How to Forecast New Home Sales for Next Year: Essential Steps including Sample Examples and Calculations

Having navigated over 25 years in new home sales and forecasting, I’ve found that a structured approach like this one enhances planning accuracy and resource coordination, which I’d like to share.

Developing a comprehensive sales forecast isn’t an easy undertaking, but is invaluable—not just for setting sales targets, but for providing key insights to those in senior leadership positions such as the VP of Finance, Construction, Ops and the Division President to help guide their strategic decisions.

In my experience, when we actively research and refine forecasts based on historical sales data, qualified traffic patterns, conversion rates, and community timelines, we support our leadership team with a dependable foundation for budgeting, staffing, and inventory planning. By owning this process, sales leaders can offer grounded, real-time market perspectives that refine our forecasts, highlight growth opportunities, and strengthen our division’s competitive edge. A disciplined, data-driven approach allows us to anticipate challenges and respond strategically, ensuring we support our leadership and position the division for sustained success.

Let’s dive into a step-by-step guide on how to forecast new home sales, with examples to illustrate each step.

1. Review Past Sales Performance and Closings Data

To start, historical sales data gives a foundation for forecasting by revealing trends, seasonality, and sales cycles. Suppose last year’s data for a new development, Oakwood Estates, shows:

• Annual Sales: 50 homes sold
• Monthly Breakdown: Sales peaked at 8 homes in April and were lowest at 3 homes in November.

Analyzing this data helps uncover patterns, like a seasonal spring surge in sales. Use this data to estimate next year’s baseline but adjust if market conditions or product offerings change significantly.

Example Calculation: If Oakwood Estates expects similar conditions, use 50 homes as the annual baseline for forecasting, with adjustments for monthly variations.

2. Analyze Qualified Traffic Data

Qualified traffic—leads who show strong buying interest and meet initial criteria—drives the sales pipeline. At Oakwood Estates, suppose last year’s data shows:

• Average Monthly Qualified Traffic: 120 visitors, with a peak in March at 180.
• Traffic Sources: 60% from online ads, 25% from realtor traffic, and 15% from social media.

If online ads brought the most qualified leads, consider increasing the digital advertising budget. Additionally, project a 10% growth in online traffic based on recent marketing campaigns.

Example Calculation: With the projected growth in online traffic, Oakwood Estates could expect an average of 120 qualified visitors per month (120 x 1.10 = 132), increasing traffic and potentially boosting sales.

3. Calculate Conversion Rates

Conversion rates—the percentage of qualified leads who purchase a home—are essential for forecasting. Last year, Oakwood Estates had:

• Average Conversion Rate: 10% (e.g., 12 out of 120 monthly qualified visitors bought homes)
• Seasonal Variation: March through May showed a 12% conversion rate, while November was only 5%.

Apply these rates to projected monthly traffic to estimate the number of sales.

Example Calculation: For March, with 180 qualified visitors and a 12% conversion rate, Oakwood Estates could expect 22 sales (180 x 0.12 = 22).

If conditions remain stable, use these rates for monthly forecasts, making adjustments for anticipated seasonal or market shifts.

4. Consider New Community Openings and Closures

Next, new community openings or closures impact the overall sales volume and inventory. Suppose Oakwood Estates will finish its last phase in September, and a new community, Maplewood Villas, will open in October as its replacement.

• Oakwood Estates Closing: 15 homes remain for the year.
• Maplewood Villas Opening: A projected 50 homes are available upon opening, with an expected initial 20% higher traffic due to a fresh Grand Opening launch.

New communities often attract more traffic and higher conversion rates in the initial months (depending on your market.) Plan to increase sales projections and staffing to manage the higher traffic and sales volume.

Example Calculation: If Maplewood Villas opens with an expected 20% traffic boost in October, projecting around 144 visitors (120 x 1.20 = 144) and a conversion rate of 12% results in a forecast of 17 sales (144 x 0.12 = 43) for its launch month.

5. Account for Staffing Changes and Productivity

Sales staff productivity directly influences sales outcomes. Review historical performance data for each sales professional. Suppose Oakwood Estates has two new home sale counselors:

• Average Sales per Agent: 15 homes per year, with top performers selling up to 20 homes.
• Staff Changes: Two new sales counselors will join Maplewood Villas in October, as the Oakwood estates sales counselors would remain to take care of their backlog of closings and any potential homes that return to the market.

New sales counselors and/or new product typically may need time to reach full productivity, so consider a conservative forecast for their first few months.

Example Calculation: If the two new sales counselors are expected to reach 75% productivity by December, forecast 6 sales per new sales counselor (75% of 8 sales per each counselor for Q4) for their first months on the job.

These estimates allow you to allocate resources appropriately and set realistic sales targets for each community.

6. Integrate Market Trends and External Factors

External market factors—like interest rates, local demand, competing builders and resale inventory—affect the buying power of potential clients. Oakwood Estates, for this example, operates in a region experiencing steady population growth and demand for suburban homes.

• Economic Conditions: With mortgage rates expected to remain stable, affordability should not hinder sales significantly.
• Local Competition: Three new developments by competing builders are scheduled to open within a 5-mile radius by mid-year, likely impacting sales at Oakwood Estates and Maplewood Villas.

Adjust forecasts for a potential market share impact due to increased competition, possibly reducing the projected conversion rate by 2% in Q3.

Example Adjustment: If the forecasted 10% conversion rate is reduced by 2% due to new competition, adjust the monthly sales forecast for impacted months. For instance, with 120 qualified leads at an 8% conversion rate, project 10 sales rather than the original 12.

7. Develop Your Forecast Model

Now, bring these components together into a monthly forecast. A spreadsheet is an effective tool for this, with columns for projected traffic, conversion rates, and calculated sales volume per community.

Each row represents a month’s forecasted sales, accounting for traffic, conversion rates, and new community openings. Use similar tables for each community if managing multiple locations.

8. Set Benchmarks and Regularly Review Your Forecast

A forecast is only effective if it’s monitored and adjusted as needed. Many builders require reforecasting on a regular basis. Set quarterly or monthly benchmarks to compare projected and actual sales, allowing room to adjust for any deviations. Regularly share this data with your Division President and others, to properly help guide your team’s trajectory.

For example, if qualified traffic in January falls short by 20%, reduce February’s forecast or plan an immediate marketing boost. (This will also affect your projected closing pipeline.) Similarly, if staffing changes lead to unexpectedly high productivity, adjust expectations accordingly.

I have learned that a balanced sales forecast is built by incorporating historical data, reviewing traffic and conversion trends, accounting for the timing of communities, and remaining responsive to market shifts. By creating a detailed and flexible forecast and reviewing it consistently, new home sales leaders can strategically allocate resources, meet goals, and stay resilient in the face of market changes."