Move over sentiment analysis, mood mapping is here

India’s largest e-tailer Flipkart, which has been working hard on building customer loyalty and stickiness over the last two quarters, has plenty to smile about.

In June (1–30), Flipkart notched up 1,24,438 mentions on popular micro-blogging site Twitter, leaving its closest rival Amazon trailing far behind at 24,234, and Snapdeal at 26,042 mentions.

While 62.3 per cent of Flipkart mentions were positive, Amazon got 59.1 per cent followed by Snapdeal at 58 per cent. Flipkart had the most number of ‘active’ and engaged user-mentions at 51.6 per cent and the least number of ‘depressed’ mentions at 18 per cent, compared with Amazon’s 46.3 per cent and 23.3 per cent, and Snapdeal’s 34.6 per cent and 24.5 per cent, respectively.

Flipkart also topped the charts, garnering 12,893 unique user conversations, while Amazon and Snapdeal had just 8,045 and 5,858. This is a small sample of customer insights gleaned by Bengaluru-based, social intelligence start-up Frrole, for the readers of BusinessLine . Frrole has combined its expertise in machine-learning with Liz Miller’s popular mood-analysis framework called Mood Mapping, one-of-its-kind in the social intelligence domain, to provide real-time data on consumer moods.

“Sentiment analysis has long been the standard approach for understanding how consumers feel about a brand. While this approach sticks to aggregating positive, negative and neutral sentiments; in a world of colours, that’s like having only black, white and grey. With Mood Mapping, we have introduced a next-generation algorithm that helps marketers understand how consumers feel about a particular brand and how they are likely to act on their feelings, something that brand marketers care for very deeply,” Amarpreet Kalkat, co-founder-CEO, Frrole, told .

The start-up provides social intelligence by tracking conversations on Twitter, Facebook and Instagram for 23 customers, including the US State Department, Telugu Desam Party, Disney, Samsung, Microsoft, Flipkart, Zoom TV, Times Now and Unilever.

Frrole maps four primary customer moods — anxious, calm, active and depressed, of which ‘active’ customers are most likely to act positively to a brand by downloading the app, buying from the brand or participating in brand contests; while ‘depressed’ customers are most likely to be unhappy with the product, service or price of the brand.

“We track 25 million social conversations a day and can provide other insights relevant to marketers such as, the time of the day customer conversations about a particular brand rise, the location where maximum conversations happen, whether the customers are men or women, the kind of devices theyuse, their personality traits, likes and interests, the people they follow, whether they are influencers with huge following, the kind of content they like, and so on,” Kalkat said.

A top global smartphone manufacturer used Frrole’s insights to conceptualise and design its product launch strategy for Tier-II and III customers. The start-up found that Tier II and III customers considered 4G not a spectrum service but an important smartphone feature. Therefore, the brand was positioned as ‘Best 4G Smartphone’ targeting the youth of 27 cities covered by Frrole’s social intelligence.

“A TV show that wants to improve audience participation can prompt viewers to send votes or opinions via Facebook and Twitter, and Frrole can provide the analysis of all conversations on the show in real-time. Similarly, for a media house, social intelligence can help gain significant insights about what content and topics work or do not work with its audiences, hence enabling it to integrate the most-interesting user-generated content into its programming and editorials,” Kalkat said.

Founded in 2014, Frrole, a Microsoft Ventures Accelerator-incubated company, had raised an angel round of $2,45,000 in 2014. The profitable company expects to hit $1 million in revenue run-rate by the end of this year. The start-up was recognised as ‘Marketing Technologist of the Year’ at the Big Data and Analytics Summit 2016.

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