Social Listening's Endgame: Navigating a Future Beyond Obsolescence

Since eCairn's establishment in 2006, we have been at the forefront of the social listening industry, witnessing its transformation from the beginning of social networks to the current era of advanced analytical tools.

Facebook was born in 2004, Twitter in 2006. Linkedin at the time was primarily serving as a repository of professional profiles. Back in 2006, blogs were the primary platforms for online discourse.

We’ve seen the rise of Radian6 (created in 2006) and its acquisition by Salesforce and the success of a few others. Yet, the path for most has been full of challenges.

It was and still is clearly extremely difficult to create a sustainable business model in a field where the perceived value is limited to a select group of experts within organizations- specifically, the social media marketing specialists.

Traditional Social Listening: A Labor of Insights

Typically, social listening within corporations is done as follows:

• A dedicated social intelligence team, usually operating under the marketing umbrella, is responsible for delivering insights and analytics, utilizing platforms such as Talkwalker, Synthesio, Traackr, … and eCairn to enrich the company's understanding and engagement with digital communities.
• This team generates a set of standard reports including metrics like brand share of voice , trending topics and competitive positioning, which often fall short of catering to the unique needs of end-users.
• It also performs ad-hoc studies to research specific products, services, events, … and customer segments
• The visibility and usefulness of social marketing is mainly shown during crisis when management is desperately trying to respond to a story that has gone viral.

When business is good, things are OK. When business is not as good it is the first organization that faces budget constraints.

The results is that nobody is satisfied

• Management perceives little ROI if any from its social listening investment.
• The outcome of the social listening is “one size fits all” and usually the team doesn’t have the responsiveness to provide intelligence when it is needed
• For the social listening team, it's a perpetual cycle of frustration, stemming from unacknowledged value and insufficient resources to deliver.
• Despite their utilities and unique strength ( eCairn specializes in monitoring and profiling opinion leaders within specific vertical) , the social intelligence platforms are often perceived as non-critical, with its value appreciated by only a limited audience within organizations. Vendors can’t build a sustainable business and their users are laid off every few years.

We (at eCairn) often joked that we have more clients than users, as our users introduces us to their new employers, each time they lost their job and moved to another company. A CEO of a company that pivoted from social media marketing to CRM told me a while back: “ social marketing and social selling is something that everyone says is a no brainer … but never implement”.

The Generative AI Revolution

I believe generative AI is making applications obsolete.

All applications.

This is even more relevant for applications whose core purpose is the make data actionable.

Why do you need an application when an intelligence agent (think of a young MBA assistant) can synthesize data for you and provide a recommendation?

After all, when using Google Maps, when you’re told to turn left at the curb … you turn left and don’t ask for reports and datapoints justifying that going right would be a bad decision.

Social listening is mainly reading and interpreting data and generating a description/ summary of this data to someone with a particular profile/need.

• generating a description/ summary : This is the core feature of generative AI.
• reading and interpreting data : This is what retrieval augmented generation (RAG) offers.
• someone with a particular profile/need : This is what prompt engineering delivers.

This has profond consequences for every player down the chain

For users, the integration of generative AI makes social listening obsolete.

Imagine an enterprise equipped with a conversational agent capable of reading and analyzing social media data in real-time. This AI assistant could be accessible to all managers and employees, enabling them to query specific research questions and receive instant responses.

There are many benefits:

1. Immediate answers
2. User friendly conversational interface (like ChatGPT)
3. Ability to tailor the analysis to the user profile and refine it thru ongoing questions/conversations
4. Understanding the landscape beyond the capability of a single tool drawing in diverse data sources
5. Cost savings

For the social marketing people.

Most of them will lose their jobs. Humans will still be required to align the system to the company’s objectives, fight hallucinations and improve the system overtime. Human will also have to ensure the quality/availability of the data sources and personalize the answers with prompt engineering.

However, this is a challenge for many people in the field as these activities require different skill sets compared to what social marketers have been trained on.

For vendors like eCairn

Most of the companies will die and close door. The only pivot that is available for them is to become a specialized engine generating genuine data i.e

• data that you can’t buy off the shelf or get from social media platforms (Twitter, Facebook, Instagram…)
• data that you can't construct easily using a vanilla generative AI.

Fortunately for eCairn, generative AI does not (yet?) understand the multi facet and nuance of influence and the subjective nature of tribes and communities.

So the next step for us is to carefully curate data, educate/train the generative AI to fill that gap and become the Influencer/Tribe- GPT.