Bottom-up Forecasting: What Is It and How to Use it

“It is far better to foresee even without certainty than not to foresee at all.” Henri Poincare

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Bottom-up forecasting involves using statistical tools to analyze historical data about sales patterns, promotions, product demand, and other factors. It’s contrasted with top-down forecasting, which relies on macroeconomic trends and other broad indicators to predict what will happen in the future.

This article will explain bottom-up forecasting in detail and provide tips to help you apply this method to your business.

What is Bottom-up Forecasting?

Bottoms-up forecasting is a forecasting method that starts with the lowest level of detail (e.g., individual salespeople) and works toward the top (e.g., total sales). With this method, you first break down the total sales target into the smallest individual units and then do a forecast for each unit. The forecasted results are then added together to generate a total forecast.

Why Bottom-up Forecasting is Important

Bottom-up forecasting is like putting together a puzzle: you begin with all the little pieces and then combine them to create one unified picture. It gives you more insight into what’s happening in each department and how they affect each other. From that, you can identify areas to improve performance and opportunities for growth.

Additionally, because bottom-up forecasting relies on historical data, it allows sales leaders and managers to make more accurate predictions about future sales, costs, and profits.

How Bottom-up Forecasting is Used

If you’re an entrepreneur or business owner, bottom-up forecasting can help you determine how much inventory to buy and when to order it. This allows you to avoid costly mistakes like having too much inventory on hand or running out of stock unexpectedly.

You can also use bottom-up forecasting to predict customer behaviors, demand for a specific product or service, and incentives that appeal to target audiences. You’ll get a lot of valuable insights to develop effective marketing campaigns.

Want to learn more about sales forecasting and how to make accurate projections? Then, follow Revenue Grid’s blog to discover actionable tips from our experts.

Bottom Up Forecasting Formula

Most of the time, when using bottom forecasting, companies follow this simple formula:


Then, add up all revenue streams and subtract all costs to get a profit or loss for an observed period.

Take ecommerce businesses as an example. They need to forecast the demand for their products daily to ensure that they have enough stock. An ecommerce manager must understand how many products each customer is likely to buy in a given time and how many customers there are likely to be during that period. Then, calculate how many units of product they’ll need overall and multiply the average number of units purchased by your total number of customers to get the estimated revenue.

That said, different companies can use bottom up forecasting in different ways.

For example, a SaaS business sells subscription services. They often look at sales channels, number of active subscriptions per month, churn rate, etc., to forecast their revenue. Once they collect that information, they calculate how many leads they’ll have from each channel, how many will convert into paying customers, and how much those customers will spend on average. Then, multiply those numbers by how many months they’ll stay subscribed.

Bottom Up Forecasting Example

Let’s look at some examples to see how bottom-up forecasting can be used in practice.

Example 1: Estimating demand for a new product launch

Say you’re launching a new line of products. You’ve done your market research and understood the overall demand. However, you need to estimate the demand for each SKU to properly plan your production and inventory.

To do this, you can look at historical sales data for similar products that you’ve launched in the past. This will give you a good starting point for estimating demand for each SKU in the new product line. From there, you can make adjustments based on any unique factors that may impact demand for the new products.

Example 2: Forecasting demand during a promotion

Suppose you’re running a promotion where customers can get a free gift if they purchase two other products. You need to estimate how much demand will increase during the promotion so that you can stock up on the free item.

To do this, you can look at historical data for similar promotions that you’ve run in the past. This will give you a good idea of how much demand typically increases during a promotion like this. Then, use that number to estimate demand for the current campaign.

Bottom-up vs. Top-down Forecasting


Bottom-up and top-down forecasting are two common forecasting methods. They have their own pros and cons but also work together in ways that can be beneficial to your business.

As said earlier, bottom-up forecasting starts with the individual pieces that make up the whole and then builds up to the total.

Bottom-up forecasting pros:

  • Provides accurate information about future sales and costs to plan ahead.
  • Allows making adjustments quickly when needed—simply changing each individual part’s demand slightly instead of trying to adjust an entire schedule at once.

Bottom-up forecasting cons:

  • Doesn’t take into account external factors that could affect the demand for a product or service.
  • Can take a lot of time to collect and analyze data and reconcile it with other forecasts.

Meanwhile, top-down forecasting looks at the big picture and then breaks it down into smaller pieces. It involves taking a macro view of your business, analyzing market trends, and then projecting sales based on those trends.

Top-down forecasting pros:

  • Quick and easy to create a forecast as it doesn’t require much data analysis or statistical skills to implement.

Top-down forecasting cons:

  • Relies on aggregated data and can be more susceptible to errors.

Alternative Forecasting Methods

Apart from bottom-up and top-down, you can also try other forecasting methods, including trend analysis, regression analysis, and market analysis, to predict your future revenue.

  • Trend analysis looks at past performance to estimate future performance by comparing current data against historical data from the same periods. It’s useful if you have a lot of historical data available and your business has been relatively stable in recent years. It’s also suitable for short-term forecasting (usually up to 1 year). The downside is that it can be challenging to determine what trends will hold true in the future, so you may end up making projections that turn out to be wrong.
  • Regression analysis is similar to trend analysis, but instead of looking at historical data, it uses statistical tools to predict the future based on past performance. It can be helpful if your industry has experienced rapid growth or decline in recent years that was not reflected in historical trends. That said, regression analysis can be time-consuming and expensive when performed by human analysts. Some businesses use AI-powered tools that automate the process and save money on labor costs while delivering similar results.
  • Market analysis looks at how well other companies in your industry are doing compared with yours. This is useful when determining whether there’s room for growth within your niche or whether it’s best for you to focus entirely on other areas of business.

How to Improve Your Revenue Forecasting Model

Revenue forecasting is an essential part of any business’ financial plan. To create a successful revenue forecasting model, you need to know what factors impact your business, what drives sales, and how these factors are likely to change over time.

If you don’t have a system in place for tracking your sales data and insights, you may also need to adopt one. Tools like Revenue Grid provide sales data, revenue insights, and risk assessment that help you keep track of what’s changing in your sales pipeline and where you can maximize your revenue.


Revenue Grid also allows you to use data and insights from sales forecasting to coach your team. Think about advising your team on what kind of content they should produce next, the best time to send a sales pitch to a prospect, or what deals have the highest possibility of being closed. In doing so, you can help your sales reps become more confident in their work and boost their sales productivity.


Perform your bottom-up forecasting with Revenue Grid

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    How to perform bottom-up forecasting with Revenue Grid – 4 simple steps

    1. Submit accurate forecasts across your sales team with sales forecasting cadences:


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    4. Guide your team at each stage of bottom-up sales forecasting process with Revenue Signals


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      Core UX Writer at

      Lavender Nguyen is a Freelance Content Writer focusing on writing well-researched, data-driven content for B2B commerce, retail, marketing, and SaaS companies. Also known as an Email Marketing Specialist, she helps ecommerce B2C brands develop high-converting, customer-focused email strategies.