How to Optimize Sales Processes With Software Integrations

The sales stack that runs our $4.4M+ agency: CONTEXT We run outbound campaigns for > 70 B2B organisations. We need to be flexible because our clients are: - in different niches - targeting various personas - at different stages (enterprise, scaleups, SMBs) Some platforms overlap, since we adapt to clients' existing software stack. TOOLS 1/ Data "The list is the strategy" The first step in a successful outbound campaign is to build an Ideal Customer Profile (ICP) list. We can do this in several ways: - exporting data from b2b databases - scraping websites to find custom data - leveraging ai agents to research data at scale - uncovering buying intent by using monitoring signals Depending on the use case, we'll leverage: - AI Agents: Relevance AI, Claygent - Enrichment Platforms: Prospeo.io, FullEnrich, Icypeas, LeadMagic - Intent Data: Common Room, Trigify.io, LoneScale, Unify, Vector 👻 - Data Scrapers: Instant Data Scraper, PhantomBuster, ZenRows, Serper - Data Sources: Openmart (local data) DiscoLike (ai lookalikes) TheirStack (technology data) LinkedIn, Apollo, Ocean (b2b databases) To validate this data, we use 1 out of Instantly.ai, BounceBan, LeadMagic or NeverBounce. 2/ Outreach "The right message, in front of the right person, at the right time" The right message is easier to write when you have the right person. That said, you can get some extra help with platforms like Octave for ICP research, Twain for copywriting or Grammarly for spelling. To send these "right" messages, we use Instantly.ai (best at email outreach) & lemlist (best at multichannel outreach) Depending on projects, other platforms we'll use include: - Woodpecker.co, Unify, Smartlead (for email sending). - HeyReach.io (for LinkedIn outreach) - Salesfinity (for cold calling) 3/ Workflow Orchestration To bridge the gap between outreach & data, we use workflow builders that let us add conditions around how data should interact with sales engagement platforms. In practice, that means that platforms like Relevance AI, Default, Clay or n8n allow you to automate: - receiving enriched contact data - creating conditions for whether someone shall be contacted - routing leads to the appropriate campaign - reaching out The best way to think about 'workflow orchestration' is to imagine what you'd do manually if you had all the time in the world. Then, replicate these manual steps using workflow builders. 4/ Deal Closing We use OutboundSync to synchronise leads generated through outbound efforts with our clients' CRM. Plus, we use: - Attio as our CRM. - Breakcold for social selling. - Attention for meeting recording. - Qwilr to send proposals after our prospects' meetings. That's it. Once again... we use way more tools than necessary because we switch from one to another depending on our clients. If you're running outbound for your company... Pick 1 platform max per category. And you'll do just fine. That said... anything you'd add to this stack?

Look - we need to have a real conversation about #SFA/#CRM implementations. For years we've focused on building these massive systems of record, expecting sellers to just... figure it out? Meanwhile, many #sales leaders keep wondering why #adoption is #garbage and #ROI is #nowhere to be found. Here's what Gartner's latest research reveals: we've been doing this completely backwards. Instead of obsessing over features and capabilities, what if we started with the actual workflow of selling? Not the idealized version - the real, messy, human process of moving deals forward. And then focusing the efforts on high effort components of the workflow! This "Seller Action Hub" concept: - Start with the natural flow of sales work (actually involve your sellers to map it out and document it) - Map the high-effort actions that actually matter - Then (and only then) layer in automation and AI to support low-level actions. The idea is that you want to build a next best action engine not just for the sake of it but to espouse best practices of your sales playbooks and top performers! The breakthrough isn't the tech. It's the mindset shift. Stop treating your SFA like a fancy database and start treating it like an orchestration engine for seller behavior. The real magic happens when you bridge that gap between what experienced sellers do intuitively and what your systems can automate and augment. It's not about replacing human judgment - it's about scaling it. #SalesTransformation #CRM #SalesOps #SellerFirst #gartnersales #gartner

"𝗜'𝗺 𝗮 $𝟭𝟯𝟱𝗞 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝘀𝘁 𝘀𝗽𝗲𝗻𝗱𝗶𝗻𝗴 𝟳𝟬% 𝗼𝗳 𝗺𝘆 𝘁𝗶𝗺𝗲 𝗮𝘀 𝗮 𝗱𝗮𝘁𝗮 𝗷𝗮𝗻𝗶𝘁𝗼𝗿 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹𝗺 𝗼𝗳 𝗔𝗜" That's how Marcus, RevOps Leader at a 55-person SaaS company, described his reality. His setup: 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 + 𝗢𝘂𝘁𝗿𝗲𝗮𝗰𝗵 + 𝗚𝗼𝗻𝗴, supporting 7 AEs, 9 SDRs, and 3 CSMs. Marcus knew exactly what his VP of Sales needed:  𝘁𝗲𝗿𝗿𝗶𝘁𝗼𝗿𝘆 𝗼𝗽𝘁𝗶𝗺𝗶𝘀𝗮𝘁𝗶𝗼𝗻, 𝗹𝗲𝗮𝗱 𝘀𝗰𝗼𝗿𝗶𝗻𝗴 𝗿𝗲𝗳𝗶𝗻𝗲𝗺𝗲𝗻𝘁, 𝗮𝗻𝗱 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝘃𝗲𝗹𝗼𝗰𝗶𝘁𝘆 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀. But his actual week looked like this: • 𝟰𝟮 𝗵𝗼𝘂𝗿𝘀/𝗺𝗼𝗻𝘁𝗵: Building reports, fixing broken workflows, cleaning duplicate data • 𝟭𝟴 𝗵𝗼𝘂𝗿𝘀/𝗺𝗼𝗻𝘁𝗵: Troubleshooting integration failures and user access issues • 𝟭𝟮 𝗵𝗼𝘂𝗿𝘀/𝗺𝗼𝗻𝘁𝗵: Manual data validation and field updates • 𝟴 𝗵𝗼𝘂𝗿𝘀/𝗺𝗼𝗻𝘁𝗵: Actually doing strategic work During Q2 planning, Marcus spent 4 days building an in-depth analysis dashboard. While he was heads-down in formulas, their 𝗢𝘂𝘁𝗿𝗲𝗮𝗰𝗵-𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 sync broke, and 𝟯𝟰𝟬 𝗾𝘂𝗮𝗹𝗶𝗳𝗶𝗲𝗱 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝘀 went uncontacted for 𝟳𝟮 𝗵𝗼𝘂𝗿𝘀. His honest assessment:  "𝘐 𝘬𝘯𝘰𝘸 𝘩𝘰𝘸 𝘵𝘰 𝘰𝘱𝘵𝘪𝘮𝘪𝘴𝘦 𝘰𝘶𝘳 𝘴𝘢𝘭𝘦𝘴 𝘱𝘳𝘰𝘤𝘦𝘴𝘴, 𝘣𝘶𝘵 𝘐'𝘮 𝘵𝘰𝘰 𝘣𝘶𝘴𝘺 𝘬𝘦𝘦𝘱𝘪𝘯𝘨 𝘵𝘩𝘦 𝘭𝘪𝘨𝘩𝘵𝘴 𝘰𝘯 𝘵𝘰 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘥𝘰 𝘪𝘵." For a company at their scale, this administrative burden was costing an estimated $𝟳𝟱𝟬𝗞 annually in lost productivity and revenue leakage, roughly 𝟭𝟮% of their ARR. 𝟯𝟬 𝗗𝗮𝘆𝘀 𝗔𝗳𝘁𝗲𝗿 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝗖𝗹𝗶𝗲𝗻𝘁𝗲𝗹𝗹:  • Administrative time: 72 hours/month → 18 hours/month  • Strategic project time: 8 hours/month → 54 hours/month  • Report turnaround: 2-3 days → 5-minute chat requests  • Integration uptime: 78% → 99% 𝗪𝗵𝗮𝘁 𝗠𝗮𝗿𝗰𝘂𝘀 𝗕𝘂𝗶𝗹𝘁 𝗪𝗶𝘁𝗵 𝗛𝗶𝘀 𝗙𝗿𝗲𝗲𝗱 𝗧𝗶𝗺𝗲:  • Predictive lead scoring model (increased MQL-to-SQL conversion by 𝟮𝟯%)  • Territory rebalancing analysis (identified $𝟭𝟴𝟬𝗞 in untapped pipeline)  • Sales velocity dashboard (reduced average deal cycle by 8 days) His message last week:  "𝘐 𝘧𝘪𝘯𝘢𝘭𝘭𝘺 𝘧𝘦𝘦𝘭 𝘭𝘪𝘬𝘦 ��'𝘮 𝘦𝘢𝘳𝘯𝘪𝘯𝘨 𝘮𝘺 𝘴𝘢𝘭𝘢𝘳𝘺 𝘢𝘴 𝘢 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘪𝘴𝘵, 𝘯𝘰𝘵 𝘢 𝘮𝘢𝘪𝘯𝘵𝘦𝘯𝘢𝘯𝘤𝘦 𝘸𝘰𝘳𝘬𝘦𝘳. 𝘞𝘦'𝘳𝘦 𝘯𝘰𝘵 𝘫𝘶𝘴𝘵 𝘴𝘢𝘷𝘪𝘯𝘨 𝘵𝘪𝘮𝘦; 𝘸𝘦'𝘳𝘦 𝘢𝘤𝘵𝘪𝘷𝘦𝘭𝘺 𝘮𝘢𝘬𝘪𝘯𝘨 𝘮𝘰𝘳𝘦 𝘮𝘰𝘯𝘦𝘺." The Bottom Line: Same $135K RevOps budget. Now, 80% goes toward growth initiatives instead of maintaining systems. Sound familiar? If your RevOps team is drowning in administrative tasks instead of driving strategic growth, 𝗹𝗲𝘁'𝘀 𝘁𝗮𝗹𝗸. You might be leaving significant revenue on the table.

NetSuite and your CRM don’t need to fight, but they do need to speak the same language. Ops wants NetSuite. Sales lives in Salesforce or HubSpot. And no one wants to own the messy middle. What happens? Sales closes a deal → Finance gets incomplete or delayed info RevOps builds workarounds → Manual syncs, broken lead-to-cash process Reporting across systems? Basically useless Here’s the fix: Stop thinking of the integration as a “sync.” Start thinking of it as a business process handoff. You need to align: Data structures (SKUs, product bundles, customer records) Ownership and timing (when does Sales hand off? what triggers invoicing?) System logic (pricing rules, quote-to-order workflows, subscription terms) Whether you're using Celigo, Boomi, or custom APIs, the integration needs to be built around your actual sales process, not just what the tools can technically do. At TFR Solutions, we help clients get this right, because fixing NetSuite without fixing the CRM handoff is like patching a leaking pipe but ignoring the water main.

Yesterday I posted a case study on how we reduced a client's time to contract and invoice by 30% and saved them 5-7 hours per week. Here's exactly how: After posting this yesterday, I'm receiving a lot of messages asking how we did it. I thought I'd make a post about this. Here's exactly how we did it: First, we mapped out the process. Before working with us, the company relied on a fragmented and unreliable system. Their order-taking, contracting, and invoicing processes lacked automation, leading to delays, errors, and a poor experience for both their team and clients. Then we optimized it. We designed a fully integrated workflow that begins with a Typeform order form, which feeds directly into Monday and Airtable to manage requests, generate contracts, and track invoices with a Softr interface for easy access to order updates and relevant documents. Then we implemented. The new system helped the sales team save approximately 5-7 hours per week by streamlining client intake and ensuring name cohesion across tools. It also reduced the time it took to send invoices and contracts by about 30%. Finally, we optimized again after implementation. Key features include automated contract and invoice generation, real-time order tracking, and a client-facing portal built with Softr. All of which improved efficiency, accuracy, and the overall client experience. The result? A centralized, user-friendly experience that eliminated manual steps and improved operational efficiency. The takeaway: Don't just automate. Optimize first, then implement, then optimize again based on real usage. Follow me Luke Pierce for more automation case studies like this.

SAP S/4HANA MM-SD Integration (Materials Management - Sales & Distribution) is a crucial part of logistics and supply chain processes. Here’s an overview of how MM and SD modules work together, along with key integration points and process flows. ⸻ 🔄 Overview of MM-SD Integration • MM (Materials Management) handles procurement, inventory, and material valuation. • SD (Sales and Distribution) deals with order processing, shipping, billing, and customer delivery. • The integration ensures seamless data flow between purchasing and sales activities, especially for third-party, intercompany, and stock transfer scenarios. ⸻ 🔗 Key Integration Points Area Integration Description Sales Order Creation (SD) Triggers demand in MM for goods. In third-party or make-to-order scenarios, it can initiate purchase requisitions. Availability Check SD uses MM inventory data (stock, reservations, etc.) for ATP (Available to Promise). Delivery When goods are picked and packed (SD), inventory is reduced in MM. Billing After goods issue in SD, accounting and controlling documents affect MM for inventory valuation. Procurement for Sales Order (Third-Party Process) SD sales order creates a purchase requisition in MM. Once goods are received at the customer, billing is done directly without physical stock in inventory. Intercompany Sales A sales order in one company code can trigger a PO in MM for another. ⸻ 🧾 Common Business Scenarios 1. Third-Party Order Processing • SD Sales Order → Purchase Requisition (MM) • MM Purchase Order → Vendor delivers directly to the customer • SD creates billing document based on delivery confirmation 2. Make-to-Order Production • Sales order triggers production or procurement • Stock is maintained as sales order stock (special stock) 3. Intercompany Sales • Sales org in Company A sells; supplying plant is in Company B • MM creates a PO (Company A) → SD delivery from Company B • Intercompany invoice and final invoice handled via SD billing 4. Stock Transfer Order (STO) • MM creates STO (plant to plant) • SD handles delivery and shipment • MM handles goods receipt at the receiving plant ⸻ 🔧 Configuration Touchpoints 1. Assign Delivery Types to Sales Document Types 2. Item Category Determination 3. Schedule Line Category Determination 4. Account Determination (MM + SD) 5. Stock Determination Rules ⸻ 📈 Integration Benefits • End-to-end visibility of supply chain • Real-time inventory updates • Automated PO creation from sales orders • Reduced manual interventions ⸻ • #SAP • #SAPS4HANA • #SAPMM • #SAPSD • #SAPIntegration • #DigitalTransformation • #SupplyChainManagement • #ERPImplementation • #BusinessProcessManagement • #EnterpriseTechnology • #OrderToCash • #ProcureToPay • #LogisticsOptimization • #SAPConsulting • #TechLeadership

Something every revenue leader knows but few admit: Conversation Intelligence tools alone won't fix your broken sales process. They just amplify chaos. If your sales tech stack still feels scattered, it's because you’re missing true Revenue Action Orchestration (RAO). Gartner defines Revenue Action Orchestration (RAO) as a centralized AI-guided system that orchestrates sales actions across multiple channels for coordinated, efficient workflows. Momentum.io has been doing this for years and the big boys in CI talk about how they do this, but they usually fall short. Here's why: 1. Conversation Intelligence tools give insights, but don't orchestrate actions. Insights alone don’t close deals. They fill reports but still leave reps overwhelmed, manually connecting dots across too many tools. Gartner calls this chaos—not orchestration. 2. RAO isn’t just about insights—it’s about coordinated action. Momentum.io matches Gartner’s vision of RAO perfectly: a centralized AI-native platform orchestrating insights and actions seamlessly. It automates deal updates, detects churn risks, coaches reps in real-time, and aligns pipeline management—all from one place. 3. AI-ready, structured data drives real-time decisions. Conversation Intelligence tools rely on fragmented integrations and human actions post-call. RAO platforms like Momentum automate capturing structured, actionable data—reducing manual tasks and freeing reps to sell more effectively. 4. Systems of Engagement, Intelligence, and Internal Process connected seamlessly. Momentum integrates deeply with your existing tech (CRM, Slack, Zoom) to unify seller actions and intelligence, exactly as Gartner illustrates RAO. 5. RAO simplifies the tech stack, enhancing sales performance and collaboration. Gartner’s model replaces chaos with coordination—exactly what Momentum is built to do. It streamlines workflows, eliminates redundant tasks, and enables proactive sales decisions rather than reactive guesswork. — Don’t confuse insights with orchestration. Streamline your stack. Unlock your team's true potential with real Revenue Action Orchestration or just come talk to my team ;).

YOUR GOAL: improve seller efficiency with AI STEP 1: figure out what the heck sales reps do all day in between calls STEP 2: prioritize where AI tools and agents can help It's just: outbound and calls, right? Wrong. It's ALSO: prioritize pipeline work, process leads, monitor signals, research accounts, review past calls, prep call slides, add CRM notes, create/progress/close opps, update forecast fields, create tasks, enroll in sequences, handoff leads/accounts, assemble resources, send follow-ups, draft quotes, get approvals, sign NDAs, fill out security + procurement paperwork, log activity And that doesn't include what I missed and everything else needed to develop skills and be a teammate (call coaching, onboard new hires, pipeline/forecast meetings, trainings, team events...) Here's what to do: 1️⃣ identify opportunities + challenges in your sales motion. Customer response time slow? Stage 2 conversion not good enough? Time to quote should be faster? 2️⃣ figure out the related processes and activities that affect those metrics 3️⃣ build knowledge or action agents to help inform sales reps and/or do more work for them. Assess solutions that are practical, minimize change, and can be easily managed or improved. Sales is hard. With smarter orchestration, sales execution doesn't need to be.