The Two Biggest Ways to Get a Solid Return on Social Intelligence, According to Raconteur [Infographic]
22% of social analysts report that their data’s usage isn’t aligned with the larger organization. How does that affect the results of their work?
We are excited to announce the first round of leaders who will bring our 2020 theme HUMAN.X to life at the Broad stage this June (17-18).
In 2019, Hootsuite and We Are Social reported that social media users are spending an average of two hours and sixteen minutes on social platforms daily, an all-time high. And it’s no wonder: there have never been more spaces, more accounts, more data to consume our attention. Given that we can use the posts, tweets, Snaps, and other online interactions to learn more about our consumers, you’d think that our confidence in the data we’re seeing would be at a similar high.
You’d be wrong.
In a recent study produced by Raconteur and aggregated from a number of social media studies conducted, the picture they paint of current social intelligence is one of an industry that has access to unprecedented amounts of information, but often feels at a loss for how to use it effectively. An interesting portion of their results, pulled from The Social Intelligence Lab’s 2019 work, poses the question to social data analysis professionals: does social intelligence meet expectations? While their answers were split, the reasons why social intelligence either meets or misses the mark, aligned nearly perfectly.
When It Exceeds Expectations: It creates action from insights.
When It Misses Expectations: It fails to create action from insights.
Another piece of the Social Intelligence Lab’s study asked social data professionals, “what are your top objectives in examining this data?” More than 7 in 10 (72%) cited customer insight, and more than half (57%) said they use the data to understand customers better. These are major numbers. And based on their answers, when this intelligence isn’t used to craft copy, target campaigns, or effectively reach the right audience, the work suffers.
The good news? Other data in the report offers insight into how to right the proverbial ship. These same surveyed social data analysts report challenges in integrating social intelligence with other data sources (31%), while 22% said that social data isn’t incorporated into the organization’s larger mission. L’Oreal’s Rema Gouyez Benallal said as much during a Social Media Week London panel on social data utilization late last year. She talked about how pairing data surfaced by her team, with historical data that had already earned respect, created a relationship that allowed her team to be valued for the insight they could bring to the table. Rightfully framing these interactions (and occasional surprises) as the result of thoughtful and deliberate engagement helped higher ups see the need to value, and then implement, their insights. The ringing refrain from this quintet of social marketing pros: “[we’re] not just playing on Facebook all day!”
When It Exceeds Expectations: Tracking the right metrics.
When It Misses Expectations: Tracking the wrong metrics.
Does it feel good to get high traffic, lots of likes, or a stream of comments to the posts we share? Absolutely. No question. But using these metrics as measures of success for their own sake won’t serve us if we really want to garner the full benefit of the information these users are choosing to share with us. I can’t help but think about accounts where I’ve seen complaints frequently surface; in that instance, is a post that earns 3,000 comments doing “well” if even 10% are negative?
Moving beyond quantity to quality of engagements by tracking the sentiments expressed, more qualitative accounts as shared by consumers, or truly business-shifting metrics like webstore traffic and lower percentages of abandoned carts, needs to be the goal that we reach for when participating on these platforms. Creating relationships (real or implied) with the consumers we interact with can help us understand how they’ll let us know if our efforts are working. Moreover, we need to value these relationships even if they don’t yield the high numbers that a viral like count does. To wit: the Social Intelligence Lab’s fourth most commonly cited reason to value social intelligence was “to understand customer sentiment.” Picking, tracking, and working to impact metrics that clearly and intentionally affect this is essential to deeming our efforts a success.
The full report is worth a deeper look, pulling together a variety of details on social platform size, significance, and usage patterns. The bottom line is this: the data users choose to share on these sites is hugely reflective of our customer bases, and therefore hugely valuable when impacting our bottom lines. Using this data in ways that spur action across an organization, and that stays focused on impact in the face of vanity metrics, will help us make the most of the time that our users spend online, and that we spend online in service to them.
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