Analytics software, compared
Most CPG brands choose between spreadsheets, a BI suite, a planning platform and an enterprise data platform. Each is right for something. This page sets them against the questions CPG brands actually ask, and shows what each needs before the first answer.
Excel or Google Sheets, with exports pasted in and formulas rebuilt each period. Suits a one-off question that will not come back.
Business intelligence tools for modelling data, building dashboards and sharing reports. Suits an organisation standardising reporting across many teams.
Platforms for budgeting, forecasting and scenario planning, connected to the ledger and other systems. Suits a finance team replacing spreadsheet budgeting across the organisation.
Platforms that integrate an organisation's systems into one governed model and build applications and AI on top of it. Suits a programme to connect many systems across the whole organisation.
Reads the exports CPG brands already produce and answers the questions below, with every figure computed by our tools and checked. Set up for you within a week.
| Time to the first answer | What it needs | Who builds it | Where “why” comes from | |
|---|---|---|---|---|
| Spreadsheets | Hours, and the same hours again every month | An analyst's time each period | An analyst, by hand, every period | Whatever the analyst builds that month, checked by whoever has time |
| BI suites | Usually days to weeks: a data model built, measures written in the tool's own language, reports designed | A clean data source or warehouse, a data model, and someone who can write the tool's measures | A BI developer or analyst, often in a central data team | A dashboard shows what changed; explaining why is usually a new report someone builds |
| FP&A and planning platforms | Usually months: models built, the ledger and other systems integrated, often with an implementation partner | Model builders, integration with the ERP or general ledger, and an implementation project | Certified model builders, internal or from a partner | Built to produce the plan; explaining the month's variance often goes back to a spreadsheet |
| Enterprise data platforms | Usually weeks to months: sources integrated, a data model or ontology built, then applications on top | Integration work across source systems, a data model, and engineers who build and maintain it | Data engineers, often with the vendor's own engineers or a partner | Possible once the model is built, as an application someone designs for it |
| Covirage | Minutes on a file you already export; set up for you within a week | The exports your systems already produce. No warehouse, no modelling language, no data team | We map the columns once and set the dashboard up for you | An explain block splits every change into its causes; the lines sum to the change, and each opens to its rows |
These are typical patterns, not a verdict on any product. Each kind of tool is right for somebody; the table shows who does the work before CPG brands get an answer.
| The question | The measure | What Covirage returns |
|---|---|---|
| Explain where my revenue is coming from this quarter. | Price, volume and mix bridge | The change split into price, volume, mix, new and lost lines, by retailer and category, summing to the change exactly. |
| Where are we losing market share? | Rate of sale | Share by category and retailer from the market file against the prior period, with the SKUs behind each move. |
| Which promotions actually paid back? | Promotional net lift | Lift against baseline, the dip after, net units and margin against trade funding, per event. |
| Where are we listed but not stocked, or stocked nowhere? | Distribution voids | SKU and store combinations that similar stores carry and this one does not, valued at rate of sale. |
| Are we shipping more than the retailer is selling? | Sell-in against sell-out | Shipments against retailer sales by SKU, with weeks of cover and the inferred out-of-stocks. |
| What are chargebacks costing us, and why? | Chargebacks by retailer and reason | Deductions by retailer and reason code against invoiced value, with the repeat reasons. |
Every one is an export your systems already produce. Every way data can arrive is listed on the upload page.
Net lift. Most promotion reviews stop at the uplift in the promotional weeks and never subtract the dip.
Sell-in against sell-out. The sales team is paid on sell-in and the data for sell-out sits in another team.
Chargebacks by reason. Treated as a finance line. Sorted by reason, most trace to a few fixable causes: labelling, appointment times, advance ship notices.
Each page sets out what the product is built for, where it is strong, and when a lighter option fits better.
Alteryx alternatives · Domo alternatives · Palantir Foundry alternatives
Databricks AI/BI alternatives · Looker alternatives · Metabase alternatives · Power BI alternatives · Qlik Sense alternatives · Sigma alternatives · Sisense alternatives · Tableau alternatives · Zoho Analytics alternatives
Adaptive Planning alternatives · Anaplan alternatives · Pigment alternatives · Planful alternatives · Vena alternatives
It depends on what is in place. With a warehouse and a data team, a BI suite or a data platform gives the most control. With exports and a question that recurs every month, a tool that reads the files and answers the question directly gets there sooner. The table on this page sets the options side by side for the questions CPG brands ask.
Not to start. The measures on this page are computed from exports CPG brands already produce: store list, sell-out data, store attributes, shipment ledger. A warehouse helps when many systems must be joined continuously; it is not a prerequisite for the first answer.
It varies by approach: usually days to weeks: a data model built, measures written in the tool's own language, reports designed for a BI suite, usually months: models built, the ledger and other systems integrated, often with an implementation partner for a planning platform, and minutes on a file with Covirage, set up for you within a week.
In Covirage the AI model never does the arithmetic. It chooses the measure and explains the result; our tools compute every figure and check that the totals reconcile before anything is shown.
Asset managers · Commercial banking · Compliance · Construction and building materials · Consulting and advisory · Customer service · Distributors · Education · Finance and FP&A teams · Financial services · Foodservice distributors · Freight brokers and 3PLs · Healthcare and med-tech · Hospitality · Industrial distributors · Industrial manufacturers · Insurance brokers · Investment banking · Law firms · Oil and gas services · Pharma · Procurement · Retail banking · SaaS · Sales teams · Shipping and logistics · Sports · Supply chain · Tax and accounting · Telecoms and connectivity · Trading · Wealth managers
Bring an export you already produce. The data map opens next, every column mapped once, and the first question is answered in minutes. Free, in your browser, no account. Or talk to us and we will set it up for you.