Your Revenue Rocket Newsletter | Volume 51

Plus: šŸšØ Why 78% of SaaS Reps Missed Quota in H1

Author

Rafe Houston
July 09, 2025 ā€¢ Estimated Reading Time: 6 minutes

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TODAYā€™S TOP PICKšŸŽÆ

A Q&A on What Broke in H1 and How a Sales Operating System Can Fix It in H2

Nearly 50% of SaaS companies missed revenue targets in Q1 2025. And 78% of reps missed quota.

Thatā€™s not a rough patch. Itā€™s a system failure. In this Q&A, we unpack:

  • Why data alone isnā€™t enough to drive action

  • What happens when strategy has no execution layer

  • How companies like Fospha are turning it around with a Sales Operating System

If youā€™re relying on dashboards and headcount to fix performance, H2 will look like H1.

LEADING VOICESšŸ“£

AI Is A Great Leveller But Only If We Let It Be

Age, race, background, fancy titles.... AI should remove the gatekeepers. The only real barrier Iā€™ve felt? ā±ļø Time

As a CEO, mum of three, mid-renovation and recovering from a health scare, Iā€™ve had to be deliberate about not getting left behind. Hereā€™s how Iā€™m staying in the game (and hopefully ahead of it):

šŸ’” 1. Mindset reset
This isnā€™t a side project. Itā€™s business critical: I block time weekly to experiment with MCP and push myself to apply AI across every part of my role from board prep to sales coaching.
šŸ§  2. Make it visible: We hold weekly stand-ups where the team shares how theyā€™re using AI from product builds to day-to-day work hacks. We learn faster when we learn together.
 šŸš€ 3. Build in public: Every time I test a prompt, get an output that saves me time, or I hit a wall, I share it with the team. Transparency creates momentum. It also makes it okay to fail fast. šŸ“ˆ 4. Start with the job to be done

Thereā€™s too much AI for AIā€™s sake. I focus on jobs I already do, building decks, researching prospects, coaching reps and ask: how could AI do 80% of this?

If you lead a team, the pace you move is the pace they move. Donā€™t watch from the side lines. Get your hands dirty.

INDUSTRY INSIGHTS šŸŒ

Meta is currently evaluating proactive AI chatbots designed to enhance user retention through more engaging interactions. By allowing bots to initiate contact with users who have already shown interest through multiple messages, Meta aims to create a more dynamic user experience. However, strict guidelines are in place: bots can only reach out after the user has sent at least five messages within two weeks, with the ability to send one follow-up message. This approach seeks to position chatbots as personalized and reliable partners, steering clear of controversial topics unless introduced by users.

The initiative is part of Meta's broader "Omni" project, which seeks to monetize generative AI. Expected to generate revenue between $2 to $3 billion by 2025, the proactive features are among several under internal testing, as Meta explores ways to boost its platform's value through extended user interactions. The long-term goal is to foster meaningful engagements, potentially addressing issues of loneliness, although the specifics of public availability remain uncertain.

Artificial intelligence is most useful for speeding up routine tasks and analyzing large data sets. It's excellent at organizing emails, drafting basic content, and providing personalized suggestions based on user behavior. In healthcare, AI aids early disease detection, leveraging its capacity to quickly scan and interpret medical data. However, AI lacks emotional depth and creativity, making it unsuitable for decisions involving ethics, emotions, or complex, context-sensitive situations. In areas such as justice, hiring, and high-stakes environments like surgery or aviation, human insight and oversight are paramount. It's crucial to use AI wisely, balancing automated efficiency with human judgment to prevent bias and misjudgment while enhancing productivity.

Analytics Insight

Leading in a startup isnā€™t easyā€”tight budgets, high pressure, constant change. But some mistakes can seriously derail your momentum. Here are key ones to watch out for:

  1. Hiring the wrong people (or hiring too fast)

  2. Micromanaging and bottlenecking growth

  3. Keeping underperformers around too long

  4. Misunderstanding the burn rate

  5. Lacking clear goals and alignment

  6. Ignoring feedback from team or customers

  7. Chasing shiny objects instead of staying focused

  8. Avoiding difficult conversations

  9. Getting overconfident in high win rates

āš–ļø Balance focus, agility, and accountabilityā€”and youā€™ll set your team up to scale.

AI-enhanced outbound call centers are revolutionizing lead generation by using predictive tools to target the most promising prospects, improving the efficiency of agents and increasing the likelihood of successful connections. These tools assist in determining optimal calling times and provide real-time support, allowing agents to confidently manage calls with seamless access to customer data and insights. This structured approach not only improves the quality of interactions but also streamlines follow-ups and scheduling, reducing the risk of missed opportunities.

By tracking call performance and enabling adjustments, AI helps refine strategies, fostering a learning environment that strengthens sales teams over time. The efficiency gained translates to cost savings, allowing businesses to expand their outreach without inflating budgets. As a result, companies can transition from relying on chance to adopting a strategic, data-driven approach, ultimately achieving faster growth and solidifying customer relationships. Embracing AI technologies early positions companies to experience enhanced performance and substantial competitive advantage in lead generation.