We build dynamic, data-led forecasting models that predict revenue, acquisition, retention and channel performance. Giving you clear visibility over growth, budgets, stock and resourcing.
Most brands forecast using gut feeling, last year's numbers, spreadsheet templates with hidden logic and unrealistic growth assumptions. Incorrect attribution, broken tracking and poor understanding of retention and repeat revenue compound the problem.
Reliable forecasting requires clean data, stable attribution and a clear growth engine. Qwrki builds forecasting as a commercial system. Dynamic, scenario-tested and updated monthly as actuals arrive.
Last year's numbers multiplied by an optimistic growth rate. Hidden spreadsheet logic nobody can audit. Budgets that don't hold under pressure. Leadership teams that stop trusting the numbers.
Data-led growth assumptions, retention curves, channel efficiency curves and scenario models. Updated monthly with actuals so the forecast becomes more accurate as the year progresses.
Reliable forecasting requires
Forecast inputs
Monthly revenue projections with new vs returning customer splits, baseline growth vs incremental growth, LTV and repeat revenue forecasting, cohort-based projections and product and category contribution. A complete commercial revenue picture.
Expected CAC and ROAS, MER modelling, spend-to-revenue curves, diminishing returns modelling, channel efficiency forecasting, scenario testing for spend changes and impact of conversion rate changes. Connecting media budgets to revenue outcomes.
Journey progression forecasts, second purchase rate projections, churn and reactivation modelling, replenishment or subscription forecasting and lifetime value predictions. Modelling the retention engine as a revenue component in its own right.
AOV scenarios, conversion rate uplift scenarios, stock-level impact forecasting, new product launch projections and pricing experimentation scenarios. Three scenario models (conservative, realistic and aggressive), each with revenue, CAC, MER, LTV and operational requirements.
Media budgets, hiring plans, retention investment, CRO investment, infrastructure investment and inventory forecasting. Translating revenue projections into operational decisions across the entire business.
Phase 01
We validate acquisition numbers, conversion rates, retention curves, CAC and MER, LTV, product contribution and channel efficiency. Baseline truth must be accurate. Forecasting on wrong actuals produces wrong projections, no matter how sophisticated the model.
Phase 02
We build growth assumptions, retention curves, channel efficiency curves, predictive LTV models, scenario logic and a forecasting spreadsheet or dashboard. A dynamic model that updates as inputs change.
Phase 03
We generate best case, most likely, worst case and stretch target scenarios. Shaping marketing budgets, stock planning, revenue targets and operational decisions based on a range of outcomes, not a single fixed projection.
Phase 04
Forecasts are updated monthly with new actuals, updated efficiency metrics, retention performance, paid media changes and product performance. The model becomes more reliable as the year progresses.
Phase 05
We deliver revised projections, seasonality adjustments, risk modelling, growth opportunity analysis and channel investment strategy. Connecting forecasting into forward planning and strategic resource allocation.
Forecasting is the planning engine of the OS. Connecting validated performance data from every module into forward-looking commercial decisions.
Forecasting & Projections
Analytics & Intelligence
Analytics Dashboards
Analytics dashboards provide the validated actuals that form the baseline for every forecast model. Garbage in, garbage out.
Reporting & Insights
Monthly reporting feeds actuals into the forecast model. Keeping projections updated against real performance rather than fixed assumptions.
CRO Testing
Conversion rate improvements from CRO directly update revenue forecast models. A 0.5% CVR uplift has a calculable revenue impact across spend scenarios.
Paid Search
Paid search efficiency curves feed acquisition forecasting. Modelling how ROAS and CAC change as spend scales across Search, Shopping and PMax.
SEO
Organic traffic growth projections feed revenue forecasting. Separating incrementally new organic revenue from cannibalisation of paid.
Email & Lifecycle
Retention and repeat revenue from lifecycle flows feed repeat purchase rate forecasting. The most predictable component of revenue for established brands.
Customer Journeys
Lifecycle progression rates feed second purchase projections and LTV modelling. Journey performance directly shapes retention forecasts.
Reliable revenue forecasts. Updated monthly, grounded in validated actuals.
Clear growth targets that the business can plan hiring, stock and budgets around
Accurate CAC, ROAS and MER expectations across realistic and aggressive scenarios
Realistic LTV and retention projections built on actual customer behaviour curves
Scenarios for risk and opportunity. Conservative, realistic and stretch, stress-tested.
Better budget and hiring decisions grounded in commercial outcome ranges
Confidence in scaling paid media. Knowing the efficiency curve before spending.
A forecasting system that evolves with your business and improves in accuracy over time
Building data-led revenue targets for the year. Grounded in actuals, channel efficiency curves and retention rates, not aspirational numbers from a spreadsheet.
Translating revenue projections into media budgets, headcount plans and infrastructure investment. Connecting commercial targets to operational decisions across the business.
Building credible, data-backed revenue projections for investor or board presentations. Scenarios that can be interrogated and defended with underlying model logic.
Modelling how much customer acquisition cost can flex before profitability breaks. Understanding the spend-to-revenue curve and where diminishing returns begin.
Forecasting demand by product, category or SKU ahead of launches or high-volume periods. Ensuring stock levels are set against projected sell-through rates, not guesswork.
Modelling spend-to-revenue curves to identify the optimal paid media budget. The point where incremental spend still produces acceptable ROAS before efficiency collapses.
Get a forecasting audit and projection model proposal for your business.
Talk to a humanCore Performance
1.2s
LCP
14ms
FID
0.01
CLS
Deployments
84.2%
System Health
Stable
3 views
Conservative → Stretch
Plans
Data inputs · Forecast model · Scenario planning · Commercial clarity
eCommerce
Product contribution, AOV and catalogue performance feed product-level revenue projections and stock planning models.
