Sales Forecasting: Using Historical Data to Predict Future Success
Predicting future sales performance can feel like forecasting next year’s weather.
Is it going to rain deals? Or should you prepare for a lead drought?
Fortunately, sales forecasts don’t have to rely on gut feeling and guesstimation. It is possible to accurately predict future performance – if you know how to find, interpret, and action the right historical data.
What is Sales Forecasting and Why is it Important?
Sales forecasting is the process of analyzing past performance to estimate future sales in a specified time period. Alongside internal considerations, sales forecasts take external factors like economic conditions and consumer trends into account.
Accurate sales forecasting informs:
Budget allocation: would increased marketing spend generate more leads?
Team planning: do you need to recruit or upskill to embrace future opportunities?
Goals & KPIs: do sales and marketing teams have ambitious but attainable targets?
Strategic decisions: is now a good time to explore business expansion?
Despite its importance, many organizations struggle with sales forecasting:
55% of sales leaders and 57% of quota-carrying sellers lack confidence in forecast accuracy.
By 2025, 90% of enterprise sales organizations will still rely on intuition for sales forecasting, instead of advanced data analytics.
4 Steps to Use Historical Data for Accurate Sales Forecasting
1. Identify Accurate Data Sources
Focus on your CRM as the single source of truth for data collection. Sales records, customer data, purchase trends, and seasonal patterns are all invaluable as you begin your analysis. The challenge? Translating this abundance of data into concise findings. For a platform like Salesforce, you need a reporting solution that captures all of your historical touchpoints in custom dashboards, so you can extract meaningful insights with ease. With a Salesforce-native solution, you also avoid data syncing, storage and security issues as you gather your reports.
2. Build Your Attribution Models
Next, use your historical Salesforce data to build multi-touch attribution models. To assess the full customer journey, you need a solution that supports multiple, customizable dashboards with open weighting and scoring. This uncovers your most successful marketing channels and campaigns, and empowers you to double down on the tactics that drive the most ROI. With this granular understanding of marketing performance, you can also predict future lead volume with much greater accuracy.
3. Analyze the Sales Pipeline
Multi-touch attribution gives sales and marketing better visibility of the journey from awareness to qualified lead. But what happens when a customer enters the sales pipeline? Seek out a solution that connects leads, contacts, opportunities, and accounts into customized funnels in Salesforce. Most importantly, ensure leads can be linked to previous unknown sessions to get the most from your historical data. Evaluate deal velocity and conversion rates to predict future sales volume and timing with greater precision.
4. Forecast, Optimize, Adjust
All of this research and analysis gives you a solid overview of current performance. But how do you forecast what happens next?
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- Option 1: Maintain the same strategy and hope historical data repeats itself.
- Option 2: Invest in high-performing campaigns, optimize or eliminate under-performing channels, and adapt your strategy to drive increased sales and revenue.
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To determine the true potential of Option 2, build out a new funnel in your CRM and tweak the numbers to reflect changes in strategy. Manually, this process is time-consuming and labor-intensive. With an advanced solution, you can build a forecast in as little as 5 minutes.
Your Historical Data Holds the Key to Future Success
Predicting future sales doesn’t have to involve a crystal ball. With the right technology, it’s possible to pull an accurate forecast that you can confidently bring to the board (without hours of painstaking calculations). For a better sales forecasting experience, invest in a solution that makes historical data analysis effortless.
