LoreAds • Practical guide
Contextual advertising for AI apps
Contextual advertising matches an ad to the subject of a user's current experience rather than relying primarily on a persistent behavioral profile.
What does a contextual AI ad look like?
Imagine someone asking a chatbot how to organize a remote team's work. After the assistant answers independently, the interface may show a separate card labeled Sponsored, featuring a project management tool, a short description and a link. The sponsorship is visible and does not become part of the assistant's own recommendation.
In LoreAds' design, partner chatbots send a short, non-sensitive topic or question signal to match campaigns by category. The placement is optional: a system should be able to return no ad.
Contextual ads versus behavioral ads
- Contextual matching: uses the immediate topic or page/conversation category to select relevant advertising.
- Behavioral targeting: may use stored browsing history, interests or cross-session identifiers.
- Critical distinction: even contextual systems may process personal information if the signals contain identifiable data or are linked to accounts. Minimize what is transmitted and document retention.
How a campaign is prepared
- An advertiser creates a concise headline, one supporting line and a destination URL.
- They choose up to three relevant topics and optional targeting settings.
- They select campaign dates, a total budget, a daily ceiling and a cost-per-thousand-views tier.
- The campaign is submitted for human review. The landing page must match the message and comply with restrictions.
- When commercial delivery is available, eligible placements depend on publisher integrations, topic relevance, approvals and budget limits.
For the current beta, advertisers can create drafts and submit creatives for review, but paid delivery and online deposits are disabled. See how LoreAds advertiser campaigns work.
What a publisher should control
- Placement position, visible Sponsored labels and accessibility.
- Topic eligibility and exclusions for sensitive conversations.
- Request limits, timeouts, and the interface when no ad is returned.
- Accurate impression and click reporting without artificially inflating events.
- Privacy notices, data minimization and a way to disable the integration.
How to evaluate ad quality
Look beyond fill rate. Review whether the sponsor matches the question, whether the destination is trustworthy, whether ads interrupt reading, and whether readers can distinguish sponsored content from chatbot responses. Check page loading time and layout stability. Claims about return on ad spend need real measured campaign data.
Frequently asked questions
Does contextual advertising require full chat transcripts?
No. Many use cases can work with a short category or topic. LoreAds asks publishers to avoid sending full transcripts, identifiers, sensitive information or user histories.
Are all AI conversations suitable for ads?
No. Sensitive topics, vulnerable users and safety-critical assistance warrant exclusion or additional controls.
Can advertisers run paid campaigns on LoreAds today?
Not yet. The current evaluation beta supports preparing and reviewing campaigns; commercial delivery requires separate activation and safeguards.