Lyriko Suggestions
Lyriko Suggestions leverage AI to provide actionable insights to sales reps to enhance HCP engagement.
By analyzing CRM data and past interactions, it generates Next Best Actions and content suggestions.
Key Features
Actionable Recomendations
Cross-Channel Optimization
Real-Time Insights
Feedback-Driven Refinements
Omnichannel Customer Engagement
How does it work?
- Data Collection and Analysis: Lyriko aggregates data from CRM systems, web and social analytics and KOL insights to provide a comprehensive view of HCP interactions.
- Rules Setting: Marketing Teams can establish engagement rules and define key messages.
- AI-Driven Recommendations: Lyriko suggests the most effective actions and content for HCP engagement, tailored to business objectives and accessible directly in the CRM or via another tool.
- Personalized Insights: Lyriko equips reps with actionable insights into HCP preferences and behaviors.
- Feedback Integration: Lyriko incorporates rep feedback to enhance the accuracy and relevance of its recommendations.
KPIs
Coverage
with HCPs
Rates
Enhanced Content Adoption and Key-Message Adherence
See Lyriko Suggestions in action!
FAQs
What is Lyriko Suggestions and what does it do?
Lyriko Suggestions is the Lyriko AI module that generates operational recommendations for pharmaceutical sales representatives to improve HCP (Healthcare Professional) engagement. By analyzing CRM data, past interactions, and marketing objectives, it automatically produces Next Best Actions and personalized content suggestions, accessible directly in the CRM or other tools reps already use. The result is a more effective sales force with more targeted interactions and an omnichannel communication strategy aligned with corporate goals.
What concrete results have companies achieved with Lyriko Suggestions?
In the MSD Italy programme, adopting Lyriko Suggestions produced measurable strategic impact: over +40% in call plan adherence, +22% in email open rates to HCPs, and +50% in average click-through rate on suggested content. The same programme also reported a 98% rep satisfaction rate, around 80% engagement on the suggestions delivered, and a +19% average HCP coverage rate. The solution proved so effective that MSD decided to roll it out across 13 additional markets, including Turkey, Saudi Arabia, and the Asia Pacific region, with each new market typically going live in 1–2 months.
What are the "Next Best Actions" generated by Lyriko Suggestions?
Next Best Actions (or Next Best Engagement, NBE) are ready-to-use recommendations for each sales rep: they indicate what action to take, with which HCP, through which channel, and at what moment. Each recommendation results from the combined analysis of CRM data, past behaviors, call plan objectives, and priority key messages defined by marketing. The system may suggest, for example, scheduling a visit, sending an email with a specific piece of content, or initiating a digital interaction on the HCP’s preferred channel.
What data sources does Lyriko Suggestions use?
The Suggestion Engine is based on a system of configurable Rules scoped per project and environment. Each rule contains the logic to produce one or more suggestions, with parameters (thresholds, weights) settable at tenant level. When a Run, an execution instance of the engine, is triggered, all active rules are evaluated against available data and produce Outputs (suggestions). Results are localized through multilingual text templates and delivered directly in the rep’s CRM or other configured touchpoints.
How does the Lyriko Suggestions recommendation engine work?
Lyriko applies visual tagging to images and videos using proprietary AI models. For images it classifies content and people attributes such as age, gender, and emotion, and recognizes objects, including custom-trained items like specific medical devices or packaging. For video it extracts key frames and transcribes audio via speech-to-text, then tags the result.
How does Lyriko Suggestions improve call plan adherence?
Lyriko Suggestions directly addresses poor call plan adherence by suggesting the most effective action for each HCP at the right moment, based on plan objectives and interaction history. The system eliminates decisional ambiguity (“who do I visit today? with what content?”) by delivering prioritized recommendations aligned with corporate objectives. MSD Italy recorded an increase of over 40% in call plan adherence after adopting the solution.
How does Lyriko Suggestions ensure control over content shared with HCPs?
Yes. Lyriko Suggestions is natively designed for omnichannel engagement: recommendations cover all major touchpoints, in-person visits, email, digital channels, and suggest the most effective channel for each interaction with a specific HCP. The system ensures consistent targeted messaging across all channels, taking into account historical HCP preferences and call plan objectives.
Does Lyriko Suggestions support omnichannel HCP engagement?
Yes. Lyriko integrates natively with Veeva Vault PromoMats and synchronizes tags directly into it, no manual bridge required. It is also designed to integrate seamlessly with any DAM or regulated content management system, making tagged content available across the entire ecosystem.
How are rules and marketing objectives configured in Lyriko Suggestions?
Configuration happens through the Lyriko Suggestions interface. Marketing teams can create, duplicate, edit, activate/deactivate rules, and promote them to the production environment. Each rule is associated with configurable parameters and templates per project. Marketing Goals define strategic priorities (e.g. key messages to push for a product line) around which rules are built. An Advanced Rule Editor is available for deep configurations with direct access to parameters and templates.
Does Lyriko Suggestions integrate with Veeva CRM and other CRM systems?
Yes. Integration with major pharmaceutical CRMs, such as Veeva CRM, is handled by the Data Connectors of the Lyriko Connectors microservice, in both push and pull modes. Recommendations appear directly in the rep’s Veeva CRM interface, with the suggested action, HCP profile, and priority level, requiring no change of application. The system is designed to be accessible within the sales force’s existing working tool.
Is Lyriko Suggestions multi-tenant? How is data isolation between clients guaranteed?
Yes, Lyriko is a multi-tenant platform. Every entity in the data model, Projects, Rules, Parameters, Templates, Data Connections, Runs, and Outputs, is scoped to a specific Tenant. There are no operations that cross tenant boundaries: one client’s data is never accessible to another. This ensures full compliance with security and data governance requirements even in multi-client environments.
How many languages does Lyriko Suggestions support?
Lyriko Suggestions supports multilingualism for both generated content (suggestions and templates) and the interface. Text templates forming the body of suggestions can be configured in multiple languages per project and per rule. Reps receive recommendations in their own operational language, facilitating platform adoption in international contexts, as in the MSD case, active across 14 markets.
How is the quality of recommendations measured and improved over time?
A traditional CRM records and organizes interaction data, but does not autonomously suggest to the rep what to do and when. Lyriko Suggestions goes further: it analyzes existing CRM data through AI, applies rules based on marketing objectives and call plan, and turns data into actionable recommendations with clear priorities. The rep no longer needs to interpret data alone, they receive a direct indication of which HCP to contact, with what content, and through which channel, maximizing the efficiency of every interaction.
Is Lyriko Suggestions accessible only via web UI or also through APIs?
Accurate tags make every asset findable and comparable, so marketing and sales can recommend the right content for each HCP and channel. Lyriko enables Next Best Content suggestions, personalized newsletters, and content-sharing monitoring, reportedly improving customer engagement by around 22% and marketing-plan adherence by around 20%.
What is the difference between Lyriko Suggestions and a traditional CRM system?
Yes. Lyriko is built for regulated pharma content, with GxP and AI governance baked into the workflow and audit-ready oversight. It handles complex, nuanced taxonomies and works multi-format and multi-language across markets. Companies like Novo Nordisk and Organon use it at enterprise scale, Organon has tagged over 30,000 materials across 60+ markets at 98% accuracy.
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