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Favor Touchpoints Over Trends, and More Lessons from Linkfluence in Social Data

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Word of mouth and social media can hugely impact how brands grow and evolve; Linkfluence’s Gareth Owens dove into why, how, and what your brand can learn from his company’s approach.

Why would a dairy company be interested in insights on veganism?

Linkfluence found themselves pondering that question when called upon by client Danone to examine social data surrounding the plant-based food market.

Managing Director Gareth Owens outlined their process in his session, “How Social Data Helps Brands to Create Business Opportunities.” In it, Owens showed how Linkfluence’s strategy helps to make sense of massive landscapes of social data—our posts, forum engagement, likes, shares, “and even poo emojis you use online.”

The Challenge of Taking and Structuring Data

Owens posed the all-important question on the minds of SMWLDN attendees: how do we bring brands closer to their customers using social data? It’s harder than we think, and many have failed, he noted. But his answer, and the one that drives Linkfluence’s strategy, is relevance.

Through their work for Danone, Linkfluence discovered that the conversation around veganism changed between 2015 and 2018. What was once a conversation dominated by the US and Europe, and largely focused on nutrition and food intolerances, gradually evolved into a worldwide dialogue concerned with activism and sustainability. By exploring the “huge amount of data, ready for you to mine”, and then breaking it down into themes, they came to a better understanding of what it could mean to engage vegans online.

The “Momentary” Nature of Segmentation

The social data Linkfluence gathers proves utility across multiple business areas; their deep dive into veganism was no exception. It’s not enough to know who the vegans are; it matters to know if they’re health conscious, environmentalists, animal activists, trend followers, or any combination of those. From these initial touchpoints, you can tailor an approach for outreach and engagement that speaks more deeply to your target audience or consumer.

Owens’ research revealed what he calls “moments of consumption” as a means to further segment users. When seeking to engage this target population, it helped to note the times of day when they’re aware of their veganism. Not just mealtimes—breakfast, lunch, and dinner—but also surrounding activities, like “pre- and post- workout.” Armed with this information, their client could focus even more narrowly on the needs of an otherwise broad defined segment. The key here is “finding something you believe to be homogenous, and beginning to break that down into individual elements that make sense for you and your brand.”

“Continue Listening to Your Audiences As They Develop”

Even as your grasp on a population evolves, Owens warned, you have to allow for the population itself to evolve in its own right. Looking to food trends that dominated searches in 2017, he pointed out that some remained constant (matcha, spirulina), while others dropped in popularity (regrettable for those who banked on macadamia). With a commitment to listening, but also to development, social data can be a powerful tool for brand management.

Just ask social-powered brand and Linkfluence client LUSH. CEO Mark Wolverton acknowledges “word of mouth and social media play the biggest part in allowing us to engage online.” Their attentiveness to social data as a means to promote the product (just look at their six user-generated hashtags for proof), create marketing collateral, and even dictate store stock, is a testament to how social data can drive the trajectory of a brand.

And in the case of Danone, social data powered a major shift in their organizational strategy: they used this rich data to successfully acquire Alpro, a plant-based food company.

In Linkfluence’s eyes, the aim is simple: “We take large amounts of unstructured social data, and structure it for our clients.” By understanding the power of such a strategy, and committing to continuously interrogating the data you mine, you can make the most of social data just as they have.

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