Owned, Earned and Paid have been discussed for years. Earned is currently having its moment. For years organisations have focused their efforts on Paid and Owned.
It has never been more important for earned media that matters more than ever. Recent data and commentary show earned media is now the most trusted layer of the paid/owned/earned mix, especially when it comes to credibility and influence.
61% of B2B buys prefer a rep free buying experience. 73% actively avoid suppliers who send irrelevant outreach according to Gartner. Before anyone talks to sales, your buyer is asking people directly or indirectly whether they trust you and what they really think about you.
This is in the form of:
- Niche communities, Reddit and subreddits
- Review sites, G2/Capterra, Trustpilot, app store reviews
- Increasingly, AI Agents and LLMs, asked: “What are people saying about [brand]?”
In those spaces and tools, people are looking for the right signals to assess credibility:
- Are there reviews about how customer issues are handled?
- Complaints?
- Do the positive reviews sound specific and real?
LLMs and AI assistants have accelerated this. Instead of manually trawling through sites, buyers can now ask a model to summarise what the web says about you. That means your behaviour across support tickets, documents and how you handle reviews is condensed into a narrative you are no longer in charge of. Those interacting with your brand, who have had an experience with it are now writing the narrative.
Trust matters more than your ads
You can ‘control’ the narrative on visible channels you own (your website and your social channels). In the wild, you don’t control:
- The review someone leaves after a frustrating implementation.
- The comment they post about your support.
- The way an LLM paraphrases your reputation based on public content.
What buyers see there shapes whether they even believe your ads.
A typical journey now looks like:
- They see or hear about you (ad, event, thought leadership, referral).
- Look for referrals from peers: “Has anyone worked with them?”
- Scan reviews and forum threads.
- Ask AI agents/ LLM’s questions such as: “What are the pros and cons of [brand]?” or “How credible is [brand]?”
If your behaviour doesn’t create the right trust signals, no campaign can repair that. The conversation about you is being triangulated from how you act and treat customers.
The Trust Signals Framework:
Every review cannot be scripted, it is impossible to manage every expectation, but you can deliberately shape the signals that feed them.
- Audit your customer journey
What are people saying about your company? What is the sentiment? What are the frustrations and can they be fixed?
- Review recent wins and losses. Understand which reviews did they come across, which communities they asked, what did the tools say about them (including LLMs)?
- List the touchpoints they used, named sites e.g. G2, Reddit, Trustpilot, specific groups.
The outcome becomes a simple “decision map” that your customer uses, that you don’t use to advertise on.
- Create better stories through behaviour
Reviews and AI summaries are downstream of how you behave.
- Look closely at the logistics in your company? Is it easy to be a happy customer. Putting your company?
- Treat escalations as chances to create a “how they really showed up for us” story.
- Systematically close the loop on issues, then follow up to check things stayed fixed.
The outcome more satisfied customers with the experience and willing to leave positive, describing specific feedback, the kind that feels real when read by their peers.
- Curate and amplify trustworthy proof
Build a system to encourage a good experience; this becomes your new model for gaining positive visibility.
- Ask at the right moments, after a win, a successful rollout, or a strong NPS response with a simple request to leave an honest review for your buyers.
- Incentivise short case stories, “before/after” narratives and with real quotes.
- Respond publicly to reviews (good and bad) in a way that shows your values.
The outcome is a landscape of reviews, stories and responses that are credible and are likely to be picked up by LLM’s.
- Watch and learn from your signals
Closely monitor your signals. It is impossible to fully control how AI tools summarise you, but you can keep an eye on the patterns and try not to let a negative theme build and go unchecked.
- Regularly search for your brand on key review sites and communities; note recurring themes and language.
- Periodically ask AI tools simple, buyer like questions about your brand and category; look at how you’re described versus how you want to be.
- Feed what you learn back into operations: if support response time keeps coming up, fix support; if “expensive but worth it” appears, embrace and find new ways to frame value.
The outcome, a stronger feedback loop where behaviour and communication based adjust to the signals that shape perception, instead of pretending they don’t exist.
Bringing it together
Your buyers are stitching together a picture of you from private conversations, public reviews and AI generated summaries long before you speak to them. Will your brands advertising alone convince customers?
This is how you design for trust, by how you handle problems, manage reputation and respond to reviews. These are some of the practical ways to manage signals that matter. Only then will they start working in your favour. Then, when someone asks an LLM or a friend “Are they worth it?”, the answer has already been formed, by 70% done according to Gartner. It leans in your favour, before a single campaign goes live.