Multichannel Customer Support Systems

At Rackspace, we reduced IT ticket volume by 70% without adding headcount. By integrating an AI coworker directly into Microsoft Teams, it now automates 500+ tickets end-to-end each month. AI works best when employees don’t have to change how they work. So our team built an AI coworker for IT (RITA) that doesn’t need a new portal or separate interface. By running inside Microsoft Teams, an app Rackers use every day, RITA fits naturally into existing workflows. Employees don’t need to switch tools or change how they work, which drives widespread adoption. Beyond answering questions, RITA executes workflows in real time and handles device provisioning, account lockouts, and everyday software issues. It completes the work, not just the request, which lets IT teams spend less time on triage and more time on higher-value work. As a result, we see a widening gap in the market. Teams that treat AI as a tool stay stuck in pilots, while teams that design AI as a participant in operations scale faster. After running RITA inside Rackspace and refining it in production, we deploy it for other IT teams that want to scale without adding headcount. Happy to start a conversation via LinkedIn DMs if this is something you’re actively working on. And if helpful, we’ve written up how this approach played out alongside three other agentic AI solutions we deployed at Rackspace Technology. The link is here: https://bit.ly/4q177Ii.

Email templates can help customer service reps improve efficiency. But what happens when just choosing the right one becomes overwhelming? It's a case where AI can unlock human super-skills. One company implemented an AI tool from Laivly to help agents select the right template. Laivly's "Smart Response" feature analyzes incoming emails to suggest the right template for agents to use. Agents can review the suggested template for accuracy, and add personalization before sending the final email. The Smart Response tool improved productivity by 49%. Even better, customer satisfaction increased 10% and first contact resolution rose by 17%. It's a great example of using AI to handle tedious, repetitive tasks so agents can be freed to concentrate on work where they can add more human value. I'm increasingly seeing stories like this. Rather than humans or AI, it's humans and AI.

Ever feel like your team is drowning in tickets, with response times so slow you start to dread opening your inbox? That was us. Our old IT Service Management tool just wasn't cutting it. It was a black box, really. No real insight into what was actually *happening* business-wise, or how incidents were connected. So, lots of manual digging, endless escalations, and honestly, a lot of frustrated users. We knew something had to change. We’d spend hours trying to piece together trends or link current problems to past ones, and it felt like we were always playing catch-up. So, we gathered everyone. Business folks, internal teams, you name it. We really dug into what was missing and what was actually needed on the ground. Then, we worked with engineering to build it out. Lots of back and forth, tweaking workflows based on early feedback. It wasn't exactly a smooth ride, but we kept pushing. The goal was a single pane of glass. A place where you could see the whole story of an issue, its history, how it related to other things, and automated assignments and escalations. And you know what? It actually worked. We launched a unified system for our global users. The results surprised even us. Ticket response times dropped by 60%. Our customer satisfaction scores jumped 50%. And escalations? Down by a whopping 90%. It’s amazing what happens when you actually have the data and visibility to make informed decisions, instead of just reacting. Anyone else ever been in a similar boat with their tools? What’s your biggest challenge with current systems? I’d love to hear your experiences. #ITSM #DigitalTransformation #CustomerExperience #ServiceManagement #ProblemSolving

Channel Management : In FMCG In the FMCG (Fast-Moving Consumer Goods) sector, channel management are especially crucial to ensuring that products reach consumers efficiently & distribution channels are optimized for speed, reach & profitability. I. Channel Leveling in FMCG 1. Segment Channels Based on Market Reach Primary Channels: Typically involve wholesalers, distributors, and large retailers who help cover broad market needs. These are often responsible for volume sales. Secondary Channels: This includes smaller retailers stores & direct-to-consumer online channels. Secondary channels help penetrate regional and local markets, catering to specific customer segments. 2. Define Roles & Responsibilities for Each Channel Distributor Responsibilities: Distributors often cover specific geographic areas and are responsible for handling stock, logistics & replenishment. Retailer Responsibilities: Retailers provide end-customer access, display & promote products, especially in high-traffic areas. 3. Minimize Channel Conflicts Price Consistency: Avoid price disparities across channels, which can lead to customer dissatisfaction and partner conflicts. Set standard pricing guidelines to maintain consistency. Geographic & Market Exclusivity: Consider giving distributors exclusivity in certain regions or channels to reduce intra-channel competition, which can improve focus & accountability. 4. Align Channel Incentives Volume Discounts for Wholesalers/Distributors: Provide volume-based discounts or rebates for bulk orders, which encourage large purchases and improve economies of scale. Retail Display and Marketing Support: Offer incentives or co-marketing funds to retailers who meet display & stocking guidelines, as well as promotional goals. II. Performance Management in FMCG Channels Major Elements 1. Set Key Performance Indicators (KPIs) Sales Volume: Measures the total product units sold through each channel. Distribution Reach and Market Penetration: Measures how widely products are available across regions, especially important for FMCG. Stock Turnover Rate: Tracks how quickly inventory moves through each channel to minimize holding costs & avoid stockouts. 2. Channel-Specific Performance Reviews Monthly or Quarterly Reviews: Review each channel’s performance regularly to evaluate sales volume, distribution reach & other KPIs. Scorecards for Key Partners: Develop scorecards with metrics for each channel partner, and share performance results to encourage transparency & improvement. 3. Incentives Based on Performance Performance-Based Rebates: Offer rebates or bonuses for hitting sales targets, increasing reach, or improving stock turnover. This is particularly effective with high-volume FMCG distributors. 4. Continuous Feedback Mechanism Partner Feedback: Collect regular feedback from distributors, retailers, and direct channels to understand challenges they face, and use this data to improve channel support and performance.

How to #Reduce IT Tickets by 40% Without #Hiring More People After 25 years in IT leadership, I’ve realized something simple — most IT teams don’t need more people; they need fewer repeat problems. Every CIO talks about #automation, #AI, or #outsourcing #efficiency, but the real magic starts with simplifying service and building #accountability — across both customer and vendor ecosystems. ⚙️ The Real Problem Isn’t Ticket Volume — It’s Ticket Design In every service review, you’ll hear: “We closed 8,000 #tickets this month.” “Average #resolution time down 10%.” But ask users if IT feels better — and the silence says it all. Because closing tickets faster isn’t success. #Preventing them is. We’re solving #symptoms, not #causes. 🚀 Step 1: #Eliminate #Repetition at the Source- Nearly 40% of tickets come from #avoidable, recurring issues — password resets, access delays, failed changes, misconfigurations. #Automate what #repeats twice:- Use self-service within #ITSM tools (ServiceNow, Jira, Fresh service, etc.). Strengthen #problem #management ownership — not just incident closure. The goal isn’t faster closure, it’s fewer #reopening. 🧠 Step 2: Move from #SLA to #XLA Thinking- Dashboards showing 99% SLA compliance don’t prove success if users still struggle. An SLA is #transactional; an XLA (Experience Level Agreement) is #transformational. Track:- How often the same issue recurs. How users feel about the service. How incidents affect business flow. And remember — more SLAs with 100% targets don’t mean excellence. They often serve the vendor, not the enterprise. Simplify. Focus on outcomes, not paperwork. ⚖️Step 3: Fix the #Ownership Loop- Most enterprises lose time between vendors, #L2/L3 teams, and user departments — everyone waiting for the other to act. The solution isn’t hiring more people. It’s clear #accountability. Define ownership and #escalation beyond the tool. #Governance isn’t about finding who’s at #fault — it’s about ensuring the issue never returns. 🔧 Step 4: #Measure What Matters- To truly reduce tickets by 40%: Track repeat incident rate. Measure #root cause #elimination. #Reward teams for prevention, not closure. Every ITSM tool already has #analytics. Use them to build preventive #intelligence, not just #dashboards. 💬 My Take- Reducing IT tickets isn’t a staffing problem — it’s a #strategy problem. When IT starts measuring experience instead of effort, the results follow. That’s what defines #intelligent IT — not just efficient #operations. #CIO #Leadership #ITServiceManagement #DigitalTransformation #TechnologyLeadership #EnterpriseIT #ITGovernance #ITOperations #CIOCommunity #LeadershipHiring #HiringForCIO #Headhunters #ServiceExcellence #ITStrategy #ITSM #SLAs #ProblemManagement #ExperienceManagement #Automation #ITSupport #ITLeadership

The generalist CSM model is becoming outdated. As customer needs grow more complex and outcome-driven, leading organizations are restructuring their Customer Success teams with specialized roles, smarter coverage models, and scalable engagement strategies to meet the moment. We’ve already seen the shift toward scaling Customer Success—now, we’re witnessing a new evolution: delivering high-touch, personalized experiences at scale. This transformation is accelerating the move away from the generalist CSM model. Here’s what we're seeing: 🔹 Strategic Value-based CSMs → Focus: Executive alignment, business outcomes, long-term value realization → Look for: Consultative thinkers, commercial acumen, relationship builders with enterprise experience 🔹 Adoption/Product Consultants → Focus: Driving usage, behavior change, and time-to-value → Look for: Enablement, change management, persona-based engagement 🔹 Technical Advisors → Focus: Deep technical guidance, product integration, onboarding success → Look for: Product depth, cross-functional collaboration, IT & DevOps fluency 🔹 Renewal Analysts → Focus: Churn prediction, risk mitigation, contract forecasting → Look for: Data-savvy, RevOps fluent, outcome-oriented The Shift in Models: From 1:1 to Scalable Coverage Organizations are also moving from traditional 1:1 account ownership to specialized and shared coverage models to drive efficiency and outcomes across the full customer base: 🔸 Dedicated (1:1): Best for top Strategic/Enterprise accounts needing white-glove services/custom planning 🔸 Pooled/Pod Models: Shared CSM resources based on triggers (e.g., lifecycle stage, risk signals), supported by playbooks and automation 🔸 Digital-Led: Tech-touch engagements at scale, powered by AI, in-product guidance, success centers, and lifecycle campaigns 🔸 Hybrid Models: Blend high-touch and digital support based on customer segmentation, value potential, or complexity Why Make the Shift? Because expecting one person to be a product expert, change manager, data analyst, and executive whisperer is unrealistic. Why condition your customers to expect high-touch support across every product—often delivered inconsistently—when you can instead scale the right expertise, at the right moment, through the right channels? Specialized roles and right-fit coverage models enable teams to scale effectively, align to customer needs, reduce burnout, and ultimately drive retention and growth. How is your team evolving to meet modern customer expectations? Which role or model has made the biggest impact? #CustomerSuccess #CSMStrategy #OrgDesign #DigitalCS #Scale #Leadership #PostSalesTransformation #CustomerExperience

We Boosted an 8-Figure Beauty Brand's Email Revenue by 68.5%. Here’s a complete breakdown of how we did it: 1. Background • Client: An 8-figure beauty brand • Industry: Beauty and Personal Care • Challenge: The brand needed a comprehensive overhaul of their automated flows and customer journey. Their marketing efforts were not fully optimized, and they lacked a cohesive strategy that included email, SMS, and push notifications. 2. What We Did • Funnel Analysis and Optimization: Strategy: Analyzed the customer journey and identified major drop-off points. Implementation: Developed unique abandonment flows to address potential customer objections at each step. • Plugging Messaging Gaps: Strategy: Addressed major gaps in the existing flows. Implementation: Implemented new abandoned flows based on custom on-site behavior metrics. • Campaign Strategy: Strategy: Focused on staying top of mind for customers. Implementation: Implemented a campaign strategy aimed at maintaining a consistent cadence of strong content to maintain brand presence, crucial in this client’s industry sector. 3. Results • Overall Revenue Increase: Email Revenue: 68.5% increase from the previous year. • Revenue Breakdown: Campaigns Revenue: A 32% increase. Flows Revenue: 197% increase. • Channel-Specific Increases: Email Revenue: Increased by 63%. SMS Revenue: Increased by 115%. Push Revenue: Increased by 244%. 4. How We Did It • Analyzed the Customer Journey: We conducted a thorough analysis of the customer journey to identify major drop-off points and opportunities for engagement. • Plugged Major Messaging Gaps: Addressed gaps in the existing messaging flows and implemented new abandonment flows based on custom on-site behavior metrics. • Implemented a Comprehensive Campaign Strategy: Our strategy focused on keeping the brand top of mind for customers, which is particularly important in the beauty industry. This included a mix of email, SMS, and push notifications to ensure consistent engagement. By implementing these strategic changes, our client saw a significant increase in revenue across all channels. The improved approach made their marketing efforts more effective, driving higher engagement and conversions. If you’re looking to optimize your email campaigns and drive more conversions, reach out to us at Dispatch. We’re here to help you achieve your marketing goals with tailored, high-impact email strategies.

The FMCG Playbook: Winning Strategies for Evolving Channels The FMCG landscape is transforming rapidly, with channels like Quick Commerce (QComm) emerging alongside traditional General Trade (GT), Modern Trade (MT), and E-Commerce. While the shift has also been in terms of consumption patterns of customers, here are a few companies that have started innovating to meet evolving customer demand : 1. Leverage Technology for Precision AI and ML are transforming operations in FMCG. Example: Colgate-Palmolive India uses machine learning to optimize inventory forecasting, ensuring product availability even in remote regions. Strategy: Invest in AI-driven analytics to enhance forecasting, reduce wastage, and improve supply chain efficiency. 2. Develop Channel-Specific Portfolios Different channels demand tailored strategies: Example: Marico Limited introduced travel-friendly, single-use sachets of Parachute coconut oil for QComm, meeting the needs of urban, on-the-go consumers. Strategy: For QComm, focus on fast-moving SKUs. For MT and E-Commerce, emphasize premium assortments and combo packs. 3. Optimize Dark Store Shelf Space Securing space in dark stores is crucial for QComm success. Example: Britannia Industries Limited negotiates for prominent placement in platforms like Zepto and Blinkit, driving visibility for its snack products. Strategy: Collaborate with QComm players to ensure shelf prominence and create exclusive promotions to drive traction. 4. Audience-Centric Segmentation Consumer preferences vary by demographic and geography. Example: Nestlé India targets Gen Z with instant meal solutions via QComm while focusing on older demographics through GT and MT. Strategy: Use granular data to design campaigns and assortments for segmented audiences. 5. Embrace Data-Driven Marketing Real-time data is indispensable for today’s marketers. Example: ITC Limited integrates its D2C platforms with QComm insights to refine campaigns dynamically. Strategy: Invest in data tools to analyze and act on trends in real-time, ensuring campaigns remain relevant and engaging. 6. Strengthen Supply Chain Agility Quick delivery demands flawless execution. Example: Dabur India Limited revamped its distribution network to meet QComm’s instant delivery requirements while maintaining MT and GT efficiency. Strategy: Build flexible, agile supply chains to support diverse channel needs. 7. Innovate for Retention In QComm, loyalty is fleeting. Example: PepsiCo frequently launches limited-edition SKUs on Swiggy Instamart to capture consumer attention. Strategy: Regularly refresh product offerings and campaigns to maintain excitement. The future of FMCG is not just about reaching shelves but owning the consumer journey across all channels. Thats what a winning strategy would entail in times to come.

Busywork in engineering is dying. Control isn’t. A few months ago, structuring requirements meant days of manual effort. Thousands of lines. Endless clustering. Clicking through tools just to keep traceability intact. Everyone accepted it as “part of the job” Until now. In a recent experiment, unstructured requirements for a simple system - a windshield wiper - were turned into a fully structured requirement and ticket structure within minutes. No manual modeling. No clicking through tools. No chasing traceability. Here’s what happened behind the scenes: 1. Raw requirements were written in Cursor IDE 2. Passed to Claude Opus 4.6 for structuring 3. Converted into a ReqIF-based hierarchical model 4. Imported into Codebeamer, a PTC Technology 5. Call of Atlassian MCP server to trigger ticket creation 6. Automatically transformed into 140 structured tickets in Jira (initiatives, epics, user stories) including test cases, relationships and full traceability What used to take days now happens in minutes. No-touch engineering is no longer a concept. It’s working. Here’s the core shift: AI is not replacing engineering. It’s replacing everything around engineering. The real value was never in formatting requirements or creating tickets. It was always in thinking, deciding and designing. The takeaway: - Stop optimizing manual workflows - Start automating the operational layer completely - Focus engineering time on decisions, not documentation - Treat structure as something AI generates, not engineers maintain The engineers who win won’t be the fastest clickers. They’ll be the ones who design systems where clicking is obsolete. So here’s the real question: What part of your engineering workflow are you still doing manually even though it shouldn’t exist anymore? Vlad Larichev | Dr. Pascalis Trentsios | Sebastian Linzmair | Timmo Sturm | Nitin Ugale

I've been thinking about what DTC brands get wrong about omnichannel expansion recently. The temptation is to try to be everywhere at once. But the real winners are strategically aligning each channel to build a holistic growth engine. Here’s how to do it right → First, you must have channel-specific thinking. Every channel needs its own playbook. A helpful framework to structure your efforts... DTC Website: • Focus on basket building • Higher AOV targets • Full-price strategy • Data collection hub • Customer relationship building TikTok Shop: • Single-product purchase reality • Organic content engine • Lower AOV expectations • Limited data access • Treat as a retail channel Amazon: • Multi-pack strategy • Bundle economics • Marketplace presence • Competitive monitoring • Specialized management Next up, the Integration Challenge → The biggest mistake brands make is trying to force the same strategy across all channels. Example: One brand we spoke with increased shipping costs on TikTok Shop to push customers to their website. Instead of fighting the platform's natural behavior, they should have optimized for it. You must also consider your unit economics because each channel has its own cost profile. - TikTok Shop might be a loss leader but drive retail success. - Website sales might have better margins but higher customer acquisition costs. - Amazon might have lower margins but better operational efficiency. Here is the new omnichannel playbook: 1. Channel Optimization - Build channel-specific content - Adjust pricing strategies per platform - Create platform-specific bundles - Set realistic KPIs for each channel 2. Data Strategy - Accept data limitations on newer platforms - Focus on first-party data where possible - Build cross-channel customer profiles - Use creative solutions for retention 3. Team Structure - Specialized expertise per channel - Clear ownership of metrics - Flexibility to shift resources - Mix of in-house and agency support The brands that will win aren't the ones just running around trying to be everywhere - they're the ones being intentional about how they show up in each place. Success also isn't about ideal profit extraction across all channels. It's about understanding each channel's role in your broader ecosystem and optimizing accordingly. Key Takeaway: Don't try to make every channel work the same way. Start building channel-specific strategies that work together to drive overall growth.