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Sales Forecasting

Discover smarter sales planning with real-time data and insights from LinkedIn.

Sell with LinkedIn / Resources / Sales terms / Sales forecasting

Sales Forecasting

Discover smarter sales planning with real-time data and insights from LinkedIn.

Global events, political shifts, and macroeconomic trends always make it difficult to predict sales volume.

 

However, there are ways for companies to improve their sales forecasting processes and optimize their sales team performance. This guide provides an overview of sales forecasting and strategies for maximizing sales.

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What is sales forecasting?

A sales forecast is an estimate of expected sales revenue within a specific time frame, such as quarterly, monthly, or yearly. It expresses how much a company plans to sell. Forecasters analyze economic conditions, consumer trends, past purchases, and competitors to make accurate predictions. This helps the business plan, allocate resources, and identify opportunities and risks. 

 

However, there are no universal solutions, and external factors can affect forecasts. Thus, it's critical to create a custom plan for data collection, evaluation, and forecasting.

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How is sales forecasting different than demand planning?

It’s common for people to confuse sales forecasting with demand planning. While sales forecasting and demand planning are both essential for managing inventory and resource allocation, they focus on different aspects of the process.

 

Sales forecasting focuses on predicting future sales of a product or service with the help of historical data, market trends, and other relevant factors. The primary goal of sales forecasting is to enable better financial planning, budget allocation, and strategic decision-making.

 

Demand planning, on the other hand, is a more comprehensive process that includes sales forecasting as one of its components. Demand planning takes a holistic approach, aiming to forecast customer demand and devise strategies to meet that demand efficiently while optimizing inventory levels, production, and resource allocation. Demand planning requires collaboration among multiple departments, including sales, marketing, operations, and finance.

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Why is sales forecasting important?

Sales forecasting helps businesses capture relevant data that leaders can use to make strategic business decisions. With accurate forecasting data, businesses can plan sales quotas strategically, allocate resources properly, and reduce unnecessary spending.

Other benefits of sales forecasting include:

  • Avoiding cash flow problems

     

  • Budgeting more efficiently

     

  • Planning for more accurate staffing

     

  • Aligning sales quotes with revenue expectations

     

  • Estimating future revenue more accurately

     

  • Focusing on high-revenue opportunities and eliminating sales failures

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Sales forecasting helps businesses capture relevant data that leaders can use to make strategic business decisions. With accurate forecasting data, businesses can plan sales quotas strategically, allocate resources properly, and reduce unnecessary spending.

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What a business needs to prepare for accurate sales forecasting

A business’s sales forecasting is only as good as its data collection methods. If a business doesn’t have good data about its own products and services, sales forecasts will be off, and revenues will drop.

Document sales processes

How a sales team approaches clients vary greatly depending on what the company offers and who its potential clients are. As such, it’s essential for businesses to document the various stages of their sales cycle.

 

When businesses understand each step involved in their sales process and review their current sales pipeline, it’s easier to capture data and identify potential problems and future opportunities.

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Review sales goals

It’s challenging for any business to make accurate sales forecasts if they don’t have a foundation.

 

Businesses that want to improve sales forecasting should start by setting sales and revenue goals. Businesses should also review those sales goals periodically to see if their sales team is hitting the mark or falling short.

 

When a business understands its sales goals and past performance, sales forecasting and related business decisions are more accurate.

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Review sales benchmarks

Benchmarks help companies understand the sales process and identify wins and shortcomings. Companies can then compare these benchmarks to new data and use them to set better goals and make more informed sales forecasts.

Some basic sales metrics to measure include:

 

  • Number of opportunities generated. The number of leads that have expressed interest in a product or service.

     

  • Conversion rate. The percentage of leads that have become customers.

     

  • Average deal size. The average amount of money customers spend.

     

  • Number of deals closed. The total number of purchases.

     

  • Average sales cycle. The average amount of time it takes for a company to complete a full sales cycle.

     

  • Win/loss ratio. The amount of sales that have been won versus those that have been lost.

     

  • Customer retention rate. The percentage of customers that continue doing business with a company.

     

  • Customer lifetime value. The total value a customer brings to a business over the entire course of their relationship.

     

  • Sales productivity per sales representative. A measure of the effectiveness of each sales representative, usually measured by the number of sales closed divided by the number of working hours.

By establishing benchmarks, companies can better measure and identify the progress of their sales, have a reliable starting point for forecasting, and gain a better understanding of their overall performance.

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The sales forecasting process

Gartner reports that 55% of sales leaders and 57% of quota-carrying sellers lack confidence in forecast accuracy. Additionally, Gartner projects that by 2025 90% of enterprise sales organizations will still rely on intuition instead of advanced data analytics.

 

The result of relying on intuition over hard data can result in inaccurate forecasts, missed sales quotas, poor inventory, and missed opportunities with investors.

 

The first step businesses need to take in order to be excluded from this grim statistic is to establish a proven forecasting process. Here’s a closer look into a winning sales forecasting process.

Set sales forecasting goals

Before setting forecasting goals, a business should have already documented sales processes, reviewed sales goals, and reviewed sales benchmarks.

 

The next step in the process is to use that data to set forecasting goals. Companies can start this step by looking closely at the last few years of business performance data—especially as it relates to sales and revenues.

 

Analyzing historical data provides an excellent baseline for establishing forecasting goals. Next, examine future growth potential. Take into account time-sensitive market factors, economic conditions, competitor research, consumer behavior, and new legislation.

 

Use this data to set realistic expectations for your forecasting efforts.

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Invest in sales forecasting technology

It’s difficult for any company to predict future sales performance if they don’t have the necessary technology to capture the right data, analyze that data, and use it to make projections.

 

An essential step in the sales forecasting process is to review CRM data. Companies should make sure CRM data is up-to-date and integrates well with other data collection software.

 

When looking for the right sales forecasting technology, businesses should opt for solutions that capture customer, sales, and historical data. Furthermore, the sales forecasting solution should integrate with all relevant data solutions and sync data in real-time.

 

A tool like LinkedIn Sales Insights is an excellent solution and helps sales teams capture robust, reliable, and trusted data for smarter sales planning.

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Gathering sales data

Most businesses have tools to continuously collect data. The next step is pulling together reports with the right data and cleaning that data.

Here are the most essential types of data to gather and analyze:

 

  • Sales data. Sales data is the most critical data to collect when forecasting. It can include sales performance information, inventory data, purchasing history, and any of the other pre-established sales benchmarks.

     

  • Market and industry data. Market data includes any recent and relevant analysis about the current economic and industry climate. This tells businesses what industry factors to take into consideration when making sales forecasts.

     

  • Customer data. Customer data includes any relevant information about a business’s customers as it relates to sales. This could include purchasing history, preferences, patterns, and demographics. Customer data helps businesses better target their customer base to improve the sales cycle.

     

  • Internal data. Internet data provides information about internal corporate changes that may affect sales. For example, turn over rate, new company policies, and new sales team hires are all internal data.
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Choose a forecasting methodology

As mentioned earlier, there is no universal sales forecasting methodology or solution. There are several ways to go about sales forecasting. The methodology a business chooses will depend on various factors. Here’s an overview of the most common types of sales forecasting methodologies businesses use:

  • Historical forecasting. Historical forecasting is when sales professionals look at past data to predict future trends. This methodology operates under the assumption that history repeats itself. For example, a business could look at past Black Friday sales and use that information to predict future Black Friday sales. While historical forecasting is a common methodology, it’s important to remember it doesn’t take drastic external or internal changes into consideration.

     

  • Pipeline forecasting. Pipeline forecasting is a methodology where sales professionals analyze the current sales pipeline and compare it to other sales data. This approach evaluates every potential opportunity a sales team has to close deals and sets goals based on that data. There are several tools that help sales forecasters dive deep into a current sales pipeline and make predictions.

     

  • Opportunity stage forecasting. Opportunity stage forecasting dives slightly deeper into the sales pipeline. It focuses on different potential sales in different stages of the deal. Sales forecasters use this data and compare it with metrics like the average length of a sales cycle to predict future closes. 

     

  • Intuitive sales forecasting. Intuitive sales forecasting is a method where sales forecasters interview sales teams and gather qualitative data and stories to understand the sales process better. While capturing first-hand information into the sales process is highly useful, it’s important to use it along with data-driven forecasting methods.

     

  • Length of sales cycle forecasting. Length of sales cycle forecasting focuses on how long it takes sales representatives to close a deal. Typically, sales forecasters will look at historical data and compare it with the length of the sales cycle. Then, they will use that information to make forecasts about future sales. 

     

  • Multi-variable sales forecasting. Multivariable sales forecasting is the most detailed and comprehensive forecasting methodology. It reviews comprehensive data and uses predictive analytics to make sales forecasts.
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Evaluating the sales forecast methodology and process

The last step in the sales forecast process involves periodic reassessments to the methodology, and the process is accurately measuring data.

 

Most sales forecasters will capture data in real time and set up a regular forecasting schedule. In addition to a regular forecasting schedule, a forecaster would re-evaluate sales forecasts every time there is a drastic internal or external change.

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Sales forecasting best practices and challenges

Sales forecasting is a data-driven approach to making sales and business decisions that grow a company. While there are many different ways to approach sales forecasting, there are some best practices every business can follow to ensure accurate and reliable results.

Here are some best practices for excellent sales forecasting:

  • Integrating findings into other business processes.

     

  • Involving other departments in the planning process.

     

  • Communicating findings with all relevant stakeholders.

     

  • Collaborating with sales and marketing teams to capture qualitative data.

     

  • Using technology to capture and analyze data and automate processes.

     

  • Revisiting sales forecasts regularly and anytime there’s a market change.

     

  • Considering all historical, economic, and market trends in forecasts.

Here are some of the most common challenges to consider when creating sales forecasts:

  • Lacking historical data or sufficient data.

     

  • Facing unpredictable market and economic conditions.

     

  • Adapting to rapid changes in consumer behavior and preferences.

     

  • Improving visibility into the future sales pipeline.

     

  • Anticipating the impact of promotions and other events accurately.

     

  • Planning for market disruptions.

     

  • Encouraging collaboration and communication among departments.

     

  • Overcoming resistance to change and adoption of new forecasting methods.

     

  • Encountering inaccuracies in data collection and analysis.

     

  • Addressing inconsistent sales performance across different regions or product lines.

It’s also essential to understand potential challenges with sales forecasting. Anticipating potential setbacks helps businesses prepare better.

 

These potential challenges can be offset with the help of robust and accurate data captured by LinkedIn Sales Navigator and proper planning.

Sales forecasting with LinkedIn

Sales forecasting is crucial for the success of any B2B business. When businesses prepare data, make goals, and choose a proven sales forecasting methodology, they capture insights that help them plan sales quotas and estimate future revenues.

 

Businesses looking for help with sales forecasting should look into LinkedIn Sales Navigator. LinkedIn Sales Navigator helps businesses target the right buyers, capture the right data, and transform sales planning with more accurate account insights to focus sales teams on the right accounts.

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