What is Sales Forecasting
Sales Forecasting is a process in which a company models future revenue based on a combination of historical data, the current sales pipeline, market trends and internal factors (production capacity, campaigns), typically on a monthly, quarterly or annual basis.
Most commonly used methods
| Method | Description | When it makes sense |
|---|---|---|
| Historical trend | Projecting year-on-year growth and seasonality into the future. | Stable market, repeat orders. |
| Pipeline-based | Sum of opportunities × probability of closing by CRM stage. | Long B2B cycle, detailed data in CRM. |
| Bottom-up (Deal Forecasting) | The sales representative estimates the closure of each deal (commit / upside). | Fewer large contracts. |
| Top-down (Market Share) | The company’s share of the estimated market × expected market growth. | New products, market expansion. |
| Machine-learning models | The algorithm takes hundreds of factors into account (lead activity, weather, advertising). | Sufficient historical data, BI team. |
The highest accuracy is usually achieved using a hybrid model – combining historical trends, pipeline data and AI scoring.
Why Sales Forecasting is important for B2B
- Cash flow and production
planning An accurate revenue forecast enables the CFO to manage working capital, whilst the COO knows how many units to produce and when. - Pipeline prioritisation
A probability-based forecast identifies ‘weak’ quarters in advance. Sales and marketing teams can quickly launch campaigns or ABM initiatives. - Motivation and quotas
Realistic sales quota figures boost confidence and reduce staff turnover; they also help HR plan recruitment. - Investor Relations Both
public and private companies must report revenue forecasts. An accurate forecast enhances credibility with investors and reduces the cost of capital. - Risk Reporting (Early Warning System)
Early warnings of a drop in revenue give management the opportunity to reallocate the budget, adjust the marketing mix or reorganise production.
Practical applications and examples
- AI-powered Forecast in Salesforce Einstein
CRM predicts the probability of closing each opportunity. The accuracy of the quarterly forecast rises from 73% to 88%. - Weighted Pipeline in an industrial company
: ‘Proposal’ phase 10%, ‘Offer’ 40%, ‘Negotiation’ 70%. Total weighted pipeline CZK 80 million vs. target CZK 100 million. Triggers a marketing push campaign. - Scenario planning
A software vendor builds three scenarios (optimistic, likely, worst). The 25% difference between the likely and worst scenarios is covered by the capacity of external developers on meal vouchers. - Rolling Forecast
Instead of annual plans, the company rolls out a 12-month horizon every month. When competitors withdraw from the market, it immediately increases the forecast and production. - Deal-by-deal Commit
For technology integrations with a deal size > CZK 5 million, each sales representative manually marks ‘commit’/‘upside’. Accuracy in enterprise segments: 10 percentage points
5 tips for improving sales forecasting
- Keep CRM data clean:
deduplicate accounts, update stages, require mandatory fields (value, close date). - Define phase exit criteria
Transition from “Offer” to “Negotiation” = confirmed budget and timeline. Eliminates false optimism. - Introduce objective Lead/Deal Scoring
AI models or a points system to reduce salespeople’s subjectivity. - Analyse the variance between forecast and actual. Conduct a “forecast
accuracy review” after each quarter. Identify recurring errors (e.g. unrealistic close dates). - Link marketing signals Lead
activity (downloading a datasheet, viewing pricing) can be a stronger predictor than time spent in a stage.
Related terms
- Pipeline Management – operational management of opportunities, the basis for forecasting.
- Revenue Operations (RevOps) – integrates marketing, sales and customer care data.
- Sales Enablement – materials and processes that increase the likelihood of a deal being closed.
Further resources
- HubSpot – Ultimate Guide to Sales Forecasting (https://www.hubspot.com/sales-forecasting)
- Gartner – Predictive Sales Forecasting (https://www.gartner.com/)
- Salesforce – State of Sales Report (https://www.salesforce.com/resources/)
Summary
Sales forecasting provides B2B companies with predictability, reliability and control. Using clean data, clear stage criteria and modern AI models, you can not only accurately estimate revenue but also identify risks and growth opportunities in good time. If you wish to set up or refine forecasting within your organisation, please do not hesitate to contact us.