Descriptive
What happened. KPIs, trends, performance.
- Revenue, conversion rate, response time
- Ticket volume, overdue invoices, pipeline
- Clean dashboard and weekly summary
Analytics • Decisions • Next Best Action
AI analytics that tells you what to do next
Not another dashboard. Turn your CRM + WhatsApp + invoicing + operations data into clear next steps your team should take today, ranked, explained, and trackable.
Built for lean SA teams: start with 1 to 2 data sources and a few high-impact decisions, then expand.
From dashboards to decisions
Most reporting shows what happened. Prescriptive analytics closes the gap by turning insights into decisions. Recommendations, tasks, routing, and measurable follow-through.
Predictive
What’s likely to happen. Risk and probability.
- Lead priority and propensity scores
- Churn risk and collections risk
- Demand and volume ranges
Prescriptive and Next Best Action
What to do next. Ranked, explained, trackable.
- "Do this next" action lists per team
- Playbooks from signal to recommendation to action
- Optional automation with approvals
Stop reading reports. Start getting next steps.
Your team should not need a meeting to decide what to do first. We deliver ranked actions with reasons, then track whether actions were executed and what happened after.
Examples of next best actions
Practical recommendations that show up in your daily operating dashboard.
Sales follow-up
Speed-to-lead and pipeline velocity.
- "Lead opened quote twice. Follow up in 30 minutes with 2 options."
- "High score and no reply in 24h. WhatsApp reminder and book-a-call link."
- "Deal stalled 14 days. Escalate to manager review."
Collections and cashflow
Reduce overdue value and improve follow-through.
- "Customer overdue twice in 90 days. Use structured payment plan flow."
- "Overdue and high risk. Add to priority chase list today."
- "Promise-to-pay missed. Trigger escalation playbook."
Support and retention
Protect customers before churn happens.
- "Ticket breach risk. Auto-route to skilled agent."
- "Top customer at churn risk. Proactive check-in and recovery task."
- "Repeat ticket. Escalation workflow plus retention outreach."
What we connect
We start with what you already have and build a joined-up signal layer across systems.
Typical inputs
Messy real-world data is normal. We map it into decision-ready events.
- CRM and pipeline stages
- WhatsApp outcomes and opt-in status
- Email and web forms
- Invoicing and accounting exports
- Support tickets and call outcomes when available
What "good" looks like
We track system health, adoption, and business impact.
- System health: match rate, refresh latency, completeness, error rates
- Adoption: acceptance rate, time-to-action, actions executed
- Impact: conversion, churn, collections days, SLA performance
How it works
We treat decisions like systems: define them, instrument them, improve them with feedback loops.
1
Decision workshop
Pick 3 decisions that move revenue or efficiency.
- Lead follow-up priority
- Overdue invoice chasing
- Ticket escalation rules
2
Connect 1 to 2 sources
Start small to get speed-to-value.
- CRM export or system
- Invoicing sheet or export
- WhatsApp outcomes if needed
3
Map events
Create decision-ready signals.
- Lead created to replied
- Quote sent to stalled
- Invoice overdue to paid
4
Actions and playbooks
Turn signals into clear next steps.
- Top priorities today
- Thresholds and recommended steps
- Weekly insight summary
5
Automate safely
Approvals and audit trails for sensitive actions.
- Human-in-the-loop checkpoints
- Consent-first suppression logs
- Monitoring for drift
Packages
Modular packages so you can launch fast and add predictive scoring and automation over time.
Starter
Visibility, alerts, and a weekly summary.
- KPI dashboard and baseline metrics
- Alert rules for stalls, spikes, and overdue
- Weekly insight summary with recommended actions
- Connect 1 to 2 sources
Growth
Predict and prioritise with daily action lists.
- Everything in Starter
- Predictive scoring for one priority use case
- Prioritised today list for teams
- Adoption tracking for actions taken
Scale
Playbooks plus automation with guardrails.
- Everything in Growth
- Cross-team playbooks for sales, finance, support
- Automation for safe actions like tasks and routing
- Approval queues, audit trail, and monitoring
Not sure where you fit?
Bring one dataset and we’ll recommend the fastest path to a live dashboard, alerts, and next actions loop.
Responsible automation
We design for compliance and safety: lawful processing, minimality, data quality, security safeguards, and human review for higher-impact decisions.
How we handle your data
Practical controls that keep things safe.
- Minimality: only collect what’s needed for outcomes
- Security safeguards and role-based access
- Audit trails for recommendations and actions
- Decision transparency where required
Guardrails
Automate what’s safe, approve what’s sensitive.
- Human approvals for higher-impact actions
- Consent and opt-out governance for marketing
- Monitoring for performance and drift
- Continuous measurement and refinement
Two-week quick win timeline
A practical plan for lean teams: go live with a working dashboard, alerts, and next actions process, then iterate.
Week 1
Foundation and visibility
- Decision workshop and data audit
- Connect 1 to 2 sources and map events
- Launch dashboard and alert rules
Week 2
Actions and adoption
- First playbooks and next actions lists
- Train team, pilot, and go live
- Weekly summary and reporting loop
Disclaimer: accuracy and impact depend on data quality, consistent usage, and market realities. We baseline first, then measure and refine continuously.
FAQ
Short, practical answers.
Is this just BI dashboards with a new label?
BI often stops at reporting. This is designed to close the insight to action gap by producing next steps
with reasons, then tracking whether the team executed them and what happened after.
Do we need a data warehouse first?
Not always. Many SMEs start by connecting 1 to 2 sources and building a small number of decision-ready signals.
You can expand the data foundation later as the loop proves value.
Can it trigger actions automatically?
Yes for safe actions like tasks, routing, and reminders. For higher-impact decisions, we use approvals plus audit trails.
How do you prove ROI without fake stats?
We baseline your current metrics, then measure system health (data quality), adoption (actions taken),
and outcomes (conversion, collections days, SLA performance). You get before and after comparisons specific to your business.
