With the ongoing expansion of social media most businesses, and particularly their Marketing teams, remain focused on the broadcast power these channels provide. However, this one-dimensional view of social on covers a fraction of the value that can be delivered on an ongoing basis to brands.
Mining the attitudes, behaviors, trends and perspectives deep within the billions upon billions of daily social discussions provides unprecedented insight into an organization’s consumers, champions, critics and competitors.
With the continuous discussion and debate surrounding “listening” to social media discussions, many companies realize the wealth of unbiased, immediate, actionable insight social intelligence can provide to answer valuable, complex questions like:
Why do shoppers buy my product?
What advantages do consumers see in my competitors?
Do unmet consumer needs exist that I can address?
What are the specific demand moments for my brand?
To answer these sorts of highly specific, complex questions with actionable intelligence, companies are using a combination of streaming big data supercomputing and advanced concept model in place of traditional keyword lists.
First, many marketing organizations see the “social universe” as focused on Facebook and Twitter and perhaps YouTube, Pinterest or another network of two. Given the limitations of social monitoring tools, Marketers are often forced to select narrow views of the social universe.
It’s understandable why many marketers limit their social focus to one or two networks, after all, managing and tracking millions of channels becomes a daunting, if not impossible, but it’s by no means ideal or acceptable.
The biggest sources (the mainstream social networks) are often not the best when it comes to consumer insights. Often, shoppers, consumers, influencers and evangelists of your brands are interacting in specialized or focused communities, blogs or channels. To find them, means you have to expand the scope of your view holistically to the entire social universe relevant to your brand.
A Big Data Challenge
Most organizations, if they’re “listening” to social conversations at all, are doing so at a cursory level, using basic keyword tools to monitor a sample of the social universe. Given that different segments of consumers congregate on different social sources, these snapshot views only deliver a limited, and often deceptive, view of the population. On top this, individuals do not speak in keywords and typically use a social lexicon that is continuously shifting and evolving.
Keywords will find exact, limited mentions, but will miss the vast majority of conceptual posts which can vary infinite ways and never mentioning a defined keyword, brand or product. A major challenge of social media keywords is keeping up with the ever-changing lexicon of discussions, which in and of itself makes keywords an obsolete approach.
The best that can be typically hoped for with keyword tools is basic, high-level “buzz” (or sentiment) on their product or brand, which is vague, inactionable and often inaccurate.
As the open social universe continues to exponentially expand, social commentary has evolved into big data – billions of daily posts from hundreds of millions of individuals across millions of sources. It’s ugly, unstructured data, but provides deep ethnographic insight from what essentially is the ultimate unbiased focus group.
To extract these insights Marketers need to unleash big data super processing that can handle the volume, velocity and variety of social data in real-time. Companies already using advanced big data social intelligence solutions have an incredible advantage over their competitors gaining the ability understanding their consumers, shoppers, influencers and competitors better than ever before.
A Widespread Impact
Brands embracing advanced social intelligence find a wide array of valuable applications for this insight to set strategy, guide decisions and drive innovation, including understanding of:
Consumer Personas: Understanding of consumer behaviors, decisions, attitudes, interests and activities to construct personas for enhanced reach.
Path-to-Purchase: Analysis of the decision influences for specific products, including factors, milestones and trends.
Demand Moments: Shopper interests and activities to pinpoint engagement channels to build market strategies and media plans.
Market Entry: Evaluation of established products in terms of consumer sentiment, market traction and unmet needs for opportunity identification.
Market Testing: Efficacy measurement and validation of promotional campaigns, marketing channels, packaging, positioning and messaging.
Innovation Drivers: Multidimensional insights that drive product development, feature enhancements, brand positioning and overall marketing strategy.
Competitive Tracking: Tracking of competitors’ strengths and weaknesses, as well as consumer decision points and abandonment motivators.
The ability to understand consumers, markets and competitors through ethnographic understanding of big social data has never been more powerful, allowing organizations to address the bias of surveys and focus groups and go beyond superficial “buzz” to uncover actionable consumer insight like never before. The key to achieving this is first, treating social media data as the complex big data that it is. Unlocking the insights requires advanced processing technology and concept modeling to address the volume, speed and complexity of the open social discussions in real-time.
Once unlocked, this advanced social intelligence can make a company-wide impact across Marketing, Product, Brand, Research, Insights, Innovation and beyond, by delivering unbiased, actionable insight to drive decision making, market strategy and innovation and provide a massive competitive advantage to organizations.
Question: Is your organization understanding shoppers and consumers to drive your innovation? If so, how? If not, why?
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