This trend is supported by data provided from Influential, a social data platform that leverages the most advanced artificial intelligence (AI) technology to select influencers, inform content and strategy, and deliver against measurable business outcomes and return on investment for brands.
We live in an age of hyperbole, and you don’t have to spend more than a few minutes on social media to realize it. Imagine eating a slice of pizza, turning to your friend, and saying “I literally died after that bite. Fight me.” But why do we feel the need to speak in such extremes online?
In 1997, an article in Information Society stated “Internet technology liberates the individual from the body and allows the separate existence of multiple aspects of self that otherwise would not be expressed and that can remain discrete rather than having to be resolved or integrated as in ordinary social participation.” To put it a simpler way: People want their emotions to be heard.
But what happens when those words and actions lose their meaning? Semantic or verbal satiation is when repetition causes a word or phrase to lose its meaning for the listener. For example, say the word “watermelon” 30 times. By the time you get to the end, you probably won’t think of watermelon as a delicious fruit. In fact, you probably won’t think anything of it at all – it will just be a noise that has no meaning. In this instance, the word only loses its meaning for a short period of time and for just one person.
Semantic satiation can also occur when the collective devalues a word or phrase for just one person. For social media community managers, this can happen when trying to understand the emotions behind a brand’s social media mentions. Social sentiment allows us to add the proper context to the volume of conversation around our brands at any given time. Without understanding sentiment, the data we use to guide our work can be incredibly misleading and can incorrectly shift our creative or how we address our fans at scale or on a one-to-one basis. But it’s an imperfect measure that requires a human eye, which means by the time a community manager has read “I love your peanut butter so much I die” for the 100th time, odds are the phrase has lost all meaning. Over time, the true brand love is categorized with the casual conversation and disregarded. Similarly, a fan may be less inclined to believe it when a brand replies “OMG, we love you too!!” for the 100th time.
To understand just how much more expressive we’ve become on social media, Influential analyzed more than 2.6 million branded social conversations over the last ten years. Using natural language processing techniques, they applied a language library of what was considered “normal” (i.e., standard English language and relevant to the context) vs. “exaggerated” (i.e., use of extreme levels of language, memes, or emojis that are not fully relevant or applicable to the context). Based on the above, they developed an index of how extreme language was on a scale of 1 (not extreme) to 5 (extreme and exaggerated language). The index takes into account both frequency and sentiment of the categorized language used.
Over time, to break through the noise and have our voices online be heard, we’ve gotten more exaggerated with how we express our emotions online, which has created two unique challenges for brands in how they assess and address fans on social media.
A primary role for community management is to identify and interact with a brand’s fans and detractors. To do this efficiently, there is a rule of 10 percent: Don’t focus on the top 10 percent of your most committed brand fans or the top 10 percent of your brand detractors because their opinions will never change. Instead, community managers focus their efforts on the middle 80 percent to either push them into the top 10 percent of fans or correct any negative perceptions. Measuring who falls into the 10 percent is a judgment call informed based on brand sentiment and what your brand deems content-worthy of either 10 percent. However, if everyone is speaking in hyperbole, how does a community manager know who truly cares about their brand? Similarly, if everyone’s sentiment falls into the extremely positive or negative, does the rule of 10 percent still apply?
Focusing too hard on distilling the true meaning behind what our target audiences are saying about us online can also create a significant blind spot with understanding where the biggest opportunities lie. Brands have to remember to place the right context in who is talking about your brand online and who is always a part of driving overall business objectives. Influential surveyed 15,000 consumers to better understand how online interaction does and does not play a role in the purchase journey across verticals. The survey’s results were analyzed and consumers were segmented into the following four audiences based on the brand accounts they followed, the social content they engaged with, and the brands from which they purchased:
The two largest audiences turned out to be the ones who weren’t regularly talking about or engaging with brands online.
Finally, in efforts to be seen as more human and have more personality online, brands have adapted the same voice as the audiences from which we seek attention. The result is that our brand voices have grown more polarizing over time as well. Expressing a simple “thank you” to consumers seems too vanilla and corporate, so we say fans are “OMG the literal best. Period.” instead. It goes beyond just community management too. Brand exaggeration permeates: Did you ever think your shaving cream or your microwavable pizza was extreme? Probably not, but online they have to have an electrifying personality to break through the feed and grab your attention.
The second challenge is a sort of self-fulfilling prophecy. Aside from reactively engaging with consumers with more exaggerated language, brands are also actively celebrating extreme emotion and, as a by-product, are setting unrealistic consumer expectations. Over the last few years, more and more brands have resorted to over-the-top efforts to celebrate and get the attention of fans. This approach is generally pitched as a tactic to help make a big splash and spike consumer conversation on social media. When a super-fan named Carter asked Wendy’s how many retweets he would need to get free nuggets, 18 million was their answer and #NuggsForCarter became the darling of social media presentations. Spoiler alert: Carter fell short of his retweet goal, but did get the nuggets.
On paper, #NuggsForCarter was an incredible success with statistics including millions of social media impressions, national news coverage, and Carter became a mini-celebrity in his own right. What it failed to capture, however, was the spawn of copycats that occurred immediately after. Brand pages were filled with requests for outlandish rewards for arbitrary retweets, likes, comments, etc. Brands, anxious for their own magical social media moments, were quick to encourage these requests. And while some brands made good on the requests, far more disregarded them when the conversations didn’t have the same meteoric rise as the original.
Another negative side effect stemming from these over-the-top actions is that it forces regular consumers to be more closely tied to a brand than either they or the brand may ultimately want. Brand fans are sometimes subjected to intense scrutiny in the form of digging up old social media posts or requests for press interviews where they speak as if they’re a part of the brand without proper media training.
Addressing these challenges will ultimately improve how we identify and address our target audiences on social media, and it starts by reevaluating the methods on how we assess our brand sentiment. If evaluating on words alone no longer works or is not as insightful as it once was, brands need to look at adjusting community management moderation and monitoring processes to make sure they are smarter with reactive and proactive consumer engagement.
Reactively, brands need to build a social listening and response model that doesn’t rely purely on qualifiable sentiment so as not to let what consumers are saying distract entirely from what they’re doing. When we arbitrarily assign values to social sentiments that we think are “valuable,” it can disassociate the social conversation from the comprehensive brand health because those behaviors may not be linked to the right business results.
Looking beyond qualifiable data, brands can take a quantitative approach to assess the lifetime value engagement of a single user vs. their value on a specific post. This approach lets a community manager know, regardless of the overall tone, if this is a consumer that deserves an elevated level of attention. For example, looking at the four audiences mentioned earlier, a consumer may initially appear to be “The Sure Thing” based on the way they’ve engaged with a brand’s most recent post or posts. However, a quantitative audit may show they are actually in the “Persuadable” audience due to long stretches of nonengagement. This kind of insight can let the brand know to prioritize engagement to capture this consumer’s undivided attention, so the brand can prioritize content and communications to users who have been engaging with content and positively advocating for a brand off the brand’s page.
Another option is to deprioritize qualitative or quantitative terms, and focus on ways to connect the social conversation to actual business results. Machine learning can be incorporated to a comprehensive social listening plan to build a model that identifies these actions on social and how those actions correlate with business results and objectives at scale. For example, there’s quantitatively supported evidence on previous social campaigns that indicate “sharing” content has a positive/strong correlation with sales regardless of the degree of sentiment in the conversation. And if that’s the insight, it would provide clear direction to a brand to create content that is optimized toward advocacy and shares.
Proactively, brands and agencies need to accept brands do not have to mimic their target audiences to get their attention or win their favor. In recent years, it’s become common to see a brand social persona that is vastly different from the brand’s identity. Brands such as Nike and The North Face are extremely successful online because they stay true to their brand identity.
Aside from adjusting social personas to be more in line with their offline identity, brands need to stop trying to capture lightning in a bottle with over-the-top consumer engagement efforts. As an agency, we’ve seen success making more authentic brand actions with our fans that more appropriately match with their true level of brand love. For Go RVing, a brand that doesn’t have traditional transactional business objectives, social media is used to celebrate everyday fans by having real conversations with them to get to know them better. The result is an increasingly loyal fan base that looks forward to engaging and sharing stories on posts, which leads to more brand-to-consumer interaction.
Finally, and most importantly, the solution comes with understanding this is something that can’t be fixed easily or overnight. Shifting conversation takes time, dedicated effort, and investment at all levels of the marketing program. A temporary effort will yield a temporary result that will definitely not be “lit af.”