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Despite the increased volume of internal and corporate communication facilitated by email and other collaboration tools, a Gallup study found that most employees still feel disconnected from their companies.
It doesn’t help that most corporations don’t have a method to ensure the effectiveness of their communications, as measuring this effectiveness is paramount. In B2B and B2C selling, it matters even more — the buyer’s journey can be long and complicated, and purchase decisions could be derailed due to a lack of engagement. In fact, according to the 2016 Content Preferences Survey Report, 47% of B2B buyers look at three to five pieces of content before reaching out to a salesperson.
But what does effective communication hinge on? A clue can be found in how we use the internet. We are used to visiting websites based on what we find most appealing and engaging. Our expectation for entertainment has translated over to our day-to-day communication. People need to be inspired to listen and absorb information, whether that’s to be in the know of what’s happening at a company or seeking out a product.
Considering all of this, where do the challenges in effective communication within organizations lie? How can technology help address them?
Why Facts And Figures Are Not Enough
Many people approach communication incorrectly, from the misconception that conveying facts and figures is enough. Unfortunately, our brains don’t work that way. We are bombarded with an endless stream of information (including our own thoughts). Amid this stream, people tend to be more attuned to that which resonates with their minds the most.
In e-commerce, consumers won’t click on an email or ad without an impactful headline that resonates with them. Many wealthy people prefer the iPhone to a Samsung, for example, and the reason probably has a lot to do with the fact that Apple has done such a good job with its messaging and branding. Even if Samsung offered the exact same capabilities, features and benefits at a reduced price, those facets might not be enough to sway consumer preference. The image of quality, the popularity and the perception of chic have hijacked people’s brains to favor the iPhone.
Just like with consumers, employee involvement and productivity are driven by emotions — by how well employer communication can stick in their minds. Even if employees are required to logically process information accurately, many do so without any sense of engagement, not being able to connect how the task relates to the greater vision of the organization.
The Empathy Challenge
Many content producers know that emotions, not logic, drive consumer action, but they approach this challenge the wrong way. They will often hire marketing experts to generate content solely based on that expert’s prior experience. Then, the marketing experts will produce content, based on their intuition and personal experience, that they feel will connect with the audience.
The problem is that it eschews the power of market research. Instead of solely relying on intuition, content producers should interview real audiences and customers. They need to understand whether and how their content resonates with them. Not doing so is akin to launching an arrow in the dark. Market research, though, can be tough to obtain.
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Real-Time Market Research
Technology can help by approaching market research differently. Instead of sending an actual survey, we can gauge engagement where it is happening — Facebook, Instagram, Twitter, blogs, etc. Platforms like Twitch and YouTube, for example, have given us an actual indication of how real-time customer reactions can help streamers adjust their content to suit the needs of their audience. Indeed, more platforms are coming up to bring that level of feedback, even in other contexts like peer-to-peer content reviews from bloggers and others for freelance and journalistic work.
But how can we further break things down to better understand what content strikes a particularly emotional chord among audiences? What data points would help us understand what customers or employees are feeling or how they are reacting?
- Tools that provide grammar and content correction. Several of these tools use machine learning to tag sentences to specific thoughts and feelings as they happen within certain contexts. The sentence could be analyzed around two aspects of customer sentiment: tone and emotion. Being able to associate the structure of a sentence with the tone and emotion could give us a treasure trove of data. That data could help marketers predict customer responses to a specific type of content based on historical trends.
- Tools that track sentiment. Sentiment analysis is used to determine whether the content contains negative, positive, or neutral emotions. Using natural language processing (NLP) and machine learning, sentiment analysis trains machines to learn from known examples of emotions in text and machines to detect sentiment automatically. Marketers always want to create positive associations with their products via the messages they share.
- Tools that track the performance of messages. There are also tools that track how will messages do in driving traffic to a company’s website, and then once on the site, how long the visitor stays, which pages are visited and the number of returning visitors. In general, the goal of outbound communication is to drive traffic to the website or registration page. Tools such as these offer robust, quantitative summaries of how content has performed, but they can’t tell us anything about why it has performed as such or how it will perform in the future.
In today’s sensationalism-driven world, one of the true value propositions of technology lies in giving us a way to measure shareability and storytelling impact to make our employees more engaged, motivate consumers to make purchases, and keep audiences tuned in. In addition, technology can help democratize and revolutionize the content approach to communicating with our audiences, in both commercial and non-commercial contexts, according to the shifting trends posed by the media.
