# How a mobile growth platform went from 2 to 13+ meetings a month > How a mobile attribution and ads platform scaled from a 2-meetings-a-month internal cap to 13+ meetings a month with SalesMonk's signal-led, multi-product outbound, and expanded into Australia and the UAE without new hires. This mobile growth platform, a mobile attribution suite plus a CPM advertising platform, had internal SDRs capped at roughly 2 meetings a month across a segmented TAM of 2,000-3,000 app-first brands. SalesMonk ran multi-product, signal-led outbound across email, WhatsApp, LinkedIn, and calling, ramping to 13+ meetings a month by month 3 and opening tests in Australia and the UAE, with no new hires. **Industry:** Mobile attribution & advertising **Segment:** AdTech / Mobile growth **HQ:** Southeast Asia **Offer:** Outbound The challenge This mobile growth platform sells two products, a mobile attribution suite and a CPM advertising platform, to app-first brands in fintech, e-commerce, and gaming. Its internal SDRs were capped at roughly 2 meetings a month against a finite, segmented TAM of 2,000-3,000 accounts, each vertical needing its own messaging. Two products meant two distinct GTMs, Southeast Asia gave little traction on email or LinkedIn alone, and the team had no signal-based prioritization to catch triggers like funding, hiring, or app launches. The solution SalesMonk's AI agents ran multi-channel outbound across email, WhatsApp, LinkedIn, and calling, with messaging split by product and persona: ROAS and CPM optimization for the ads platform, post-iOS 14 measurement accuracy and privacy compliance for the attribution suite. Accounts were prioritized on 20+ live intent signals, every touch was personalized from public data like app reviews and Play Store metadata, and AI agents nurtured trial users with usage-based follow-ups. Early wins triggered expansion tests in Australia and the UAE. The results 4 -> 13+ ### Meetings/mo, month 1 to 3 0 ### New SDR hires needed 3 ### Markets in play HOW IT WORKED ## Inside the **outbound engine** Two products, a segmented TAM of 2,000-3,000 app-first brands, and an internal cap of about 2 meetings a month. Here's how SalesMonk turned that into a compounding outbound motion across Southeast Asia and beyond. ### Multi-product outbound campaigns The attribution suite needed technical, integration-focused messaging; the ads platform needed performance-focused storytelling. Crafting distinct, persona-specific GTMs for each was complex and resource-draining, and mass outreach across a diverse TAM of gaming, fintech, and commerce brands didn't work. AI agents ran multi-channel outbound across email, WhatsApp, LinkedIn, and calling, with localized, intent-rich messaging for each persona: growth marketers, Heads of UA, digital marketing managers, and PMMs. Messaging was split cleanly by product. Ads platform outreach focused on ROAS, CPM optimization, and mobile growth. Attribution suite outreach focused on measurement accuracy post-iOS 14, privacy compliance, and SDK simplicity. - Month 1: 4 meetings (3 ads platform + 1 attribution) - Month 2: 8 meetings (5 ads platform + 3 attribution) - Both product lines booking meetings from a single outbound motion ### Intent signals The team had no signal-based prioritization. It was missing timely triggers like funding, hiring, app launches, and intent-rich LinkedIn activity. Accounts were prioritized on 20+ live signals: funding news, hiring for growth roles, app launches, ad campaign reviews, and competitor tool displacement. Outreach landed when an account was actually in motion, not on a fixed cadence. - Outreach prioritized by 20+ live signals instead of static lists - Meetings rated higher for relevance and decision-making authority than previous outreach ### Data insights & personalization Southeast Asia posed a major challenge: email or LinkedIn alone got limited traction, and generic outreach across verticals fell flat. Every outreach included context pulled from public data (app reviews, Play Store metadata, social media posts, and press mentions) and referenced specific milestones or pain points for that brand. As feedback from the sales team came in, the AI adjusted targeting and messaging in real time, with weekly review loops keeping campaigns optimized. - Within the first month, AI agents generated more ICP-fit meetings than the internal SDR team had managed in previous months (~2/month cap) - Improving conversion rates from meetings to opportunities via weekly review loops ### Freemium & trial follow-ups AI agents nurtured trial users with usage-based follow-ups, reaching out after a campaign launch or an inactivity streak. Only high-potential accounts were escalated to the human team. - Trials converted into meetings at key usage moments - Human team focused only on high-potential accounts ### Exploring new markets Beyond Southeast Asia, early campaign success with ed-tech and fintech apps triggered exploratory tests in Australia and the UAE, unlocking new segments without any additional headcount. - Month 3: 13+ meetings, scaling across verticals and regions - No internal team expansion needed BEFORE & AFTER ## From a capped SDR motion to a **compounding meeting engine** Before SalesMonk Internal SDRs capped at ~2 meetings a month Two products needing two GTMs, resource-draining No signal-based prioritization of accounts Little traction in Southeast Asia on email or LinkedIn alone With SalesMonk 4 -> 8 -> 13+ meetings a month over three months Messaging split by product and persona, run by AI agents 20+ live intent signals prioritizing every account Expansion tests live in Australia and the UAE, with no new hires ## Want **results like these**? 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