B2B SaaS does not sell deals — it sells subscriptions. Tonic Desk models deal value as MRR or ARR, scores leads against your ICP, tracks every touch from ad click to closed-won, and routes product-qualified leads to AEs while flagging accounts at churn risk.
A generic CRM tracks deal value as a single figure. A SaaS deal is $2,400 ARR / $200 MRR, with a 14-month average contract length, gross margin of 78%, and a renewal in month 12. None of that maps to a "deal value" field. Your forecast looks like sales and acts like cash — which is wrong.
Your ICP is fintech series B, 50-200 employees, North America, head of growth as the buyer. A lead from a 5-person bootstrap agency comes in. The SDR books a discovery call anyway because no one defined the bar. Twelve calls later you realise quota was missed because pipeline was full of out-of-ICP noise.
Marketing reports "this deal came from a webinar." Sales reports "this deal came from a cold outbound." Both are right. The lead saw a LinkedIn ad in March, signed up for a webinar in April, took a sales call in June, and signed in August. The CRM only stores the last touch. Budget allocation decisions become guesswork.
A customer stopped using the product in week 8. Their primary user changed jobs in month 4. They opened zero of the last six product update emails. The CSM finds out about the churn on renewal day, when the customer says "we already migrated to Vendor B."
Every deal carries MRR, ARR, Contract length (months), Billing frequency, and Discount % as first-class fields. The deal page shows expected lifetime value at a glance. Reports forecast new ARR by month, expansion ARR by account, and churned MRR by reason. The board deck builds itself from the live CRM data.
Define ICP attributes — industry, employee count, region, tech stack, role of buyer — and weight each. New contacts auto-score 0-100 against the rubric on the basis of enrichment data. Routing rules send scores above 70 to AEs, 40-70 to SDR follow-up, below 40 to a nurture sequence. Sales reps stop wasting cycles on the wrong shape of company.
Every touchpoint — ad click, content download, webinar registration, sales call, demo, trial sign-up — logs against the contact with timestamp, source, and campaign. Reports run first-touch, last-touch, linear, time-decay, and U-shaped attribution side-by-side on closed-won revenue. Marketing and sales argue from the same dataset, not separate dashboards.
Pipe product usage events (logins, key-action counts, feature adoption) into Tonic Desk via webhook. An automation flags an account as At risk when login frequency drops 50% week-over-week, when the primary user role-changes, or when usage stays below the activation threshold for 30 days. PQL workflows fire in the other direction — a trial team hits the second key action, the AE gets a task with usage context attached.