Customer Experience Collaboration Tools

650. That’s the staggering number of companies offering conversational AI solutions for sales and service. The flood isn’t slowing: each week brings new entrants or announcements. A year ago, the market was already crowded; today, the latest wave of AI technologies has further lowered barriers to entry, fueling an unsustainable proliferation. Beyond the three hyperscalers, only a handful of providers have surpassed $100M in ARR. I spent the summer making sense of the mayhem. The result: nine categories mapped to the core jobs-to-be-done. Customer service and support solutions fall into four categories: • Virtual Agents. IVAs and their AI evolution operate across digital channels, handling transactional interactions and escalating to humans when necessary. • AI Answer Engines. These retrieve and format answers from knowledge bases. Generative AI has dramatically improved precision for informational inquiries. • Conversational IVR and Voice Agents. Voice remains complex; these agents primarily handle transactional interactions. • Conversational Engagement and Outreach Agents. These manage outbound communications across voice, SMS, and messaging channels, complying with regulations. Historically transactional, they increasingly enable dynamic engagement. Sales solutions are grouped into three categories: • Conversational Commerce & Concierge Agents. Mature agents replacing traditional chat with conversational experiences across pre- and post-sales. "Concierge" reflects their versatility in guiding customers seamlessly. • Autonomous SDRs (Sales Development Reps). Focused on complex B2B scenarios, they enrich and qualify leads, route them to sellers, and schedule appointments. Among the most mature AI applications for B2B sales. • Autonomous BDRs (Business Development Reps). These drive outbound sales motions where relevance is critical. Complex to implement and scale, they work best in highly targeted scenarios where personalization is flawless. Some providers span the full spectrum of service use cases and Conversational Commerce & Concierge Agents. Rather than duplicating them across categories, I group them under Conversational AI Platforms, relying on robust capabilities to design, deploy, and continuously improve applications and agents. Customer Support Automation is an emerging platform category, tailored for handling support requests and a natural fit for GenAI. These platforms deliver full resolutions when possible, automate workflows, and assist agents with context and guidance. It’s a mature use case for Agentic AI, with many providers publicly demonstrating transformative results. The visual landscape below captures this segmentation. A few vendors will emerge as true platforms, while others will focus on niches or become embedded in broader applications. The market remains in motion, and I welcome perspectives on what I may have overlooked. #conversationalai #agenticai #cx #salestech

Back when I was a data analyst, I used to “collaborate” by sharing screenshots, exporting Excel files, and sending copies of local ipynb files with teammates. My workflows consisted of hundreds of ad hoc queries in SQL Server scripts or Jupyter Notebook files that were organized by code comments that only made sense to me… And even worse, they were saved as v1, v2, vFinal, etc. in various locations across a disorganized file system that we only cleaned up for archiving purposes only after the project was over 😵💫 I left that job thinking it was normal for a data team to be this unorganized and that data collaboration was overrated—we just need to code and build dashboards better and faster! As I transitioned to companies where data played a much more central role in the company rather than one that was merely an auxiliary function, I learned that collaboration is not just a single thing that data teams have or do not have. There are LEVELS to this: 1️⃣ Synchronous collaboration - At remote-first companies, I needed to be able to work through problems in the same file at the same time alongside my manager when I was stuck ↳ Data tools with real-time code collaboration features that also allow for granular role-based access controls allowed me to prototype rapidly with my virtual teammates 2️⃣ Asynchronous collaboration - I have almost always worked with people across different timezones ↳ Features like commenting and versioning allowed me to pick up work on a project where a colleague left off, and vice versa 3️⃣ Organizational collaboration - All the hard work I did on an analysis was worth nothing if I couldn’t surface the insights to other data teams and business stakeholders and demonstrate the business value ↳ Team workspaces helped us build out dedicated hubs for teams to collaborate efficiently and organize data reports used to share insights interactively A data platform that boasts all of these features and is built with the collaborative data team in mind is JetBrains Datalore. If your data team knows the pain of any of these collaboration struggles, check out Datalore at 👉 https://lnkd.in/gcZSNBeU #ad

Marketing Automation & Customer Service is no longer just about sending emails or filling out contact forms. With AI these flows can become journeys: interactive and truly personalized - unlocking new levels of engagement and conversion in Whatsapp or Chat. But where to start? Here’s a breakdown of the top journeys most e-commerce brands have implemented and how I rank their AI potential and impact: 1️⃣ Product Recommendations | AI Potential: High Helping your customer to make a choice and find the product that fits their needs. > Move beyond static scripts! AI can find best fitting products with LLM powered semantic search, resolve blockers, compare products and provide tailored suggestions. 2️⃣ Welcome Flow | High You offer an incentive, collect and opt-in and further into > With AI, this flow can become interactive: No form like answering all extrated from a normal informal conversation. Enrich their profiles for future personalization (email, birthday, ...) 3️⃣ Customer Service | High Taking care when your customers have a problem: > AI Agents will provide 24/7 multilingual support. Collect the info you need before handing over to a human if the certain problems still need the human insight, access, or touch. Save costs while enhancing customer experience. 4️⃣ FAQ Automation | Medium Make it easy for customers to find answers. > AI ensures responses are nuanced and personalized. 5️⃣ Abandoned Cart | Medium Customer is (almost) ready to buy, but got interrupted or needs a little nudge > Send a(i) personalized message based on the exact product they have in their cart. Highlight how it fits their preferences or past purchases. 6️⃣ Cross-Sell / Up-Sell | Medium Encourage customers to buy complementary products. > AI can craft compelling arguments for upgrades, bundles or next product to buy. 7️⃣ Birthday or Special Day Campaigns | Medium Send wishes and a little gift > Let AI create a personalized message, image, or video and send it via WhatsApp. 8️⃣ Winback / Replenishment | Low Remind customers to repurchase or return. > Personalization helps, but the core is timing. 9️⃣ Review Collection | Low Gather feedback and build trust with REVIEWS.io or alike > AI can personalize requests and handle negative feedback gracefully avoiding bad reviews. 🔟 Back-In-Stock | Low Notify customers when the product they wanted to buy is available again. > AI can add a personalized touch to the reminder [don't want to get out of stock? Talk to VOIDS] 1️⃣1️⃣Referral Programs | Low Encourage word-of-mouth with incentives for sharing. > AI can personalize referral messages for higher trust and conversion. 1️⃣2️⃣Fulfilment Updates | Low Keep customers informed about their orders. > Let AI add a personal touch related to the product shipped. [Want to turn into an upsell opportunity: Karla is doing a great job here] The future of e-commerce is about conversations, not campaigns. Which flow or journey are you excited to tackle first? #conversationalai

Notion is great for internal organization and collaboration, but what if you want to turn that content into a public-facing experience? Using Replit’s new Notion integration, I built a customer support page template that does exactly that. It connects your Notion databases to: → Display FAQs → Power a custom AI chatbot trained on your support docs → Log support tickets back into Notion for follow-up This setup blends Notion’s backend strengths with Replit’s flexibility to create a clean, interactive front end tailored to your users. What I really love about this setup: 1. Custom front end with Replit Replit gives you the freedom to build unique, interactive experiences: chatbots, forms, and more. 2. Real-time read from Notion No need to manage a separate backend. Just maintain one Notion database as your single source of truth. Changes update instantly across your apps. 3. Write-back to Notion You’re not just pulling data, you’re writing back to it. That means: → Tagging teammates → Collaborating in Notion → Resolving issues in one shared workspace 4. Powerful automations With Notion’s automations and webhooks, you can: → Trigger alerts and notifications → Kick off workflows → Set up autoresponders → Build async flows that scale Replit + Notion = an awesome combo. Template and instructions below 👇

At Yolt, we built teams around the customer journey Not just the org chart. That meant marketing and product weren’t just aligned, they were accountable together. Each stage of the funnel had its own cross-functional squad. Growth. Activation. Engagement. Retention. On paper, it looked ambitious. In practice, it worked better than any siloed setup I’ve ever seen. Even with marketing in London and product in Amsterdam, the collaboration felt more like a close friendship than a working relationship. Zooms full of sticky notes. Shared dashboards. Late-night Slack “what if we tried…” messages. It wasn’t always easy. But we had one rule that made it work: “Yes, and…” That mindset changed everything. 💥 It sparked more creative solutions 🔍 It made feedback feel less personal and more productive 🚀 And it gave us the confidence to try things no one else in our space was doing To be competitive in a crowded market, you need to be trying new things rather than repeating the ‘safe’ what’s worked before. If you find your sitting in meetings and the team aren’t bouncing off each other, try replacing them with “yes, and…” Have you tried this? Or what else can work for creative collaboration? #growth #productmarketing #startuplife #leadership #collaboration #customerjourney #yesand

Over the years, I've discovered the truth: Game-changing products won't succeed unless they have a unified vision across sales, marketing, and product teams. When these key functions pull in different directions, it's a death knell for go-to-market execution. Without alignment on positioning and buyer messaging, we fail to communicate value and create disjointed experiences. So, how do I foster collaboration across these functions? 1) Set shared goals and incentivize unity towards that North Star metric, be it revenue, activations, or retention. 2) Encourage team members to work closely together, building empathy rather than skepticism of other groups' intentions and contributions. 3) Regularly conduct cross-functional roadmapping sessions to cascade priorities across departments and highlight dependencies. 4) Create an environment where teams can constructively debate assumptions and strategies without politics or blame. 5) Provide clarity for sales on target personas and value propositions to equip them for deal conversations. 6) Involve all functions early in establishing positioning and messaging frameworks. Co-create when possible. By rallying together around customers’ needs, we block and tackle as one team towards product-market fit. The magic truly happens when teams unite towards a shared mission to delight users!

A customer once told me: 'We're not just buying your product —we're betting on your ability to help us succeed and grow over time.'" That comment challenged me to think differently, and it still does each today. It came up during one of my regular customer check-ins. The kind where we’re not solving fires — but stepping back and asking, “What's working well? What's not? What’s next for you?” And the answer surprised me (but shouldn't have!) They of course had some concerns about today’s pain points. But more importantly, with how fast the world is changing and the level of embedded uncertainty, they were even more thinking 6–12 months ahead: ➡ How will our strategy evolve? ➡ What help do we need today that sets us up for more wins in the future? ➡ What will we need from you then that we’re not even asking for now? It was a wake-up call and a great reminder of that quote from years ago. Our current onboarding (and broader post-sales motion) focused too much on narrow current needs — not on future ones. And in today’s pace of change, that’s not enough. So we shifted: ✅ Start every engagement (for more customer segments) by co-creating a future-state vision ✅ Build our roadmap around where they’re going, not just where they are ✅ Check in on that vision — regularly The impact? Stronger partnerships. Stickier outcomes. More trust. How are you helping your customers grow into the future, not just succeed in the present?

Inclusive Marketing Case Study: Kraft Mac & Cheese-Gate What Happened? Abby, a Kraft Heinz customer with coeliac disease, reported missing sauce packets in their gluten-free Mac & Cheese across multiple purchases. After contacting customer service, Abby received only coupons, which did not address the root issue. Frustrated, she shared her experience in a TikTok video, garnering nearly 2 million views. Kraft’s response—a public comment claiming, “We are not having a quality issue”—was perceived as dismissive and gaslighting. This sparked outrage in the comments, with over 7,000 responses defending Abby. Meanwhile, competitors Walmart and Stouffer’s capitalised on the situation by sending Abby gluten-free comfort foods, earning praise for their attentiveness. Lessons for Brands 1. Social Listening and Proactive Engagement: Effective social listening allows brands to address customer concerns early and spot opportunities for engagement. Timely, empathetic responses can diffuse tension and foster goodwill. 2. Centralised Governance: A shared incident reporting system that integrates feedback from customer service, social media, and sales teams can help identify trends and potential crises. High-profile complaints or viral posts should trigger immediate escalation protocols. 3. Empathy in Communication: Brands must avoid defensive or dismissive language. Kraft’s comment alienated customers, while Walmart and Stouffer’s empathetic actions highlighted the importance of meaningful resolutions. Acknowledging issues publicly and committing to investigate instils trust. 4. Competitor Agility: Walmart and Stouffer’s leveraged the incident to demonstrate their customer focus. Their quick, empathetic engagement attracted public praise, showcasing the importance of being prepared to act on competitor missteps. Recommendations 1. Integrated Feedback Channels 2. Pre-Approved Responses 3. Cross-Team Collaboration 4. Monitor competitor-related discussions Conclusion The Kraft Mac & Cheese incident underscores the power of social media to hold brands accountable. By implementing a governance framework and prioritising inclusive, empathetic communication, brands can protect their reputation, resolve customer concerns effectively, and turn challenges into opportunities for growth. Competitors’ agility further highlights the value of responsiveness in today’s digital-first world.

In so many organisations, so many people have so many ideas, skills and knowledge sets that could be of incredible value but their voices so often go unheard, because they work in a team or department that isn’t leading on the challenge, or their job description is only accessing 10% of their experience, expertise and interest. It is why it is so important to get people to work across teams and to broker and to catalyse that. The U.S. military have liaison officers who facilitate communication between elements of the organisation to ensure mutual understanding and unity of purpose and action. Liaison is the most commonly employed technique for establishing and maintaining close, continuous, physical communication between commands. It ensures that leaders and teams have a real time awareness of talent and expertise, wherever it may be, so that it can be deployed quickly and with immediate impact. Maybe, create a centralised information centre, where people can see what is going on where in the organisation, and can contribute through online portals to offer support and ideas. Increasingly, organisations are holding hackathons, during working hours for people to meet in open spaces, shares ideas and challenges, in order to form working groups and focused teams. I often advise clients to build work exchanges into their professional development cycles, so that people get the chance to experience other roles and responsibilities within the organisation, not only to build empathy but to foster new relationships and opportunities for information and idea exchanges. Start to see roles as missions rather than fixed job descriptions, so that colleagues can move when appropriate but always have a home base to return to.   Make sure that leaders at all levels are not only held to account for planning, strategy, vision, culture and performance but for cross-team collaboration. It is too easy for leaders to role model the silo-ing and cross departmental blame shifting that can so easily poison an organisation’s collegiate potential.  

Just got this from our Meta rep - they're launching Signals Gateway, basically their version of a Customer Data Platform (CDP). Haven’t tried it at Obvi, but here’s what Meta is saying about it… It's a data hub that lets you: - Collect data from multiple sources - Build custom audiences - Share data across channels (not just Meta) The big difference? It runs on YOUR servers, not Meta's. Most interesting: They built a new first-party pixel that's supposedly less vulnerable to browser blocks & iOS restrictions. Meta's internal testing claims a 23% CPA improvement when used with CAPI + regular pixel. If true, this means: - Better event tracking - More control over your data - Improved signal coverage for upper funnel - Works with multiple channels (not Meta-locked) One thing to note - you need a dev team familiar with AWS/Google Cloud. So it’s not plug-and-play like most Meta products, but that might actually good. More control = better data ownership. Bottom line: If you're spending serious ad dollars and looking for better CPA (who isn’t), this is worth looking into. Will share more if/when we test it at Obvi. Has anyone implemented this yet? Would love to hear about your experience so far…