Optimising for the answer, not the ranking.
More buyers now ask an AI before they ask a search engine. Slice wanted to shape what those systems say about the brand: how often it is mentioned, how it is recognised as an entity, and whether the sentiment attached to it is one a language model will repeat. So we went off-site, and built authority where the models actually read.
Slice wanted the AI systems on side.
The brief was not about rankings. It was about strengthening generative engine optimization: improving brand sentiment, increasing AI mentions and influencing the answers that language models generate about the brand, without leaning primarily on traditional SEO to do it.
You cannot rank your way into an AI answer.
Traditional SEO wins a position on a results page. It does very little to change what ChatGPT or Gemini says when a user asks for a recommendation. That answer is shaped by how widely and how favourably a brand is referenced across the wider web, which is a different problem needing a different approach.
Answers, Not Links
When buyers ask an AI system for options, they receive a synthesised answer rather than a list of links. Being on page one does not guarantee being in that answer, or being described well within it.
Entity Recognition
For a model to recommend a brand confidently, it has to recognise that brand as a distinct, well defined entity. Weak or inconsistent recognition across the web means weak, hedged mentions in the answers.
Sentiment Carries Over
Language models absorb the tone of what is written about a brand. If the prevailing sentiment across forums and articles is mixed, that hesitation surfaces in what the AI tells a prospective customer.
An Off-Site Problem
Almost none of this could be solved on the brand's own website. The work had to happen across the platforms and publications that language models draw on when they form a view.
Four phases.
Build authority where models read.
The primary focus was off-site GEO and authority building. Rather than chasing rankings, we worked to improve how AI systems understand, mention and recommend the Slice brand, across the exact surfaces those systems learn from.
Community Presence
- Large scale Reddit optimization, over 1,000 comments in six months
- Quora optimization, over 500 answers in the same window
- Presence built in the discussions language models draw on most heavily
Digital and Paid PR
- Digital PR campaigns to expand favourable coverage
- Paid PR across digital publications for reach and credibility
- Coverage placed where it strengthens the brand's reference footprint
Authority and Mentions
- Guest post acquisition on relevant, credible sites
- High authority backlinks to reinforce trust signals
- Brand mention expansion across the wider web
AI Entity and Sentiment
- AI entity optimization so models recognise Slice as a distinct, well defined entity
- Brand sentiment management to shape the tone models absorb
- Content optimised specifically for citation by AI systems
The work, and what it moved.
Execution Scale
| Activity | Execution |
|---|---|
| 1,000+ comments in 6 months | |
| Quora | 500+ answers in 6 months |
| PR | Paid PR and digital publications |
| Authority | Guest posts and high authority backlinks |
| Focus | Brand sentiment and AI answers |
What the Campaign Moved
Five decisions that shaped the answers.
Generative engine optimization is still new enough that most brands are not doing it at all. This worked because it treated the AI answer as the actual product and built toward it deliberately.
Off-Site by Design
The decision to lead with off-site authority rather than on-site SEO matched the problem. AI answers are shaped by the wider web, so that is where the effort went.
Presence Where Models Read
Reddit and Quora are among the most heavily referenced sources for language models. Over 1,000 comments and 500 answers put the brand into those conversations at scale.
Entity Before Opinion
AI entity optimization ensured models recognise Slice as a distinct, well defined entity. A model cannot recommend confidently what it cannot identify clearly.
Sentiment Managed, Not Left to Chance
Because models absorb the tone of what is written, brand sentiment was actively managed rather than assumed. Trusted brands get recommended, hedged ones get qualified.
Content Built to Be Cited
Material was optimised specifically for citation by AI systems, so the brand appears as a source rather than an afterthought when a model composes an answer.
A different scoreboard for a different game.
The hardest part of GEO is that the win does not show up as a rank you can screenshot. It shows up in what a language model says when nobody from the brand is in the room. That demands a different kind of patience and a different kind of measurement.
Answers Over Rankings
The goal was set from the start: influence AI-generated answers rather than climb a results page. That reframing decided everything that followed.
Into the Conversations
Large scale Reddit and Quora work, over 1,500 contributions in six months, placed the brand inside the discussions that language models weight most heavily.
PR and Authority
Digital and paid PR, guest posts and high authority backlinks widened the brand's reference footprint across credible, well read sources.
Entity and Sentiment
AI entity optimization and active sentiment management shaped both whether the models recognise the brand and how warmly they describe it.
A Brand the AI Recommends
Stronger AI visibility, more mentions across LLMs, sharper entity recognition and improved trust in the answers those systems generate about Slice.
Combined Reddit and Quora contributions in six months, placed where language models learn what to say about a brand.
- Ready to grow
What does the AI say about your brand?
Ask ChatGPT or Gemini to recommend a provider in your category. If your brand is missing, hedged, or described in someone else’s words, that is a generative engine optimization gap, and it is only going to matter more.
- See how AI systems currently describe you
- Build presence where language models read
- Strengthen entity recognition and sentiment
- Make your content the source AI cites