How to Project Sales: Step-by-Step Guide for Businesses

Projecting sales accurately is crucial for businesses to make informed decisions, set realistic goals, and ensure long-term success. In fact, companies that excel at sales forecasting are 7.3% more likely to hit their targets and grow their revenue by 10% or more. This step-by-step guide will walk you through the process of projecting sales, from choosing the right forecasting methods to leveraging AI tools like Bardeen to automate repetitive tasks.

Whether you're a seasoned sales professional or just starting, you'll discover valuable insights and practical tips to take your sales projections to the next level. So, are you ready to unlock the secrets of accurate sales forecasting and skyrocket your business growth?

Choosing the Right Sales Forecasting Methods

With multiple sales forecasting methods available, selecting the right ones for your business is crucial. Here's how to choose:

1. Align with sales goals: Ensure the forecasting methods support your overall sales strategy and objectives.
2. Consider data availability: Choose methods that match the type and amount of sales data you have.
3. Evaluate resources: Pick methods you have the time, expertise, and tools to implement well.
4. Analyze past performance: Look at the historical accuracy of different methods to inform your decision.

Most businesses use a combination of forecasting methods rather than just one. Using multiple methods provides a more comprehensive and accurate sales forecast.

After selecting your forecasting methods, follow these steps to perform a sales forecast:

1. Gather relevant data like past sales, customer info, and market trends
2. Analyze the data to identify patterns and correlations
3. Choose a forecasting model based on the data and goals
4. Use the model to predict future sales
5. Regularly compare forecasts to actual results and adjust the model as needed

By choosing the right mix of sales forecasting methods and following a structured process, you can generate more accurate and actionable sales predictions to inform decision-making across the business. For more insights on building a prospect list, check out our guide.

Gathering and Analyzing Sales Data for Forecasting

Accurate sales forecasting requires gathering the right data and analyzing it effectively. Historical sales figures, lead and opportunity data from CRMs, and industry trends all provide valuable inputs. But the data must be properly cleansed, organized, and prepared for analysis to yield meaningful insights.

1. Collect Comprehensive Sales Data

Projecting sales starts with collecting relevant data from various sources:

• Historical sales figures broken down by product, region, sales rep, etc.
• Lead and opportunity data from your CRM system
• Website traffic and conversion metrics
• Industry reports on market size, growth rate, and trends
• Economic indicators like GDP growth, unemployment rate, etc.

Cast a wide net to gather data that reflects the many factors influencing your sales. More data generally enables more accurate forecasting.

2. Clean and Organize the Data

Raw sales data is rarely ready for analysis right away. Common issues include missing values, formatting inconsistencies, outliers, and duplicate records.

Take time to review and clean your data to ensure accuracy and completeness. Standardize field formats, remove duplicates, and decide how to handle missing values.

Then organize the data in a structured way, such as a spreadsheet or database, to streamline analysis. Merge related data sets together and consider creating separate tables or views for different types of analysis.

3. Analyze Patterns, Trends and Key Metrics

With clean, organized data in hand, you can begin deriving insights to inform your sales forecast. Techniques to try include:

• Identifying seasonality, year-over-year growth, and other time-based patterns
• Comparing sales across different lead sources, territories, customer segments, etc.
• Calculating conversion rates, sales cycle length, average deal size, and other key metrics
• Running statistical analysis to measure correlations and forecast future sales based on leading indicators

Save time and increase accuracy in your sales forecasting by using Bardeen's automation tools to handle repetitive tasks and analyze your data more effectively.

Look for the patterns and metrics that have historically been most predictive of sales for your business. Insights from this analysis will form the foundation for building your forecast model.

Thorough data collection and analysis is essential for sales forecasting. Take time to gather comprehensive data, clean and organize it properly, and mine it for insightful patterns and metrics.

Up next, learn how to use these insights to develop a robust sales forecast model. The next section walks through the process step-by-step.

Building Robust Sales Forecast Models Step-by-Step

Developing a reliable sales forecast model is critical for projecting sales accurately. The process involves building the model framework, layering in advanced techniques, and pressure testing the outputs. By following a structured approach, you can create a model that provides trustworthy sales predictions to guide business decisions.

1. Construct a Basic Forecast in a Spreadsheet

Start by setting up a spreadsheet with the core components of a sales forecast:

• Timeline (months, quarters, years)
• Number of leads, opportunities and closed deals
• Conversion rates between each stage
• Average deal size and sales price

Use formulas to project future sales from these inputs. For example, multiply leads by conversion rates to estimate closed deals, then multiply by average price to forecast revenue.

A simple model like this is a good foundation. But to maximize accuracy, you'll want to incorporate advanced techniques covered next.

2. Enhance the Model with Advanced Factors

With the basic framework in place, make the model more sophisticated by accounting for additional factors:

• Seasonality: Layer in seasonal sales patterns from historical data
• Sales cycle changes: Account for deals taking more or less time to close
• Rep ramp time: Model the learning curve for new sales hires
• Segment differences: Forecast separately for different products, regions, or customer types

Analyze past data to quantify these effects and factor them into the model's formulas. The exact techniques will vary based on your business.

The goal is evolving the model to reflect the nuances of your sales process and market. The more realistic the model, the more accurate the projections.

3. Stress Test the Model Outputs

Before relying on the model, validate that it performs well by:

• Back-testing: Compare model projections to actual results from past time periods
• Scenario planning: Model how sales would change if key inputs increased or decreased
• Sensitivity analysis: Identify which assumptions have the greatest impact on the outputs

Testing helps uncover errors or hidden risks in the model. It also builds confidence in the forecast outputs.

Iterate on the model until it demonstrates strong predictive power. Document assumptions and limitations for transparency.

A trustworthy model is essential for translating sales forecasts into decision-making. Investing time upfront to get it right pays dividends.

The key things to remember: start simple, layer in complexity, and validate the outputs. This approach will result in a model that reliably projects sales.

Coming up, discover how to use the sales forecast model to guide core business planning processes. We'll explore applications to budgeting and planning, hiring, pricing and more.

Applying Sales Forecasts to Drive Better Business Decisions

Sales forecasts are a powerful strategic tool for guiding core business planning processes. By projecting future revenue, forecasts enable more informed decision-making around budgeting, hiring, inventory, pricing, and more. Integrating forecasting with other functions aligns the entire organization around a single view of expected performance.

1. Support Key Planning Activities with Forecast Insights

Use sales forecasts to build annual budgets, set sales quotas, and allocate marketing spend based on projected revenue by segment. Adjust hiring plans and compensation structures according to growth expectations. Optimize inventory levels and production schedules to meet demand predictions.

For example, a forecast predicting 25% growth in a key product line would trigger increased investment in production capacity, sales headcount, and marketing for that offering. Regularly revisiting forecast assumptions keeps resource allocation aligned with the latest sales outlook.

2. Integrate Forecasting with Finance, Marketing and Operations

Treat the sales forecast as a shared strategic asset, not a siloed sales tool. Collaborate with finance to sync forecasts with financial plans and investment strategies. Work with marketing to validate assumptions about demand generation. Align with operations on capacity requirements.

Integrated forecasting enables coordinated, agile planning cycles. For instance, by jointly monitoring the forecast, sales and marketing can quickly adjust lead generation spend if opportunities aren't progressing as expected. Removing silos keeps execution in lockstep with forecasts.

3. Continually Monitor and Course-Correct Based on Actuals

Regularly compare forecasted versus actual results to gauge accuracy, understand variances, and identify risks or opportunities. Feed lessons learned back into forecast models to enhance predictive power.

If an unforeseen competitor enters the market, for example, immediately quantify the impact on the forecast and adjust sales targets or hiring accordingly. Proactively update key stakeholders about material forecast changes so they can adapt their plans.

Monitoring also reveals leading indicators of sales performance, like opportunity volume or pipeline velocity. Track these metrics to detect trends that could alter future forecasts.

The bottom line: effective business planning hinges on sales forecasts, so make sure they're fully integrated into decision-making processes across the organization. Collaborative, data-driven forecasting aligned with actual results will drive smarter resource allocation and improved performance.

Save time and focus on what matters by automating sales prospecting with Bardeen. Spend less effort on repetitive tasks and more on closing deals.

We've covered a lot of ground in this guide to sales forecasting. Give yourself a pat on the back if you've read this far - your forecasting acumen has leveled up! But don't get too comfortable, because without mastering these practices, you risk missing your number and losing credibility in the market.

Conclusions

Accurate sales projections are critical for effective business planning, budgeting, and goal setting. In this guide, you discovered:

• Selecting the optimal forecasting method based on data availability, business maturity, and sales cycle
• Gathering, cleansing, and analyzing sales data to identify trends and calculate key metrics
• Building, refining, and pressure testing sales forecast models in spreadsheets
• Applying sales forecasts to guide strategic decisions across the organization

Don't leave your company's future to chance - master the art and science of sales projections or risk missing targets and losing market share!