5X your brand revenue from the AI Purchase Channel in half the time

GEO (Generative Engine Optimisation), AEO (Answer Engine Optimisation), and LLM Optimization all carry the same assumption: AI is a search engine, and your job is to rank in it. That framing puts you in a reactive posture — optimise content, check a score, optimise again. It treats AI as a tool a human uses to find things, and your job as making your content slightly more findable than your competitors'. Slingso starts from a different premise. AI assistants aren't just surfacing content — they are completing transactions, comparing prices, and shortlisting products. Buyer agents are beginning to purchase autonomously with no human in the loop at all. The question isn't 'does our content rank in AI?' The question is 'is our brand winning the purchase decision inside the channel?' That's a revenue question, not an SEO question. Slingso is the agent you hire to answer it — and to change it.

Nothing, if visibility is a means to an end. The problem is when it becomes the end itself. Visibility means your brand name appeared somewhere in an AI response. That's an impression — the same vanity metric that made CMOs feel good about banner ads in 2003. An impression doesn't tell you whether the AI recommended your product, whether it was first in the list, whether it named a competitor instead, or whether a purchase happened. Slingso's leading metric is purchase likelihood: how likely your specific product is to be the one an AI assistant recommends during a real shopper journey. The lagging metric is attributable revenue from the AI channel. Mention rate (what others call visibility) is a supporting data point — useful context, not the goal.

No — and this matters. Purchase intent ('best protein powder under £40') is just one moment in the journey. A consumer's AI shopping session typically starts weeks earlier: 'I want to start strength training, what do I need?' Then category research: 'what should I look for in a protein supplement?' Then comparison: 'Gymshark vs Myprotein protein'. Then, finally, a purchase decision. AI assistants maintain conversational context across a session. A recommendation made during the research phase often determines the purchase outcome three queries later. Slingso simulates your target personas' full AI shopping journeys — from first awareness through comparison and purchase intent — across ChatGPT, Gemini, and Perplexity. Winning at purchase intent but losing at research means you're losing the channel. We track the whole chain.

Because a dashboard requires a person. Someone has to open it, interpret the numbers, decide what to do, brief a writer, review the content, get it published, then check the dashboard again weeks later to see if it moved. That loop takes 4–6 weeks per cycle and requires headcount you don't have. The AI purchase channel moves daily — models update, competitor content goes live, pricing shifts across channels. A dashboard captures a moment. Slingso's agent owns the loop continuously: every day it simulates purchase journeys across AI assistants, every week it analyses patterns and competitor positions, every few weeks it writes content and brings it to you for approval. Your job is 15 minutes of weekly review. The agent owns the channel.

Peec and Hall give you a score. Slingso changes it. Both tools tell you where you rank in AI responses — that's where they stop. You still have to figure out why, decide what to do about it, brief someone to write the content, get it published, and check again in a month. Slingso's agent does that entire loop: it diagnoses why competitors are winning specific queries, researches what content is getting them recommended, writes the content that closes the gap, asks for your approval, and tracks whether it improved purchase likelihood and attributable revenue. The monitoring is the starting point, not the product.

Yes. The Analyse loop maps where competing products are listed — DTC site, Amazon, Walmart, specialty retail — and what they charge on each channel. When a competitor wins an AI purchase recommendation because they're cheaper on Amazon, or because they're running a 20% promotion, the agent surfaces that alongside specific suggested actions: adjust price, list on a new channel, run a counter-promotion. Content optimisation alone can't close a pricing gap.

Yes. Perplexity triggers a shopping result on 92% of consumer queries and has native buy buttons. ChatGPT Shopping surfaces product cards with purchase links directly in the conversation. Google AI Mode connects to Google Shopping. Agentic AI — where the assistant completes the purchase without the consumer seeing a traditional results page — is already in early release. This channel is not arriving. It's here.

Enter your URL. We scrape your site, identify your hero products and target personas, then simulate their full AI shopping journey — from first awareness through comparison and purchase intent — on ChatGPT and Gemini. You see your exact channel position: which products led recommendations, which didn't appear, who appeared instead of you, and 2–3 specific things to do about it immediately. Takes about 30 seconds to submit. No account required.

The agent learns your brand's tone, positioning, and product details from your site and from every piece of content you approve over time. Before anything is published, you read it. Edit it if it's off, or reject it entirely. Nothing goes live without your sign-off. The approval gate is not a formality — it's the architecture.

The agent runs daily: simulating purchase journeys, diagnosing gaps, generating content. Your active time is 15–20 minutes per week — reviewing what the agent produced and approving or rejecting it. Everything else is automated.