Build event recommendations

Use this guide when your product needs to recommend trade shows from a company website, ICP description, target audience, or existing event shortlist. Lensmor exposes more than one event-discovery endpoint because recommendation workflows differ by starting point. The main design choice is whether you already know the candidate event set.

Choose the right endpoint

Starting point	Recommended endpoint	Why
User wants to browse events by keyword, country, city, or date	Events list	Returns a neutral paginated catalog.
User provides a company website or target audience and wants recommended events	Apply profile and get recommended events	Applies profile context and returns scored event recommendations.
User already has one event and wants a compact fit result	Events fit score	Scores one event without returning a full recommendation page.
User already has several candidate event IDs and wants them sorted	Events rank	Ranks a known shortlist.
User knows an exhibitor company name and wants related events	Exhibitor event search	Reverse-lookups events from company name context.

Recommendation-first workflow

Collect profile inputs

Ask for a company website, target audience description, or both. Better input context usually produces better recommendations.

Apply profile matching

Call POST /external/profile-matching/actions/apply-recommended-events/paged with filters such as country, category, date range, or attendee count.

Review event metadata

Use match_score, matched_exhibitor_count, geography, dates, and event size fields to decide what to show first.

Drill into the chosen event

Fetch event detail, preview exhibitors/personnel, and unlock event coverage only when needed.

curl -X POST "https://platform.lensmor.com/external/profile-matching/actions/apply-recommended-events/paged" \
  -H "Authorization: Bearer $LENSMOR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "company_url": "https://acme.example",
    "country": "United States",
    "future": 1,
    "page": 1,
    "pageSize": 20
  }'

Example: rank a shortlist

Use ranking after your product has already narrowed the event universe.

curl -X POST "https://platform.lensmor.com/external/events/rank" \
  -H "Authorization: Bearer $LENSMOR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "event_ids": ["139574", "139575", "139576"]
  }'

Interpreting recommendation data

match_score is useful for ordering and visual ranking. Avoid treating small score differences as exact mathematical truth.
matched_exhibitor_count indicates whether an event has account overlap with the profile context.
unlocked tells you whether full event-scoped coverage is already available.
profile_version and active_result_version help clients understand result freshness.

UX recommendations

Let users edit profile inputs and rerun matching.
Show enough event metadata to make the recommendation explainable: location, date, scale, and matched exhibitor count.
Avoid spending credits during the recommendation step. Use unlock flows only after the user selects an event.
Keep pagination controls visible. Recommendation results can span multiple pages.

Identifiers

Understand id, eventId, and event-scoped identifiers.

Credits and access

Learn which follow-up workflows can consume credits.

​Choose the right endpoint

​Recommendation-first workflow

​Example: recommend events from a company website

​Example: rank a shortlist

​Interpreting recommendation data

​UX recommendations

​Related concepts