WWV26_-_WO_-_Zaal_3_-_Lannoo_x_Us_NV.pdf

Transcript

1. From fragmentation fragmentation to synergy Digital transformation at Lannoo Publishing Group in a a consolidating brand landscape 1
2. Lannoo Publishing Group One of the largest publishing houses in Belgium & The Netherlands with 4 publishing houses and over 20+ brands. Representing hunderds of authors and publishing books in every genre. 2
3. Background case Fragmented ecosystem ecosystem Multiple tools and systems used used across the group Inefficient reporting Lack of consistency and visibility visibility across brands High operational costs Overlapping tools leading to unnecessary spend Low usability Too many platforms and websites to manage effectively effectively Clear need for unification One streamlined system across the entire group 3
4. Core challenge How do we unify tools, data, and processes — without losing brand autonomy? 4
5. One platform. One customer view. Multiple brands. Solution 5
6. A unified CDP and Customer Experience Platform that connects connects everything behind the scenes scenes — without compromising brand brand identity, access control, or independence Solution 6
7. Multibrand setup Solution One platform SALESmanago as a single source of truth Structured data separation separation Clear naming conventions to organise databases databases Controlled access Permissions based on role, company, or brand brand Brand-specific style kits Consistent identity per publishing house 7
8. Multibrand setup Solution One platform SALESmanago as a single source of truth Structured data separation separation Clear naming conventions to organise databases databases Controlled access Permissions based on role, company, or brand brand Brand-specific style kits Consistent identity per publishing house 8
9. Data privacy & custom consents Solution Strict role-based access Users only see the brands they are responsible for Brand-level data isolation No visibility across publishing houses without permission permission Custom consents per brand brand Customers give and manage permissions separately for each for each brand Zero risk of cross-brand mistakes Impossible to send campaigns to the wrong audience audience Data privacy & access control 9
10. The cherry on the cake MCP P 10
11. What is MCP? Model Context Protocol IDEs and code editors Claude Desktop, Goose MCP Standardized protocol Development tools Git, Sentry, etc. Chat interface Claude Desktop, LibreChat Data and file systems PostgreSQL, SQLite, GDrive Other AI applications 5ire, Superinterface Productivity tools Slack, Google Maps, etc. AI applications Bidirectional data flow Bidirectional data flow Data sources and tools 11
12. Think of it as a USB-C port for your data. Model Context Protocol Before MCP, every AI tool needed a custom cable cable — — custom API, custom integration, months of months of dev work. MCP is the universal connector. connector. Any AI agent (Claude, ChatGPT, Cursor...) plugs straight into SALESmanago data. Instantly. 12
13. Model Context Protocol 13
14. What can MCP enable? Agents can access your Google Calendar and Outlook, acting as a more personalized AI assistant. MCP can generate an entire web web app using a Figma design. Enterprise chatbots can connect to multiple databases across an organization, empowering users to analyze data using chat. AI models can create 3D designs designs on on Blender and print them them out using a 3D printer. 14
15. Fast visualisation of 360° customer view Use cases 15
16. Fast visualisation of 360° customer view Use cases 16
17. Strategy grounded in your real data. Fast visualisation any data Use cases Instead of: “Create a high-value segment.” MCP-enabled AI can: Query your CRM Define high LTV customers Identify churn risk signals Create dynamic segments Generate messaging per segment 17
18. Define next best actions Use cases With MCP AI connects to analytics Summarizes weekly performance Highlights anomalies Explains why metrics changed Suggests next actions From reporting → to decision support. Marketeers spend hours building reports. 18
19. Connecting data 19
20. Use cases Define next best actions 20