Facebook, Twitter, Instagram, Pinterest, Reddit etc. and also from several blogs, forums and news sites. We then process and augment this data (with sentiment, gender, removing spam etc) and allow marketers to get insights from this data. We show them trends, insights, a lot of charts and graphs and allow them to make better business decisions.

Mr. X – So you are a big data company. Sounds like tough work. What kind of business decisions can be made?
Ram – Yes, we are indeed a big data company. Currently, our clients are enterprises, typically marketers, who would like to know their customers better, research their markets, analyse their competitors, identify top influencers, get real time alerts on topics of interest etc. We are also launching our SME product shortly.

Mr. X – So, do you invade people’s privacy? Isn’t this data private?
Ram – We only crawl data that is already publicly available. Anything that is private or protected by you is completely out of bounds for us. We do an incredibly good job of collating all of this data in our platform and marketers find tremendous value in quickly viewing trends from 10,000 feet but also in the ability to drill down to understand the “why” and “how” behind the trends.

Mr. X – Will this be useful for my company?
Ram – If people are talking about your company, your brands or topics that you are interested in tracking, you will definitely find it useful.

Mr. X – Where can I get more information?
Ram – Here’s my business card. Please visit our website https://www.circussocial.com where you can find a lot more information about what we do and a list of some of our clients. You can also sign-up for a free demo.

Mr. X – Sounds good. Thank you!
Ram – You are welcome!