When someone searches on social, what do they really want? Annaleis Montgomery at Tug Agency explains how AI is helping brands to deliver on customer expectation.
Social search has moved beyond just a concept and into an actuality that agencies are fighting to nail. It’s becoming a primary way audiences discover brands and products, with search behaviours shifting from traditional engines like Google to platforms like TikTok, Instagram, and YouTube. In fact, according to a study by Tint, over 75% of consumers have used social media to search for or discover new brands and products.
AI is at the heart of this transformation. Gone are the days when a simple keyword match was enough to surface relevant content. Today, AI delves into the very essence of user intent, context, and human emotions to deliver a more nuanced, effective experience. This shift means marketers can’t afford to stick to traditional SEO strategies, but need to embrace an intent-focused approach to authentically connect with audiences at all steps of their user journey, which includes social searches on social media platforms.
Deciphering intent
A sophisticated interplay of data analysis ius needed to go beyond surface-level queries. AI reviews user behaviour, engagement patterns, and content to paint a big picture. AI can detect user intent in a number of ways.
One of these is through sentiment analysis. This allows AI to understand the emotional tone behind a user’s language. Are they expressing frustration, curiosity, excitement, or a need for information? Sentiment analysis identifies nuances in phrasing, emojis, and even the pace of interaction to infer underlying emotions and ultimately intent.
Then there are contextual cues. AI doesn’t just look at individual keywords; it considers the surrounding conversation, the user’s past interactions, and their demographic information. If someone consistently engages with content about sustainable fashion, AI understands their ‘search’ for a new pair of jeans isn’t just about finding a piece of clothing, but likely one that aligns with their eco-conscious values.
And lastly, there’s behavioural data. Every click, like, share, comment, and reach provides valuable data. AI algorithms analyse these engagement patterns to understand what resonates with a user. If a user consistently watches long-form videos on a specific topic, AI learns they prefer in-depth content for that subject, influencing future search results.
Although keywords still play a role in the initial analysis, they can’t capture the fluidity and complexity of human communication on social platforms. A user searching for ‘best coffee’ might be looking for a local cafe, a recipe for brewing at home, or even a review of a new coffee machine. Traditional keyword matching would struggle to differentiate these intents, leading to less relevant results.
Content for intent
Given this strategic evolution, marketers must shift their focus from stuffing keywords to creating content that truly resonates with diverse user intents.
What exactly does this involve? Firstly, SEO teams need to understand the ‘why?’ behind the search. Instead of asking what users are searching for, they need to focus on why they’re searching for it. What problem are they trying to solve? What aspiration are they pursuing? What emotions are being expressed?
Secondly, thorough user journey mapping needs to happen. Teams need to acknowledge that users have different needs, questions, and intentions at different points in their search journey. Because of this, different stages of the user journey require different types of content. For example, a user in the awareness phase might need informative blog posts, while another in the consideration phase might be looking for product comparisons or testimonials.
And lastly, there needs to be a prioritization of value and empathy. Content that provides genuine value and demonstrates empathy for the user’s situation will perform better in an AI-driven search environment. SEO teams must focus on solving problems, answering questions, and inspiring action.
Measuring success requires moving beyond traditional KPIs. SEO teams now need to look at metrics like sentiment shifts (as mentioned earlier, we’d want to prioritize content that had a ‘positive’ sentiment), as well as the more classic metrics like comments and shares that help understand engagement. We can draw similarities between a ‘like’ and a ‘click’, which we use to measure SEO performance, and ‘estimated reach’, which is similar to an organic impression, as it shows how many unique users have seen the content without it being paid for.
Like SEO, social search comes with a whole host of performance metrics and touchpoints we need to understand to help us pinpoint gaps, opportunities, and instances of growth.
Stay relevant
AI-driven social search is the new way to connect with users by understanding their deeper motivations. To truly succeed, marketers need to know how to achieve this. Traditional marketing and SEO no longer accurately represent a user’s search journey. Going beyond the norm and exploring other organic search methods, as well as using AI-powered searches, can help us understand a user’s intent and facilitate that journey to conversion.
If your content isn’t optimized for this intent-driven AI, you’re essentially invisible to a significant portion of your target audience. Users are increasingly interacting with search in conversational ways, expecting immediate, relevant answers, often directly within the search interface itself. Additionally, if your brand isn’t producing content that AI can ‘feature’ – such as structured FAQs, how-to guides, or comparative analyses – you’re sacrificing your visibility.
For Tug, understanding and leveraging this shift is paramount to keeping our competitive streak and clients happy. Our proprietary Helpful Content Tool allows us to audit content at scale, score helpfulness, and identify areas to optimize in line with how AI search algorithms reward helpfulness with greater search visibility. Providing users with a specific scoring criterion, the tool helps overlay content optimization efforts with search and business performance KPIs.
As we look forward, social search is no longer a prediction but our reality. By embracing the evolution of AI-powered search and adapting our strategies, marketers can unlock opportunities to connect with their audiences on a deeper, more meaningful level.