The nearly 300,000 Twitter followers and over 250,000 of Facebook users talking about it gave the Aam Aadmi Party (AAP) enough firepower to ask for mandate even after vote-counting was over. It canvassed for show of support to form the government in the state of Delhi through its social media handles, directing people to sign a form on its website. There were 99,043 unique responses on the site, of which 20,969 were from Delhi and 14,256 of them had said yes (through other media such as phone calls, SMS and public meetings, another 183,087 said yes).
The utopian use of social media by AAP may have drawn flak due to the dubious nature of such responses but it has claimed it is meant to bolster its offline efforts and analytics.
For the user of social media, it is not just political parties who are taking what they say into account. While AAP might listen for feedback on policy-making and action, a broadcaster might be waiting to get a cue to tweak the content it puts out on the airwaves, an FMCG company its distribution, a bank its service standards.
Chief marketing officers have spoken about engagement online for years now, even as wary CEOs have listened on. This year has seen an increasing number of them going beyond their social media listening. They are making the buzz on the Internet work for them.
But the data, unlike big data that marketers use for analytics, is mostly unorganised, though keywords help to an extent. Tushar Vyas, managing partner-South Asia at GroupM who handles WPP's media group's digital business in India says, "Most of the companies were listening for quite sometime. Tools have been always around but it is about putting human intelligence on top of it. Based on the category, we have different ways of culling out the data on insights. For example, for broadcasters, we classify the findings into implications for marketing, programming and distribution."
|NOT JUST FOR FIREFIGHTING|
Star TV network
Distribution: Chatter on loss of signal or unavailability of programmes has been relayed from the central team to the regional CRM team
Programming: Feedback on bias in commentary and even language (football in Hindi) have been taken into account
Promos: If a character who is not a protagonist generates a buzz, promos are cut featuring the person, people’s anticipation of the storyline heard online are incorporated in the teasers, the pace of character development have also been registered Of the nearly 85 million users of Facebook India, Star has 18 million across its many network handles. So, it will look for prepping up high TVT shows which might not have high social buzz and even vice-versa by encouraging sampling online and offline, respectively.
Product service: Someone with a locked credit card and an impending overseas journey tweeted about his ordeal that got the bank to rush an alternate card at his doorstep before he left.
Gets inputs from fashion bloggers for reviews and style trends
Star on the Internet
Group M, after all, has been helping Star TV India with making the social media work for its many business needs. Venke Sharma, vice-president - digital marketing at Star TV says, "Social media listening had been basic so far. Agencies would use some tool and brand managers would get reports on what got retweeted, liked, basic sentiments. Actionable insights had been missing despite tonnes of data. But the feedback to use need not necessarily be about dissatisfaction, it can be about behaviour patterns. So, an entire shift has happened in our reports on actionable insights."
Vyas explains what the second screen feed means for his client, which Sharma describes as the world's largest focus group. "Broadcasters need real-time feedback for an impact because the product itself is real-time. The feedback tracking has to be a newsroom kind of operation where they need to listen, pick up the cues and act on it as soon as possible. It even enables the central team to alert the local teams on issues they might miss." Please see box for details.
"We are trying out APIs (software applications) from Facebook. While Twitter shows you what is trending, Facebook too now has a trend indicator," says Sharma. Facebook launched two beta programmes in September, to display real-time feed of public posts for a specific word and to aggregate posts according to a specific terms in a given time frame.
Nielsen tied up with Twitter for to measure activity and reach of TV-related conversation in the US. Nielsen is mulling a similar initiative in India that could materialise by mid-2014. For clients, the ratings would enable TV networks to measure engagement around their programmes. It would help agencies make data-driven media plans to take into account second-screen strategies for Twitter.
Though Sharma cautions, "Automatic organic reach on social media vehicles have decreased from the earlier 20 per cent to 5-10 per cent. So, if earlier you could reach 20 per cent of your online fan base by default through any posting, now it would be only 5 per cent who would see the post automatically on their feed."
Even though the second screen is yet to gain sizeable import (there are 550-600 million TV viewers, and the largest social media platform has around 82-85 million, ie. Facebook). Sharma says that there has been a huge surge in digital properties.
HDFC banks on turnarund times
For Karthik Jain, executive vice-president and Head Marketing at HDFC Bank, inputs from social media are about giving the bank's servicing a sharper edge. "Why would somebody post on Twitter or Facebook? Either they are happy with the services or are unhappy. If they are facing an issue, then the critical to respond as quickly as possible. So, I might be listening but what is my response time is what we have worked over the last one year," says Jain.
Jain's team has worked worked internally with the service quality team to respond to 90 per cent of the posts made during office hours (9 am-9 pm) within one hour. The bank thinks of a solution to the problem and tells the customer about it in another three hours. The emails with a reference number generated online are prioritised.
To organise the data, HDFC categorises the feedback under marketing comunications, products, financial performance and customer complaint and rates the negative ones on a scale of one to six for criticality (the most critical ones go up to the senior-most management), ones meriting a five generate an SMS to Jain, the service quality head and the corporate communications head. They get on a call together to discuss and troubleshoot.
The usual suspects who resort to making data on social media work for them are the e-commerce players such as Myntra, a lifestyle retailer and travel sites such as MakeMyTrip for user habits (see box). While FMCG companies can get hindered by the time taken up by the decision-making process, that calls for deeper offline ratification for products that have longer lifecycles than TV soaps or sports events.
A senior media planner who refused to be quoted points out how an FMCG major in dairy and chocolates has constructed a hub with 15 live screens to flash trends on the Internet so that a brand manager walking in can walk in to see what is happening in the category and the brand she handles at any point in the day. "The quality of content has imprved as a result, and the decision-making time cut short," he adds. Pepsi too has tailored its communication after picking up cues while Parle Agro has tried it with its distribution (see box).
Correlation is the catch
One of the challenges is to match a brand's audience with the online users to see which feedback matters. Vikas Ahuja, CMO at Myntra.com warns, "Companies will have to keep in mind the disparity between online and offline audience when ploghing back feedback into their business processes. For FMCG brands, it will be more difficult to achieve a correlation than others." Myntra's focus on an audience below 30 years of age ensures that there is a high affinity with the social media users too.
Star too has refined its listening process for feedback, especially on programming and communication cues. "We listen to whoever has been consistent with feedback and we are still learning such checks and balances," says Sharma.
Jain has found that the people who had complained on the bank's social media pages, were more engaged with the bank, with higher balances and usage of its products, more than its average user. "We will file the social media handles of real users if they write to us online for future reference and scale it up across platforms,"says Jain.
Vyas says that the next stage in social media listening would be to model sales prediction based on the feedback. "Mathematical models are done for sales projection based on GDP and other macro parameters. Now social chatter -- signals in sentiments and moods -- can also have an impact. We are doing a beta and would validate it in a year's time."