Your sales team talks to the right people. Not everyone.
Every morning a clear list: these leads are worth it today. Based on real behavior — not gut feeling, not who called last.
Today's Reality
Who gets called today is decided by gut feeling — or whoever last sent an email. Systematic prioritization doesn't exist.
Your sales team spends hours on leads that will never buy — and those who would are waiting too long for a response.
When is a lead ready for a conversation? Every salesperson has a different answer. Unified criteria are missing.
CRM entries, email interactions, trade show contacts, external signals — the data is there. It just sits in different systems and is never combined.
How It Works Instead.
Collect
CRM, email interactions, trade show contacts — and external signals: press releases, job postings, social media activity, public tenders. The system combines internal and external sources into a complete picture — including the signals that nobody has systematically evaluated before.
Score
Every lead gets a score — based on real behavior and profile characteristics, not assumption. Company size, industry, purchase timing, interaction history: everything flows in.
Prioritize
Your sales team sees every morning: these leads are worth it today. With context why — not just a number, but a rationale your team can understand and trust.
Learn
Every closed deal and every rejection makes the model more precise. Your sales experience flows back — the system learns what truly predicts a close with your customers, not what works for someone else.
Especially relevant if:
- Your sales team handles more leads than it can qualifiedly follow up — and prioritization runs on gut feeling, not data.
- You sell B2B with longer sales cycles and products that need explanation — where the right moment for a conversation is decisive.
- Your sales data is scattered across CRM, email, and Excel — and is never systematically combined.
Under the Hood
Infrastructure
On-premise or EU cloud — in both cases under your control. Customer data, sales history, pricing conditions: no US provider, no Cloud Act risk, GDPR-compliant by design.
Integration
Connection to CRM and email systems — plus external sources: press releases, job postings, social media, public tenders. The system works with internal and external data simultaneously.
Models
Trained on your historical sales data — not on generic scoring benchmarks. The system learns what predicts a close with your customers, in your industry, with your product.
How It Works
Design Sprint
2 WeeksWe analyze your sales data, identify which signals predict closes with your customers — internally and externally. You get: technical solution architecture, business case with ROI numbers, identified risks, and a clear go/no-go recommendation. Fixed price. If the project doesn't pay off, we say so here — before you invest big.
Implementation & Go-Live
4–10 WeeksScoring model built, integrated into your CRM, external sources connected. Your sales team tests with real leads — not demo data. When the system goes live, we train the team directly on real cases. Clear scope, clear price.
Operations
OngoingEvery new closed deal and every rejection makes the model more precise. New signal sources can be added at any time. Either as a managed service by us — or we hand over to your IT with full documentation. No vendor lock-in.
“Omniance has made our internal administration significantly faster and simpler — with excellent return on investment.”
INOS GmbH & Co. KG
Industrial On-Site Solutions
Built by a team with 16 AI patents and 14 years of applied AI development — at Philips Research, Heidelberg University Hospital, and CERN. Our standard: systems must work 10 out of 10 times. Not 9.
Meet the teamHow much time does your sales team spend today on leads that will never buy?
No pitch. We look at your sales data together — and honestly tell you whether systematic lead scoring makes sense for you. If not, we'll say so.