# How to interpolate in 4 steps (with definition and benefits)

By Indeed Editorial Team

Published 14 November 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Interpolation is a method of estimating a missing value between two known values. Businesses use it to fill in gaps between data points or to predict the future based on past data and trends. Learning about interpolation can help improve how you collect and work with data. In this article, we explain what interpolation is, outline how to interpolate in four steps, look at when businesses use this statistical process and list its benefits.

## What is interpolation?

Interpolation is a statistical process that uses known points within a given dataset to estimate the values between those points. This is helpful when trying to extrapolate information from incomplete data. Businesses use interpolation in situations where they want to estimate the value of something that isn't directly available. For example, if an employee is trying to determine how many people live in an area, they may use interpolation to create a map of the estimated population density based on known values from census data.

This statistical process is also useful when you want to make predictions about what may happen in certain circumstances. For example, if you have a spreadsheet that tracks your monthly sales and want to know what happens if you increase prices by 5%, interpolation allows you to fill in the blank spaces with predictions based on what happened when you increased prices by 5% last year.

Related: How to create a sales forecast: step-by-step instructions

## How to interpolate

Here's how to interpolate in four steps:

### 1. Consider your current data

The way you represent your data when interpolating determines what kind of function you use to produce the interpolated value. With this in mind, it's crucial to consider your current data and determine how you want to represent it. For example, if you represent your data as a graph and you want to interpolate between two points on that graph, you can use linear interpolation to find an estimate for the value at any point between them.

In contrast, if you represent your data as an image and you want to interpolate between two pixels, you can use bicubic interpolation to find an estimate for the value at any pixel between those two pixels.

Related: What is numerical data? (Types, characteristics and uses)

### 2. Determine the available range of values

The next step involves determining the range of values that are available at each point along your dataset. Doing so allows you to choose an appropriate interpolation method. If there's a large range of values available at each point, choose an interpolation method that takes advantage of this variation. For example, if there are many values close together, then take the average. Conversely, if there are no values close together or if they're widely dispersed, taking an average may not be as optimal. This means that it's advisable to look for another interpolation method.

### 3. Select an appropriate interpolation method

Next, select an interpolation method that's suitable for your situation and input to gain reliable results. For example, if you're trying to interpolate data points from two different datasets with various dimensions, like one dataset with three dimensions and another with four, using a linear interpolation method might not be ideal. The reason for this is that linear interpolation assumes there are no gaps in the data, so it may produce unreliable results in this instance.

### 4. Convert your input data into a compatible format

Finally, it's crucial to convert your input data into a format that's compatible with the program you're using. For instance, when you use spreadsheet software, convert your input data into a format the program can understand and then use that format to compute your output data. This allows your computer to process more information at a faster rate than if you didn't convert it into a compatible format.

Related: What is data mapping, and why is it important to business?

## When to use interpolation

Interpolation is a good tool to use when you want to take an idea and break it down into smaller steps. This can be helpful in the workplace when you have a new project that involves a lot of people working together or if you want to encourage everyone involved in a project to work towards the same goal.

Interpolation allows you to identify what your end goal is, which helps you determine how to reach it. It's also useful for making sure everyone involved in a project has their own input, so they feel more invested in the whole process.

Related: What are business goals and how to create them (with steps)

## Interpolation benefits

Here are some of the main benefits of interpolation for businesses:

### Estimate future trends more accurately

Interpolation allows businesses to gain more accurate estimates of future trends because it helps them to use past data to account for data gaps. For example, if a company is trying to find out whether there might be an increase in sales over the next five years, but they only have one year's worth of relevant data, they may use interpolation to estimate the other four years of sales. Then, they can compare this number with the actual sales figures from the first year to get a better idea of how much money they may make.

Related: What are the technology trends shaping businesses today?

### Make better decisions

Additionally, interpolation allows businesses to make better decisions because it enables them to predict how customers may respond to new products. This is crucial as it can prevent companies from wasting money on products that don't sell well. For example, if a company wants to release a new line of skincare products, they may want to ensure they're making the right decisions about what to include in this product line.

In this scenario, interpolation is useful as it allows them to test different kinds of products to see how customers react. If the company then gains positive reactions from customers, they can use this information to confirm a certain product's place within the line.

Related: What is strategic decision-making? (With examples)

### Use resources more efficiently

Another key benefit of interpolation is that businesses can use it to improve how they manage their resources. It allows them to use fewer resources and also enables them to make more accurate predictions about future events.

For example, if a company wants to know how many customers it may have in six months, it can take its current number of customers and add it to an exponential curve until it reaches the desired number. This allows them to accurately predict how many customers they may have to start preparing their warehouses and production lines to meet this demand.

Related: How to calculate work efficiency and why it matters

### Develop stronger customer relationships

Interpolation can also help businesses build stronger relationships with their customers. For example, if a business wants to reach out to customers and make them aware of an upcoming promotion, it can use interpolation to do this. Interpolation makes it possible for businesses to reach the right people at the correct time, allowing them to target their outreach efforts more effectively. This involves building a database of customer information and using that data to create personalised messages to send to customers via emails or text messages. By doing this, businesses can potentially gain additional purchases and profits.

Related: How to build client relationships with these top tips

### Increase customer loyalty

Businesses may also use interpolation to help increase customer loyalty. They may do this by estimating the amount of money that customers are likely to spend during a given period and offering them discounts or incentives based on these estimates.

For example, if a company knows that its customers tend to buy shoes from its online store around the same time every year, it may offer them 20% off all shoes if they buy before 31st December. By doing this, the business can increase its sales while encouraging its customers to spend more money with them throughout the year rather than during one specific period.

Disclaimer: The model shown is for illustration purposes only, and may require additional formatting to meet accepted standards.