Abhord Quickstart Guide (2026 Refresh)
This refreshed edition adds updated recommendations for cross-LLM normalization, clearer guardrails for survey prompts, and practical ways to operationalize insights. If you used the previous guide, look for: stronger sampling guidance, improved advice on entity canonicalization, and expanded tips for competitor tracking and alerting.
1) Initial setup and configuration
Before running surveys, spend 20–30 minutes getting the foundations right.
- Create your workspace and project
- Name projects by objective (e.g., “US launch Q2”).
- Set locale(s) and time zone to keep trend comparisons consistent.
- Connect LLM providers
- Use Abhord’s managed connectors or bring your own API keys for major providers (e.g., OpenAI, Anthropic, Google, open-source gateways).
- Add at least 3 distinct models to build a meaningful “panel.”
- Define entities and synonyms
- Add your brand, product lines, and priority features as canonical entities.
- Add competitor names, common misspellings, and product nicknames.
- Set negative keywords to exclude false positives (e.g., “apple (fruit)” if you track Apple Inc.).
- Configure governance
- Roles: assign Owner (billing), Editor (surveys), Viewer (stakeholders).
- Data: select retention window; enable PII redaction if you ingest user text.
- Notifications: connect Slack/email for threshold-based alerts.
- Recommended defaults (new)
- Sampling: 3–5 models, minimum 150 total completions per survey (e.g., 50/model) for stable share-of-voice (SOV).
- Normalization: enable cross-model canonicalization and deduplication.
- Baseline: schedule a baseline survey now to compare against future lifts.
2) Run your first survey across LLMs
Think of Abhord as an LLM “panel test.” You ask structured questions; Abhord aggregates, cleans, and scores responses.
- Choose a survey intent
- Awareness: “Which tools solve X?” “Who are the top Y platforms?”
- Consideration: “Compare Brand A vs Brand B for