The latest Boost Labs release includes eight updates: four new system integrations and four new automation blocks. Each one follows the Labs development pattern — built initially as a custom solution for a specific client engagement, refined across multiple deployments, and productized once the pattern proved reliable and broadly applicable.

This release focuses on two themes. The integrations close the data gaps between the financial, scheduling, reputation, and communication tools that mid-market companies use daily. The automation blocks add intelligence to the workflows that drive pipeline, retention, and operational efficiency.

Here's what's new, what it does, and how operators are using it.

New Integration: QuickBooks Online Two-Way Sync

The problem: Financial data lives in one world. Sales and operational data live in another. The CRM says a deal closed for $47,000. QuickBooks says the invoice was $43,500 because the scope changed during onboarding. The pipeline dashboard shows projected revenue based on CRM deal values. The P&L shows actual revenue based on QuickBooks. The CFO spends three hours every Monday reconciling the two before the leadership meeting.

This reconciliation problem appears in some form at virtually every mid-market company we work with. The CRM and the accounting system contain overlapping but inconsistent data, and the gap between them erodes trust in both.

What it does: The QuickBooks Online integration creates a bidirectional data flow between your CRM and your accounting system.

When a deal closes in the CRM, the integration generates a draft invoice in QuickBooks based on the deal data — client information, line items, amounts, and payment terms. The billing team reviews and sends the invoice from QuickBooks as they normally would, but the manual data re-entry step is eliminated.

When a payment is recorded in QuickBooks, the integration updates the CRM deal record with payment status, amount received, and outstanding balance. The sales team and leadership can see financial status directly in the CRM without logging into QuickBooks or waiting for a finance report.

When an invoice is adjusted in QuickBooks (scope changes, credits, partial payments), the CRM reflects the adjustment automatically. No more deal values that don't match invoice values. No more pipeline projections based on stale financial data.

The sync runs continuously — not on a batch schedule. Changes in either system propagate within minutes. And every sync event generates an audit record, so the finance team can trace exactly what changed, when, and from which system the change originated.

Practical use case: A $16M professional services firm was spending roughly 7 hours per week on CRM-to-QuickBooks reconciliation — their controller and an operations coordinator manually comparing deal records against invoices every Monday and chasing discrepancies. After deploying the two-way sync, reconciliation time dropped to approximately 45 minutes per week. The remaining time is spent reviewing the sync logs and handling the occasional edge case (non-standard deal structures, multi-phase invoicing) that requires human judgment. The controller estimated the time savings at $23,000 annually in loaded labor cost — from a single integration.

Configuration notes: The integration supports custom field mapping between CRM deal fields and QuickBooks line items. Multi-currency support is included for companies operating across markets. Tax calculation logic follows QuickBooks settings — the integration passes data, it doesn't override your accounting configuration.

New Integration: Google Business Profile Automation

The problem: Online reputation directly influences inbound lead quality and volume, particularly for local and regional service businesses. A company with 14 Google reviews and a 3.8-star average gets meaningfully less inbound interest than a competitor with 85 reviews and 4.7 stars, even if the first company does objectively better work.

Most mid-market companies know this. Few have a system for it. Review collection is typically ad hoc — someone remembers to ask a happy client for a review, or an email goes out sporadically. The result is a slow trickle of reviews that doesn't reflect the actual quality of the company's work.

What it does: The Google Business Profile automation connects your operational workflow to your reputation infrastructure. When a project is completed, a service is delivered, or a milestone is reached (the trigger is configurable based on your business model), the system initiates a structured review request sequence.

The sequence is designed around timing and psychology. The first request goes out within 24 hours of project completion or service delivery — the moment when the client's satisfaction is highest and the experience is freshest. If no review is submitted within five days, a gentle follow-up is sent. A third touchpoint at day twelve offers an alternative: if the client doesn't want to leave a public review, would they share private feedback instead? That private feedback is valuable for operational improvement even when it doesn't generate a public review.

The system also handles review responses. When a new review is posted, the appropriate team member receives a notification with a response template customized to the review's content and tone. Positive reviews get a personalized thank-you. Critical reviews get a response that acknowledges the concern and offers to resolve it — drafted by the system and reviewed by a human before posting.

Practical use case: A commercial cleaning company deployed the review automation eight months ago. At launch, they had 29 Google reviews with a 4.2-star average. Today they have 143 reviews with a 4.8-star average. Their operations manager reports that inbound inquiry volume has increased roughly 28% over the period — a figure she attributes partly to the review growth and partly to concurrent marketing improvements, but the correlation with review velocity is strong.

The more significant impact has been on lead quality. Prospects who arrive after reading dozens of positive reviews are further along in their decision process. They've already built trust with the brand before the first conversation. The sales team reports that prospects from organic search (where Google reviews are prominently displayed) convert at 31% versus 17% for prospects from paid campaigns where the review social proof is less visible.

Configuration notes: The trigger event is fully configurable — project completion, invoice paid, service milestone, or any CRM stage change. The sequence timing can be adjusted. Multi-location businesses can route review requests to the appropriate Google Business Profile based on service location. The system respects Google's terms of service: it requests reviews without incentivizing them or filtering for positive responses only.

New Integration: Enhanced Scheduling Integration

The problem: Lead qualification and appointment scheduling are separate systems in most mid-market operations. The AI lead response qualifies a prospect. Then the prospect is sent a generic scheduling link. They pick a time. It might be with the right team member, or it might not — because the scheduling tool doesn't know about the prospect's qualification data, service needs, or geographic location.

The result: misrouted appointments. A prospect interested in enterprise services books with a rep who handles small business accounts. A prospect in the Dallas market books with a team member based in Atlanta. A high-value opportunity gets a 15-minute discovery slot instead of the 30-minute deep-dive it warrants. Each misroute creates friction, delays, and a less-than-professional first impression.

What it does: The enhanced scheduling integration connects your AI lead response data directly to your scheduling infrastructure. When a prospect is qualified, the system routes them to the appropriate team member's calendar based on multiple factors simultaneously: service type (which team member handles this category), territory (which team member covers this geography), deal size (which seniority level should take the meeting), and availability (who actually has an open slot at a time that works for the prospect).

The scheduling link the prospect receives isn't generic. It shows availability specifically for the team member best matched to their needs, with appointment duration appropriate to their deal complexity. A qualified enterprise prospect sees 45-minute slots with the senior account executive. A small business inquiry sees 20-minute slots with the appropriate rep. The routing logic is invisible to the prospect — they just see a clean scheduling interface with the right options.

The integration also handles post-booking workflow. When an appointment is confirmed, the assigned team member receives a pre-meeting briefing pulled from the qualification data: prospect company, inquiry details, ICP match score, estimated deal value, and any relevant CRM history if the prospect is a returning contact. The team member walks into the meeting prepared without any manual research.

Practical use case: A $22M IT managed services company was experiencing a 23% misroute rate on scheduled discovery calls — nearly one in four meetings started with "actually, you'll want to talk to my colleague about that" and a warm transfer or reschedule. After deploying the enhanced scheduling integration, the misroute rate dropped to under 4%. More importantly, their appointment-to-proposal conversion rate improved from 47% to 63%. The team attributes the improvement to better matching — prospects speaking with the right person from the first conversation — and better preparation, since every meeting now starts with the rep already briefed on the prospect's situation.

Configuration notes: The integration works with Calendly, Cal.com, and native CRM scheduling tools. Routing rules are configurable through the CRM — no technical expertise required to adjust territory assignments, service categories, or team member matching logic. Round-robin distribution is available for situations where multiple team members are equally qualified.

New Integration: Slack/Teams Notification Hub

The problem: Critical business events — new deals entering pipeline, proposals accepted, high-value leads qualifying, automation alerts — generate notifications. Those notifications typically arrive via email, where they compete with hundreds of other messages and are frequently missed or delayed.

Mid-market teams increasingly live in Slack or Microsoft Teams for real-time communication. But the business systems that generate the notifications (CRM, automation platform, marketing tools) don't natively connect to those communication tools, or they connect through generic integrations that dump every notification into a single channel with no filtering or prioritization.

What it does: The Notification Hub routes business event notifications from your CRM, automation platform, and operational systems into your team's Slack or Teams environment with intelligent filtering and channel routing.

Deal alerts: when a deal moves to a new pipeline stage, exceeds a value threshold, or is flagged as at-risk, a formatted notification appears in the relevant channel. The notification includes the key details — deal value, stage, owner, and next action — without requiring anyone to log into the CRM.

Lead alerts: when a high-value lead qualifies through AI lead response, the assigned team member (and optionally, their manager) receives an immediate notification with the qualification summary. Response time to high-value leads drops from "whenever I check the CRM" to "within minutes of qualification."

Automation alerts: when a workflow encounters an error, when automation volume exceeds expected thresholds, or when a specific trigger fires (high-value proposal opened, at-risk client engages with a reactivation email), the appropriate team receives an alert. This keeps the team aware of what the automation is doing without requiring them to monitor dashboards continuously.

Pipeline digests: a configurable daily or weekly summary of pipeline changes — new opportunities added, deals advanced, deals lost, and velocity trends. Delivered to a leadership channel at a scheduled time, so the management team starts their day with a snapshot of where things stand.

Practical use case: A $9M financial advisory firm deployed the Notification Hub across three Slack channels: a #deals channel for pipeline activity, a #leads channel for new qualification alerts, and a #leadership channel for daily pipeline digests. The managing partner reports that the most impactful change was the lead alert in #leads — when a high-value prospect qualifies, the assigned advisor sees the notification immediately and can begin preparation within minutes rather than discovering the lead during their next CRM check (which, honestly, might be the next morning). The firm's average time-to-first-human-contact after AI qualification dropped from 3.4 hours to 22 minutes.

Configuration notes: The Hub supports both Slack and Microsoft Teams. Channel routing rules are fully configurable — you can route by deal value, lead source, team member, pipeline stage, or any combination. Notification frequency can be throttled to prevent alert fatigue (e.g., aggregate low-priority events into hourly digests while high-priority events push immediately). Formatting follows each platform's native message style for clean readability.

New Automation Block: Multi-Branch Lead Routing

The problem: Simple lead routing sends every lead to the same place: a shared inbox, a round-robin queue, or a single sales manager. As companies grow and specialize, routing needs to become more sophisticated — routing by service type, geography, deal size, and qualification score simultaneously. Building this multi-dimensional routing logic as a custom automation has been one of our most common implementation tasks.

What it does: The multi-branch lead routing block evaluates each incoming lead against multiple criteria simultaneously and routes to the optimal destination based on configurable rules. A lead can be evaluated on service category, geographic territory, estimated deal value, qualification score, and lead source — all in a single routing decision. The block handles conflicts (what happens when a lead matches multiple routes) through priority rules, and it logs the routing decision for analytics.

How operators are using it: An $18M commercial construction company uses multi-branch routing to handle three distinct service lines (tenant improvements, ground-up construction, and maintenance/repair), four geographic territories, and two deal-size tiers (under $200K routed to project managers, over $200K routed to senior estimators). Before the routing block, their office manager made these decisions manually for each inquiry — a process that took 5–8 minutes per lead and occasionally produced misroutes when she was busy. The block handles the same decision in under two seconds with zero misroutes.

New Automation Block: Conditional Follow-Up Sequences

The problem: Static follow-up sequences treat every prospect the same. The prospect who opened your proposal email three times in two hours gets the same day-seven follow-up as the prospect who never opened it. One needs a prompt to schedule a conversation. The other needs a different approach entirely.

What it does: Conditional follow-up sequences adjust timing, content, and channel based on prospect engagement signals. The block monitors opens, clicks, replies, website visits, and CRM activity, then branches the follow-up sequence accordingly.

A prospect who opens the proposal email multiple times within 48 hours receives an accelerated follow-up: a warm check-in at day two instead of day seven, with messaging that acknowledges their engagement ("I noticed you've had a chance to review the proposal — happy to walk through any questions"). A prospect who hasn't opened the email after five days receives a different message on a different channel — perhaps a brief text or a direct phone call prompt to the assigned rep.

How operators are using it: A professional services firm saw their proposal-to-close conversion rate increase from 26% to 34% within 60 days of deploying conditional follow-ups. The primary driver: hot prospects (those showing high engagement signals) received human follow-up 4–5 days earlier than they would have under the static sequence. In B2B sales, those 4–5 days often make the difference between closing while intent is high and losing to a competitor or internal inertia.

New Automation Block: Automated Proposal Generation

The problem: Proposal creation is the most time-consuming step in most B2B sales processes. It requires assembling data from multiple sources (CRM, pricing databases, previous proposals, case studies), applying judgment on scope and pricing, and formatting everything into a professional document. The assembly is labor-intensive. The judgment is valuable.

What it does: The automated proposal generation block handles the assembly so humans can focus on the judgment. When triggered (typically by a CRM stage change indicating a qualified opportunity), the block pulls client data from the CRM, project scope from the discovery notes (captured via the post-interaction CRM update workflow), pricing based on project type and historical margins, and relevant case studies from the company's portfolio. It assembles a formatted proposal draft and delivers it to the assigned team member for review.

The review step is mandatory by design. Proposals require human judgment — is this the right scope, the right price, the right framing for this specific client? The block eliminates the 2–4 hours of data assembly that precede that judgment. The reviewer spends their time on strategic decisions, not on formatting and data retrieval.

How operators are using it: The pattern that originated at Harmon Structural Engineering (where proposal turnaround dropped from 3–5 days to same-day) has been refined across 40+ professional services deployments. The average time savings per proposal across our client base is 3.1 hours. For a company generating 15 proposals per month, that's 46.5 hours recovered monthly — more than a full work week redirected from document assembly to client relationship and strategic selling.

New Automation Block: Churn Prediction Alerting

The problem: By the time a client tells you they're leaving, the decision was made weeks or months ago. The retention engines we build (as detailed in our piece on LTV engineering) include churn prediction as a core component. This automation block makes the prediction mechanism available as a standalone capability.

What it does: The churn prediction block monitors five signals across your client base: engagement frequency (declining communication or usage), satisfaction indicators (NPS trends, support ticket tone), payment behavior (late payments, disputes, requests for contract flexibility), champion status (departure of your primary contact), and usage patterns (declining utilization of contracted services).

When the composite risk score for any account crosses a configurable threshold, the block generates an alert to the account owner with a recommended intervention playbook. The alert includes the specific risk factors driving the score, the account's financial value, and suggested actions based on the risk profile — ranging from a proactive check-in call for moderate risk to a senior leadership engagement for high-value accounts at critical risk.

How operators are using it: A $14M B2B services company deployed churn prediction across their 87 active accounts. In the first quarter, the system flagged 11 accounts as at-risk. The account team intervened on all 11 — with proactive outreach, value demonstrations, and in two cases, scope adjustments that better aligned the engagement with the client's evolving needs. Nine of the 11 accounts renewed. The two that didn't were in industries undergoing structural contraction that no intervention could have addressed. The estimated revenue preserved: $412,000 in annual contract value that would have churned silently without the early warning.

What's Next

The Q3 roadmap (covered in our product roadmap post) includes the enhanced AI lead response engine, the Operations Dashboard, the Client Portal, and industry-specific automation block sets for healthcare, construction, professional services, and home services. The integrations and blocks in this release are the foundation layer — the connecting tissue that makes those larger products work.

Every integration and automation block in this release runs on the standard $1/action pricing. No licensing fees, no per-feature charges, no minimum commitments. The blocks are available to all Boost clients immediately and can be activated through your client strategy team or during your next sprint review.

For operators outside the Boost ecosystem, these capabilities are available through a systems assessment conversation. We'll evaluate your current stack, identify where the integrations and blocks address your specific pain points, and deploy what makes sense — without committing to anything broader unless the fit warrants it.

The tools keep getting better because the problems keep teaching us. Two hundred deployments and counting.

About Boost

Boost is the growth infrastructure company for ambitious mid-market businesses. We integrate AI-powered sales, marketing, automation, and strategic consulting into one compounding ecosystem. Founded by operators. Powered by AI.

For more information, visit useboost.net.