Market research has evolved, propelled largely by the development of technology, the proliferation of data and a broader consumer reach. The shift from brick-and-mortar stores to online shops as well as the social media boom has enlarged business’ frontiers, literally and figuratively. This shift has also created new ways for brands to identify themselves, position themselves as unique in the market and truly engage with their customers. One could even argue that this new landscape has greatly increased expectations regarding market understanding, customer relations and overall marketing performance.
For a long time, marketers have used primary research – surveys, observations, interviews, etc. – as one of their main ways to keep in touch with customers. Today, marketing analytics adds an even deeper dimension. Social media listening combines technology, data and analytics to become the latest addition to the marketing toolbox. You don’t have to ask a single direct question, yet you still get a wealth of rich insights garnered from social-media-listening tools and services. Online users routinely share their independent reviews, their comments and concerns about brands, even their unfiltered experiences. The emerging topics and recurring themes should be of great interest to any marketer.
Marketers love their keywords when it comes to online advertising. In social media listening, keywords again play an important role. Choosing the right keywords can give you remarkably exact data. Once you zero in on the type of keyword – broad ones for your category, precise ones for your brand – you’re on your way to social media listening. In this slideshow, Anil Kaul, CEO of Absolutdata, has identified four types of social media conversations and the advantages that come with them.
Analyzing Social Media Conversations
Click through for four types of social media conversations and the advantages retailers can gain from listening to them, as identified by Anil Kaul, CEO of Absolutdata.
Category-Level Conversations
Category-level data helps you identify the trends in the market; category-level conversations are like real-time market information generators. The topics are broad: hair, pizza, cars. Just focus in on your category and look for themes. If hair styling is your category, conversations let you know what kind of content and dialogues are being based around hair, hair color trends, style, etc. These topics become your themes. When carefully studied, these themes can improve your campaign-based category data insights.
Brand-Level Conversations
These conversations are specifically based on a single brand name, such as Tata tea or Hershey’s chocolate. Sentiments and major themes can be extracted through sentiment analysis, topic modeling and text analytics for brand. Focus on brand-level conversations when you want to find data for measuring brand equity, analyzing brand recognition, and gauging brand marketing effectiveness.
Product-Level Conversations
A lot of social media users post product reviews and recommend their favorites. For example, data can be analyzed for Kwality Walls’ range of ice cream products (Cornetto, Carte D’or, Magnum etc.) to see which product or flavor is most or least popular among users. Zeroing in on data based on the product name will help your organization see product performance and market popularity. User feedback can show you how to enhance your product (or service) as well.
Competitor-Level Conversations
Digging up data about your competitors clues you into their overall performance in the market. If Cadbury is the main brand, then it can measure the performance of its competitors like Mars, Hershey and Godiva to analyze their campaigns, mentions, brand presences, engagement levels and other key areas.
Advantages of Using Social Media Data
Making social media listening a part of your marketing strategy comes with great benefits. To start, the data is legit. The data is made up of users’ own comments. It is entirely genuine and an excellent source of insight on what motivates consumer behavior. Social media data can be easily extracted through tools like Radian 6, Broadwatch and others, making it very accessible. Beyond the ease and accessibility, this data is fast. Any new campaign, marketing activity, or product launch can get near instant feedback. Lastly, this data can identify sentiment and recurring themes about the products or services that can be extracted by using analytics techniques like text analysis or sentiments analysis.
