We implement Zoho Analytics — connecting your Zoho CRM, Books, Desk, People, Projects, and Inventory into unified dashboards that detect anomalies automatically, eliminate manual reporting, and let leadership ask questions in plain English.
Manual reporting, conflicting numbers, issues discovered at the weekly review — these patterns appear in every business analytics audit we run.
Someone pulling data from CRM, Books, and Desk into a spreadsheet every Friday. Hours of work producing a report that's already out of date before it's shared. Zoho Analytics automates the assembly and delivers on schedule — finance reviews instead of builds.
CRM says revenue is £284k. Books says £272k. Different definitions, different timing, different filters. Zoho Analytics creates one canonical data model — one agreed definition for every metric applied consistently across all connected sources. One number everywhere.
Conversion rate dropped on Monday. Discovered at Friday's meeting. Four days of compounding impact. Zoho Analytics anomaly detection flags deviations from baseline within hours of occurrence — issues surface immediately, not at the scheduled review.
Every data question goes through IT or a BI analyst. Days to get an answer. Zia's natural language query lets non-technical managers ask questions in plain English — "show me our top 10 accounts by revenue last 6 months with declining order frequency" — and get an accurate answer in seconds.
Data pulled from multiple sources, formatted manually, narrative written from scratch each month. Zoho Analytics automates the data assembly — finance reviews and approves rather than building from zero. Two days becomes 30 minutes.
Dashboards showing what happened last week. No indication of what's likely to happen next week. Zoho Analytics connected to Zia AI shows forecast alongside actuals — so leadership is making decisions about the future, not just reviewing the past.
One data model. Anomaly detection. Automated reports. Natural language queries. All your Zoho products connected.
CRM, Books, Desk, People, Projects, Inventory — all connected with agreed metric definitions. Before building any dashboard, we define what every metric means consistently across all sources. Revenue means the same thing in the CRM pipeline view as it does in the Books financial report. No more conflicting numbers between departments.
Executive dashboard (P&L, pipeline, team capacity, support SLA — all in one view). Sales dashboard (pipeline by rep, conversion rates, deal velocity, at-risk deals). Finance dashboard (receivables, margins, cash position, tax position). Support dashboard (ticket volume, SLA compliance, CSAT). Each audience sees their data in the format that drives decisions.
Zoho Analytics monitors your key metrics continuously against statistical baselines. When something deviates — revenue, conversion, margin, support volume, any tracked metric — an alert fires to the right person within hours. Issues are discovered the day they start, not at the weekly review when four days of impact have already accumulated.
Non-technical managers ask questions in plain English — "show me our top 10 customers by revenue last 6 months where order frequency is declining" — and get an accurate answer in seconds from across your connected Zoho data. No SQL, no BI analyst, no waiting. Questions answered before the meeting, not in the week after it.
Weekly sales summary, monthly management accounts, board pack data — assembled from connected sources on schedule and delivered to the right people before they ask for them. The finance team's Monday morning report arrives at 7am, assembled automatically from live data. Review and approve — not build from scratch.
Zoho Analytics connects beyond Zoho products — Google Analytics, Shopify, SQL databases, Excel and CSV files, and custom REST APIs can all be pulled in alongside Zoho data. One analytics platform for all your business data, not just the data that lives in Zoho.
Every implementation starts with the data model. The dashboards follow from there.
A service company had sales, finance, and support operating from separate dashboards with no unified business view. Leadership was making decisions from partial pictures — pipeline visible in CRM, cash position in Books, support health in Desk, but never all three together. We connected all three Zoho products to Zoho Analytics, built a canonical data model, and created a single executive dashboard. The anomaly detection layer fires Slack alerts when any key metric deviates from its 90-day baseline — issues surface within hours, not at the Friday meeting.
A sales director had a Zoho CRM with 140 active deals but no way to distinguish which were genuinely progressing from which were stalled. Standard CRM reports showed activity counts — not deal health. We built a Zoho Analytics sales intelligence layer: deal scoring based on activity pattern and stage age, pipeline velocity tracking, conversion rate by source and by rep, and at-risk deal detection. The Zia Q&A layer meant the sales director could ask specific questions without raising a ticket with IT.
A finance director wanted real-time P&L visibility without waiting for the monthly close. The business was making pricing and investment decisions from financial data that was 30 days old by the time it was reviewed. We connected Zoho Books to Zoho Analytics for live revenue, cost, and margin data — and connected Zoho CRM pipeline data to add forward-looking revenue forecasting alongside the actuals. The Monday morning management report now arrives at 7am, assembled automatically from live data. Review time: 25 minutes.
A professional services firm needed to answer a question that no single Zoho product could answer: which team members are available for new projects next month, given current project allocations and approved leave? The answer required data from Zoho Projects (current project allocations), Zoho People (approved leave), and Zoho CRM (pipeline deals likely to close and become projects). We built a cross-product capacity dashboard in Zoho Analytics that pulled from all three simultaneously.
We define what every metric means before building any dashboard. Revenue, gross margin, deal close — agreed definitions applied consistently across all connected sources. Dashboards built on agreed data, not on whichever source happens to show the preferred number.
The dashboards are valuable. The automated reports are valuable. The anomaly detection — the layer that tells you something is wrong before you look for it — is where the business impact is largest. Issues caught in hours, not discovered at the weekly review.
We connect all Zoho products natively but also bring in external sources: Google Analytics, Shopify, SQL databases, Excel files. One analytics layer for all your business data regardless of where it lives.
Every metric on every dashboard should drive a decision. Metrics that don't drive decisions are visual noise. We design dashboards around the questions leadership actually asks — not around what the data makes it easy to show.
NDA before day one. ISO 27001. We audit your data quality before recommending any dashboard build.
Data model agreed first. Dashboards built second. Anomaly detection configured third. Reports automated last.
We audit data quality across all connected sources and define canonical metric definitions before a single dashboard is built.
One agreed definition for every metric. Applied consistently across CRM, Books, Desk, People, and any external sources.
Role-based dashboards built against the agreed data model. Anomaly detection configured. Zia NLP enabled and tested.
Scheduled reports configured. Anomaly alerts tested. Leadership trained on Zia NLP. Ongoing monitoring established.
You get a weekly report that tells you what happened the week before. Anomalies are discovered at the Friday review, compounding all week. With Zoho Analytics, your executive dashboard is always current and anomalies surface within hours.
Two days on the board pack, eight hours on the weekly report, endless ad hoc data requests. Zoho Analytics automates the assembly — finance reviews and analyses instead of builds.
You have 140 deals in CRM and no way to tell which ones are genuinely progressing. Deal scoring, activity analysis, and at-risk detection surfaces where to focus and what's at risk — before it's too late to act.