now, and the future

November 28, 2016

Today, the number of people on social media is rising every second and the volume of conversations is escalating rapidly. Social intelligence is the tool of choice for businesses to decipher the diverse data—to identify opportunities and avoid blunders.

 

Social intelligence is the practice of gathering data from social media channels and analyzing it to make critical business decisions. Its common use is to mine customer sentiments, interests, and conversations in order to support marketing and business operations. Although social intelligence is a relatively unexplored territory, it is gradually emerging as a key facilitator of change. It is compelling marketers to trade gut feelings with accurate data-driven insights to devise smarter strategies, and achieve effective proactive decision-making. It is about the marketers’ willingness to be a part of social conversations and not merely assemble social data. This wealth of information has much to offer—to an array of segments including consumer technology brands, digital marketing and media agencies, and media companies. Can ‘social’ entirely displace conventional methods of marketing research and intelligence gathering? The answer is a big ‘yes’. Social insights are slowly becoming the most important piece of information for C-level executives and board members who are seeking the best possible basis for their decisions.

 

brief history

While the earliest social listening products can be traced back to 2000-2002, most of the products commonly available today belong to the 2005-2008 period. Many of these (first generation of social data products) have undergone incremental improvements and a few have taken a meaningful next-generation leap. Many of the second-generation (2009-2012) products are focused on taking social content and social data to outside interfaces such as websites, TV, outdoor displays, etc. , and can be termed as the ‘social engagement’ vendors.

The third generation (from 2012 to the present), on the one hand, includes social alert providers such as Dataminr and Banjo; on the other, includes true social intelligence vendors such as IBM Watson and Frrole. A small number of first-generation vendors such as Crimson Hexagon and Brandwatch can also be listed here, given the non-linear product progress being made by them.

 

present status

The social intelligence market today stands at an interesting juncture. While it has been growing at 30% annually, and is poised to be a $5bn market by 2020,1 Gartner has put social analytics in the trough of disillusionment.

The reality probably is somewhere in the middle. Social data continues to answer more and more customer questions for marketers and therefore continues to become more useful. Led by the next-generation products, the vendors continue to build better technology and algorithms so that they can answer more questions with more precision. Social intelligence is gradually emerging as a key facilitator of change in the world of business. It is compelling marketers to trade gut feeling with accurate data-driven insights to device smarter strategies and achieve effective proactive decision-making.

The nature of the insight is changing. Descriptive insights like number of mentions and sentiment are giving way to actionable insights like what caused the change in mentions or sentiment. While predictive and prescriptive insights are still to materialize in the real sense of the word, the next-generation vendors are focusing heavily on it and building it as a true differentiator.

Integration of social and non-social data is becoming a reality. Vendors such as IBM Watson allow the user to import various kinds of data and then build and visualize correlations between them. At Frrole, we help customers create solutions on top of the product that can combine various kinds of data, and package it in a manner that exactly meets their needs. A global agency has engaged Frrole to build a data management platform that can combine social data with ad spend data, Google search, sales, and other marketing expense data. Back in 2013, Gartner lamented in their report, Who’s Who in Social Media Analytics?, “Most of the vendors support use cases that focus exclusively on the analysis of social data, rather than the potentially more impactful insights that may be derived by analyzing both social data and other enterprise data.” It is finally changing.

There are two kinds of vendors providing people intelligence—specialized vendors such as StatSocialand People Pattern, and full-stack vendors such as Brandwatch, NetBase, Crimson Hexagon, and Frrole which provide both people intelligence and topic intelligence/social listening.

 

Hypercycel

 

 

next-generation social intelligence

Frrole is one such disruptive social intelligence startup.  We provide hard-to-obtain consumer insights to marketers and product owners, combining our expertise in the area of machine learning with our capabilities to analyze millions of universal data sets in real time. For all these data sets, we perform extensive analysis across semantic, metadata, and statistical dimensions by leveraging standard and custom-built algorithms around ML, NLP, NER, and clustering to do this analysis. While most social analytics/intelligence products provide results based on statistics and the first level of NLP, we go deeper into building semantic context for each topic and tying it up with information available in the general and historical data sets. The next-generation social intelligence companies are focusing on ‘people intelligence.’ The beauty of this is to understand the users behind social conversations beyond just social listening. Hence, analyze demographics, psychometrics, brand preferences, purchase behavior, and content affinity of people based on what they post on social media. Using derived insights, it helps marketers to measure real-time shifts in their audience haracteristics, analyze past buying behavior, and predict future patterns. Also, these deep insights, which even include ‘mood analysis’ of the targeted audience, can potentially serve as fodder for critical business decisions, both short term and long term. This is a significant next step for a brand as mood analysis can tell a brand how a consumer is likely to act on a certain feeling, something that brand marketers care for deeply.

In early 2016, one of our clients, a global smartphone maker, used social insights to derive its new product launch and go-to-market strategy in emerging markets such as India. The range of analytical techniques has exploded, and companies must tap new areas of expertise to stay ahead of the game. A brand’s customers are speaking about the brand, its competitors, their likes and dislikes, and many other interesting things. Why would that brand still completely rely on age-old market research tactics, and not embrace these organic, unbiased, multi-segmented, real-time insights about their industry, competition?

For a long time, sentiment analysis has been the standard approach for understanding how consumers feel about a brand. However, this manner of analysis sticks to aggregating positive, negative, and neutral sentiments; in a world of colors, that is like having only black, white, and grey as the available colors. It makes for a pretty dull and illegible world, whether it is the real world or the world of consumer behavior. With mood analysis, we have introduced a next-generation algorithm that helps you understand how consumers feel about a particular brand, and how they are likely to act on their feelings.

 

Social-intellligence-landscape(1)

 

the future

Social Intelligence in the future is no more going to be about understanding what your customers are saying about you on social media. It is going to be about taking what people said on social media to understand your customers—whether those customers are on your website, in your store, or sitting at their home. Leading vendors are already bringing in technology that would help you understand the demographics of a particular group of people who avail themselves of a special discount promo, or understand the needs of a group of customers in your CRM who walked into a certain store on a certain day. Social intelligence is on its way to becoming truly integrated and is no more going to be limited to social media conversations.

It is also beginning to tread into the domain previously owned by marketing research providers. Back in 2012, a seminal report by McKinsey, The Social Economy, said, “We believe 100 percent of the current ($31B) marketing analytics market can be captured through social technology”.

While this has stayed as a wishful thought for long, vendors like us now finally provide features that allow users to ask on-the-fly questions from real-time social data. You need to provide a few training examples for the answers you want to validate, and the machine learning algorithms kick in to automatically understand enough from those examples to start answering any questions a marketer might have. This obliterates the need to do expensive, infrequent, micro-sampled focus groups and consumer surveys, allowing marketing research to become both real time and real.

Social intelligence is changing the way we conduct market analytics, offering reliable data points to build audience profiles, segments, and product innovations. With the integration of social intelligence and customer data, the conventional methods of marketing research and analytics are becoming obsolete. Gone are the days of expensive focus groups and surveys. Now marketers can use social data to understand what motivates an audience and consolidate the intel with other information (i.e., customer data) for richer insights.

 

cahart-3copy

 

Customers today are more than just customers, they are the last mile for marketers. Using social media, they not only influence the buying decisions of others but can also make or break a brand’s overall perception in the long run. For brands to be dynamically competitive, it is imperative they know their customers in real time. In today’s aggressive market, organizations need to capture maximum customer information and analyze it effectively to discover patterns, trends, and other vital clues. Social media networking activity is generating big data—and these growing sources are the new frontier for customer intelligence

 

20160822_173609(1)