Sales forecasting is the process of estimating future sales.
Accurate sales forecasts enable companies to make informed business decisions and predict short-term and long-term performance. Companies can base their predictions on past sales data, industry-wide comparisons, and economic trends.
It is the act of matching opportunities with marketing efforts.
Importance of Sales Forecasting
- Reduces uncertainty
- Improves stock management
- Evaluation of past, current, and future sales
- Helps to identify and rectify minor issues before they escalate
- Improved planning of growth
- Determine the expected ROI
How to Forecast Your Company’s Sales?
There are various methods to do Sales Forecasting, namely: Time Series Analysis, SalesForce Opinion, Test Marketing Results, Market Factor Analysis, Consumers Buying Plan, etc.
In this blog, let us understand Time Series Analysis, one of the widely recognized methods of Sales Forecasting.
Time Series primarily helps the business to target upcoming sales, maintain stock data, and track the share price in the market.
With Time Series, companies can look back at the dates to detect patterns and insights to understand and compare how business was faring. This study mostly partakes during budgeting and financial analysis.
By plotting the total sales of business against particular days/weeks/months helps to get a trend line, and presents significant insights from it.
Usually, organizations sell different products to different types of customers in different regions through various channels which helps to breakdown total sales by subgroup to analyze which product is doing better at which place and also aids to know where enhancement is needed.
If needed, we can further simplify the same into many subgroups (explained below) based on the nature of business.
- Sales by Product
- Sales by Region
- Sales by Customer
- Sales by Channel
Sales by Product
This understanding gives a perspective of during which growth stage (such as Introductory, Growth, Maturity, or Decline) can the product can be unveiled. Multiple factors, like targeted place and buyers, market scenario and pricing, also play crucial roles during the forecast.
Sales by Region
Understanding which regions contribute to a high number of sales, and which don’t. Having this data helps companies to focus and come up with new strategies or tweak the product to suit the customers in regions where the product is not doing well as anticipated. Also, more stocks can be duly sent to warehouses where purchases are more.
Sales by Customer
Customers can be segmented into groups based on their purchase behavior. With the segmentation, it would be comfortable for companies to identify the pattern of sales, and also know which type of customers are contributing to the revenue.
This way, the brand can come up with attractive offers to idle target customers. Such specific offers might rekindle shoppers again.
Sales by Channel
These days sales can happen from anywhere — online stores, brick and mortar stores, social media channels, etc. Analyze what channel is bringing more orders for you, and understand the current trend market is leaning onto.
The Math Behind Sales Forecasting
Build your best sales forecasting model.
There is a lot of MATH behind Sales Forecasting. Time series analysis involves a series of steps like smoothing the data, stripping the global trends, and tuning the white noise.
Fit the model to get the forecast value, and then tune the model based on the accuracy.
Components in Time Series
In any sales graph, there are usually three components.
- Trend (Tt)
- Seasonality (St)
- Noise (Rt)
There are three types of trends, namely, Upward Trend, Downward Trend, and Sideway Horizontal Trend. Upward Trend is where the sales numbers are in growth rate, and this is also known as the bull in the stock market.
Downward Trend is where the sales numbers are on a fall. This is quoted as Bearish in the stock market. If sales are in tradeoff position, it implies the undergoing Trend is Sideway Horizontal. There will be no significant change, and the growth rate stands still.
Seasonality denotes periodic fluctuations in specific business areas that occur regularly based on a particular season. Seasons can be referred to as calendar seasons such as summer, winter, fall, and commercial season also such as the holiday season is included in this list.
Seasons significantly impact businesses, and henceforth it is a must to take note of the seasonal changes to predict future sales numbers.
Noise is a general fluctuation which happens in business sometimes without much of any definite reason. It may be due to economic, social, political, emotional, or any other external factors, which in turn affect the business.
If the same graduates over a while, then companies can derive a chance of gathering some insights based on Noise, and do the sales forecast.
Concepts of Time Series
Time Series Analysis works on two major concepts such as:
- Multiplicative model
- Additive model
When the magnitude of the seasonal pattern in the data increases as the data values increase and decreases as the data values decrease — Multiplicative Model may be a better choice.
Xt = Tt * St * Rt
An easy way to transform a multiplicative model to an additive model is to carry out the analysis on the log of the values in the time series.
Log(Xt) = Log(Tt) + Log(St) + Log(Rt)
When the magnitude of the seasonal pattern in the data does not directly correlate with the value of the series — Additive Model can be chosen.
Xt = Tt +St +Rt
Process of Time Series
- Smoothing the graph (Exponential Smoothing, Moving Average, Auto-Regressive, ARMA, etc.)
- Finding the Trend and Seasonality (Holt-Winters Model)
- Finding the Stationary and its trend
- Analyze the stationary (Noise) — Methods (Run Test, Rank Test, Difference sign Test, Turning point test, etc.)
- Build the model for prediction
At a glance, the below graph may look simpler. But when you look deeper into, it unravels a multitude of stories (upward trend, prediction of sales, etc.) about the future of a company which can be ascertained with Sales Forecasting.
Foreseeing products performance is a sure shot way to plan things safe and utilize the current scenario to elevate product sales. Productimize, the enterprise customization solution, is inbuilt with Time Series Forecasting Model which helps businesses to prepare for the future and to keep a current tab of how customized products are faring in the market.
Apart from Sales Forecasting, brands can also monitor the brand’s custom products with Productimize’s rich dashboard and analytics.
Get in touch with us, and forecast your company’s fortune, all by yourself.