SleekView for ManyChat for WordPress
ManyChat's WordPress integration writes every webhook event into the manychat_event custom post type. SleekView reads it directly so chat marketers, lifecycle ops and analysts each get a sortable, filterable, inline-editable view over the slice they actually run.
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Tens of thousands of events, one chronological list
ManyChat's WordPress integration receives webhook events from Messenger, Instagram, WhatsApp and SMS flows, then writes them into a manychat_event custom post type. Meta captures event_type (subscribed, flow_completed, tag_added, custom_field_set), channel, flow_id, tag_id and subscriber_id. Every flow trigger, tag application and subscription action lands in the same indexed schema.
The default admin renders that schema as a chronological event list. It is comprehensive and unreadable: "all flow_completed events on Instagram for flow id 4231 this week" is not a single click away. "All subscribers tagged vip in the last 24 hours" requires manual eyeballing. The data is there, the indexes are there, the workspace is missing.
SleekView reads the manychat_event post type directly. An event view shows event_type, channel, flow id, tag id and subscriber as proper columns, sortable by any of them. Inline edits route through ManyChat's CRUD where supported, so tag and status changes stay in sync with the platform. Same ManyChat webhook data, presented as a workspace the marketing team can actually navigate.
Workflow
How SleekView reads your ManyChat for WordPress schema
Connect the ManyChat events
Compose your column set
Save and scope the view
Edit inline and ship
Sample columns
A typical ManyChat for WordPress event view
wp_posts + wp_postmeta (manychat_event)
| Event | Channel | Flow | Tag | Subscriber | Received |
|---|---|---|---|---|---|
| Subscribed | welcome_dm | lead | @laralovesplants | Apr 24 10:58 | |
| Flow completed | Messenger | demo_signup | demo-booked | Tom Bailey | Apr 24 10:42 |
| Tag added | — | vip | Ria Patel | Apr 24 10:31 | |
| Custom field set | preferences | — | Sam Cole | Apr 24 10:18 | |
| Unsubscribed | Messenger | — | — | Mia Brewer | Apr 24 09:51 |
Comparison
Default ManyChat for WordPress admin vs SleekView
Default ManyChat event log
- Event log renders chronologically with a fixed column set
- Filtering by event_type, channel and flow_id together requires re-clicking facets
- Tag and custom field meta are not surfaced as columns on the row
- Bulk-tagging subscribers requires opening each one in ManyChat
- No saved per-role views (marketing campaign vs lifecycle ops vs analyst)
SleekView
- Read directly from manychat_event with meta surfaced as proper columns
- Pivot event_type, channel, flow_id and tag_id into typed columns
- Inline-edit tags and subscriber fields across many events in one pass
- Save filtered views per role ("Flow completions today", "VIP tag adds")
- Switch between event, subscriber and tag breakdowns in one tabbed page
Features
What SleekView gives you for ManyChat for WordPress
Events with real ManyChat columns
Combine manychat_event fields with channel, flow and tag in one filterable workspace. Replaces a chronological event firehose with a workspace marketing and analysts can actually navigate.
Filter combinations the default list can't
Filter to channel of Instagram and event_type of flow_completed and flow_id of demo_signup in one click. Saved filters become role-specific views for marketing, lifecycle and analytics.
Inline edits through ManyChat CRUD
Update tags, change subscriber status or annotate events inline. Edits route through ManyChat's hooks where exposed so the platform stays in sync on the next webhook.
Audience
Who uses SleekView for ManyChat for WordPress
Chat marketers
Filter to flow_completed events on a single flow id and see which subscribers actually finished. Pivot to retarget the cohort without exporting anywhere.
Lifecycle ops
Filter to tag_added events with a specific tag id and watch growth in real time. Bulk-add or remove tags inline across the filtered set.
Analysts
Sort by event_type and date to attribute opt-ins to launch campaigns. Export the filtered set for deeper analysis when a slide needs the raw data.
The bigger picture
Why a high-volume chat marketing log needs a workspace
ManyChat is a high-volume integration. Even a modest campaign can fire tens of thousands of events into WordPress in a week, and reading that as a list is impossible. The default admin treats every event equally, which is correct as an audit trail and useless as a management surface.
A filterable, sortable, role-scoped table changes posture entirely. Marketers filter to a single flow id and see exactly who completed it. Lifecycle ops watches tag growth in real time.
Analysts attribute opt-ins to a campaign by sorting one column. Same ManyChat events, same WP post type, completely different operational posture without re-architecting the integration.
Questions
Common questions about SleekView for ManyChat for WordPress
ManyChat for WordPress' own manychat_event custom post type and its meta. No data is copied, no analytics service is added, the table renders straight off the log the integration already writes per webhook event.
Yes. ManyChat writes one event row per webhook regardless of channel, with the channel name in meta. SleekView treats Messenger, Instagram, WhatsApp and SMS as slices of the same dataset so the table includes them automatically.
Yes when the plugin exposes a tag CRUD endpoint. SleekView calls the same action ManyChat exposes, so tag adds fire the existing webhooks and persist to the ManyChat platform on the next sync.
Yes. Custom field updates land with event_type of custom_field_set and the field key in meta. SleekView surfaces those keys as filterable columns so per-field cohort analysis is one filter click away.
No. WordPress indexes the post type by date and ID, and SleekView batches meta joins behind a cache. Event tables with millions of manychat_event rows render the table in well under a second on typical managed-WordPress hardware.
Yes. Each saved view is scoped by WordPress capability so marketers see flow-completion views while analysts see growth-attribution views. Each role saves its own filter and column presets.
Indirectly. Pair flow_started count with flow_completed count per flow_id by saving two views over the same dataset. The two row counts make the drop-off shape readable for any active flow.
Yes. Any filtered view exports to CSV with the exact column set on screen. Useful for campaign post-mortems where someone needs the raw event log, not a chart screenshot.
Pricing
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