Abhord Quickstart Guide (2026 Refresh)
This refreshed edition reflects platform improvements through March 2026 and new best practices for GEO/AEO teams working across answer engines and LLMs.
What’s new since the last edition
- Cross-LLM surveys: one run fans out to multiple models and aggregates results with confidence scoring.
- Aspect-based Sentiment v2: finer-grained sentiment on features, pricing, UX, support, and trust.
- Normalized Share of Voice (SoV): deduplicates cross-channel mentions and weights by source authority and reach.
- Competitor Watchlists: track families of brands, synonyms, and product lines with anomaly alerts.
- Playbooks and Scheduling: templatize recurring surveys and automate weekly/monthly runs.
- Cost and Safety Guardrails: per-run spend caps, token limits, and citation-required prompts to reduce hallucinations.
1) Initial setup and configuration
- Create your workspace
- Name, timezone, primary language(s).
- Invite teammates and assign roles: Admin, Analyst, Viewer.
- Connect data sources
- Search (SERP), news, forums (e.g., Reddit), social, app stores, YouTube, GitHub, docs, and your owned content (sitemaps, knowledge bases).
- Set lookback window (e.g., last 90 days) and crawl cadence.
- Add LLM connectors
- Bring your own keys for the models you want to test (e.g., multiple providers/versions).
- Enable Guardrails: max tokens, per-run budget, PII redaction, and “cite-required” prompts.
- Define entities and synonyms
- Brand, product lines, SKUs, and common misspellings.
- Add competitor entities now—it accelerates benchmarking later.
- Create topics and aspects
- Standard aspects: features, price/value, performance, reliability, support, integrations, privacy/trust.
- Add domain-specific ones (e.g., “battery life,” “HIPAA,” “latency”).
- Integrations and notifications
- Slack/Teams alerts for spikes; webhook to BI; CSV/JSON exports.
- Set retention and export policies to match compliance needs.
Pro tip (new): Turn on “Cross-channel dedupe” and “Authority weighting” in Settings > Scoring to improve SoV fidelity out of the box.
2) Run your first survey across LLMs
Goal: Understand how major models describe your product vs. competitors today.
- Start a new Survey
- Objective: Brand and feature perception.
- Timeframe: Last 60–90 days for a realistic baseline.
- Sources: Select SERP, news, forums, and your docs.
- Choose LLM pool
- Select 2–4 models for breadth (e.g., a generalist, a reasoning model, a long-context model).
- Sample size: Start with 30–50 prompts/model; increase after calibration.
- Draft the prompt template
- Use variables for entity, aspect, and channel. Require citations to snippets retrieved by Abhord.
Example prompt
“You are evaluating how {entity} is described across {channels} in the last {timeframe}. Using only the provided snippets, extract:
- Mentions (unique, deduped)
- Sentiment by aspect (features,