How does Strkr's WhatsApp Business CRM integration differ from Pipedrive or other CRM integrations?
Several specific differences. First, the integration uses the official Meta WhatsApp Business Cloud API rather than a scraping bot or a personal number automation, which keeps the compliance posture clean and resilient to Meta policy enforcement. Second, template management, approval tracking, and the session window are first-class product surfaces inside Strkr rather than hidden operational details, so reps see the state they are operating under rather than hitting silent errors. Third, the WhatsApp data lives on the same record as email, SMS, calls, and every other channel, so the account view includes the full relationship rather than being split across tools. Fourth, Strkr's native messaging layer, flow engine, assistant, and dashboards all treat WhatsApp as a first-class channel, so a nurture flow can span email, SMS, and WhatsApp with one definition. Fifth, pricing is included on the Strkr seat price with Meta's own conversation costs passing through at cost rather than a markup.
What does the 24-hour session window mean in practice for how my team uses WhatsApp?
When a contact sends an inbound message, a 24-hour window opens during which the business can send free-form responses. Outside that window, outbound messages must use a pre-approved template with limited content categories (marketing, utility, authentication). The practical implication is that proactive outbound ("hey, following up on your demo request") always uses a template, while reactive back-and-forth within a conversation uses free text. Strkr shows the session window state visibly on every thread with a countdown timer. When the window expires, the compose box switches to template-only mode so the rep sees the state rather than hitting a silent failure. For nurture flows, the designer accounts for session windows automatically: free-form steps inside a window, template steps outside.
How does opt-in work for WhatsApp Business, and what does the audit look like?
Meta requires an explicit opt-in from the contact before a business can send WhatsApp messages. Acceptable opt-in methods include a web form checkbox, an in-app toggle, a reply-to-join SMS flow, or a verbal consent captured through a call recording. Strkr's integration records the opt-in source (which form URL, which message, which call), the timestamp, the IP range (where captured), and the specific consent language the contact agreed to. The audit record is immutable and exportable. When a contact opts out (via reply keyword or UI action), the integration logs the opt-out immediately and prevents further outbound. Re-opt-in attempts after an opt-out are tracked separately so the compliance team can see the full consent history, which is often the exact artifact a regulator requests during an audit.
Can we automate WhatsApp conversations with the Strkr flow engine?
Yes. An inbound WhatsApp message can trigger a Strkr flow, which can read the message content, run Strkr AI classification to determine the intent, and route to the right branch. Common patterns include an auto-acknowledgment that the message was received, a qualification flow that asks a few questions to route to the right team, an FAQ flow that answers common questions through a conversational pattern, and an escalation flow that pulls in a human agent for complex cases. The flow engine respects the session window state so free-form responses only happen when the window allows. Outside the window, the flow uses approved templates. The assistant on the thread can also draft responses for a human rep to review and send, which keeps the human in the loop for sensitive conversations while using automation for the volume.
How does WhatsApp integrate with our broader marketing automation and sales motions?
WhatsApp is one channel in Strkr's broader messaging and automation layer. A nurture flow can send an email on day one, a SMS on day three, and a WhatsApp message on day seven, respecting the consent state per channel at each step. The audience builder for a campaign uses the same filters whether the output is email, SMS, or WhatsApp. The dashboards track response rates, conversion rates, and attribution across every channel so the CMO sees a unified view. The lead router handles inbound WhatsApp like inbound email or inbound SMS, assigning to the right owner based on firmographic fit, lead score, and territory rules. For teams in regions where WhatsApp is the dominant communication channel (India, Latin America, parts of Europe and Africa), this unified approach means the primary channel is treated as a first-class citizen rather than a bolt-on, which affects conversion rates measurably.
What about pricing, rate limits, and the quality tier system?
Meta charges per conversation on the WhatsApp Business API, with pricing varying by region and conversation category (marketing, utility, authentication, service). Strkr passes those costs through at cost rather than marking them up, and the dashboard shows the per-conversation cost per campaign so the team sees the real spend. Meta also sets per-number daily rate limits based on quality tier (1K, 10K, 100K, unlimited messages per day), with the tier determined by signal mix including block rate and user feedback. The integration enforces the daily cap at the send layer, queues excess outbound for the next day, and surfaces the current tier on the sending profile with the signals that are moving it. The admin acts on tier-drop signals before Meta enforces a drop rather than after, and the bulk sending dashboard paces campaigns to respect both the rate limit and the quality-signal budget.
