SleekView for AI Chatbot by QuantumCloud
SleekView reads AI Chatbot by QuantumCloud's session and lead tables, then exposes intent, entry URL, lead_captured and started_at as columns you can sort, filter and export.
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A lead list works for one lead at a time. Not for the whole channel.
AI Chatbot by QuantumCloud (sold via aichatbot.co) stores chat sessions, transcripts and captured leads in its own tables. The admin shows a recent-chats list and a separate leads list, plus an export button. That works for following up on a single lead. It does not work for running the bot as a sales channel.
Sales typically wants the joined view: every session with its intent, entry URL, lead_captured flag and started_at in one filterable, sortable table. SleekView reads the QuantumCloud session and lead tables directly and exposes exactly that.
Sort by date, filter by intent (pricing, support, demo), scope to a single entry page, save the combination as a named view. The default admin still works for one-at-a-time follow-up. SleekView is the channel-level workspace next to it.
Workflow
How SleekView reads QuantumCloud chat data
Pick the source
Compose the column set
Save and scope the view
Filter, follow up, export
Sample columns
A typical QuantumCloud sessions and leads view
wp_aichatbot_sessions + wp_aichatbot_leads (names vary by version)
| Session | Intent | Entry URL | Lead captured | Messages | Started |
|---|---|---|---|---|---|
| qc_88142 | pricing | /pricing/ | Yes | 9 | May 14 10:02 |
| qc_88141 | demo | /product/ | Yes | 14 | May 14 09:48 |
| qc_88140 | support | /docs/billing/ | No | 6 | May 14 09:21 |
| qc_88139 | general | / | No | 2 | May 13 22:54 |
| qc_88138 | pricing | /pricing/ | Yes | 8 | May 13 20:12 |
Comparison
Default AI Chatbot by QuantumCloud admin vs SleekView
Default AI Chatbot admin
- Chats list and leads list live on separate screens
- Intent and entry URL not surfaced on the standard sessions list
- No combined filter for lead_captured and intent in one view
- Bulk inspection of a single page's chat history requires manual filtering
- No saved per-role view for sales, support and marketing
SleekView
- Read QuantumCloud's session and lead tables as a joined dataset
- Surface intent, entry_url and lead_captured as real columns
- Filter by intent, page or date range and save the result as a named view
- Capability-gated message body column keeps transcripts scoped
- Export the filtered table to CSV for weekly sales reviews
Features
What SleekView gives you for AI Chatbot by QuantumCloud
Sessions and leads joined
Lead_captured becomes a column on the sessions table, not a separate screen. Sales sees every session and which ones converted in one place.
Combined intent and page filtering
Pricing intent on the pricing page, support intent on the docs, demo intent on product pages. Save each combination as a named view your team reuses.
Capability-gated transcripts
Counts, intents and lead flags visible to everyone, message bodies gated to a specific role. Reporting and investigation each get the right surface.
Audience
Who uses SleekView for AI Chatbot by QuantumCloud
Sales teams
Filter to lead_captured = 1, sort by started_at and the weekly follow-up list builds itself. Intent and entry URL tell sales which conversation primed the lead.
Support teams
Filter to support intent and sort by message count to find the long, unresolved sessions. Decide where a human handoff is worth its cost on measured data.
Marketing
Group sessions by entry_url and treat the bot as a measured surface. Run placement A/B tests and judge them on captured leads instead of opinions.
The bigger picture
Why a lead-capturing bot needs a real channel table
AI Chatbot by QuantumCloud is genuinely good at two things: holding a conversation and capturing a lead. Its admin reports on each one separately, which is fine for one-at-a-time follow-up and limiting for channel-level work. A table that joins sessions with the lead_captured flag, exposes intent and entry_url as columns and supports saved per-role views turns the same data into a sales-grade workspace.
Capability gating keeps transcripts scoped so reporting can stay open without exposing chat content. Same data, same bot, completely different operating posture toward the channel.
Questions
Common questions about SleekView for AI Chatbot by QuantumCloud
AI Chatbot by QuantumCloud's session, transcript and lead tables plus standard wp_users metadata for any logged-in chatters. No external service is required and no chat content has to leave the site.
Yes. Filter the sessions view by lead_captured = 1 for the captured set, or expose lead_captured as a column and sort. Counts of total sessions versus captured sessions give the conversion rate at a glance.
Yes. The free version exposes the session and lead tables SleekView needs. Pro versions add richer fields (intent confidence, custom variables) that simply give more columns to surface when present.
Yes. Group or filter by entry_url. Marketing uses this to decide whether the widget belongs on a different page or whether opener copy should change for a specific page.
No, unless the view is explicitly configured to show message bodies. Counts and aggregates do not require reading transcript text, and column visibility is gated by WordPress capability.
Yes. Any filtered set exports to CSV with the columns currently shown. Useful for handing a weekly lead batch to sales or for a quarterly review with revenue leadership.
Yes. Filter by intent (pricing, support, demo, general) and save the result as a named view. Useful when a sales lead focuses on one intent during a campaign.
No. The plugin remains the chat widget, intent classifier and lead capture engine. SleekView reads its tables and turns them into a workable admin surface.
Pricing
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