Sales forecasting: A Smart Methodology Reimagining

What is sales forecasting?

A sales forecasting is the process of predicting sales over a defined timeframe (month or year) in the future by estimating sales and marketing efforts and a calculated predication of the revenue in future.

Sales prediction (or forecasting) is the culmination of all the efforts made by an organization. You research the market, define your product requirement, design, develop, test, and put the product out to the market for selling, and that is when your efforts start bearing fruits.

Elements of Sales Forecasting:

  • Predict sales revenue: Sales revenue is the major component of the company revenue. Sales forecasting gives you an estimate of this component.
  • Estimate marketing efforts: Sales forecast gives you an estimate of how much a product or service will sell. This gives you an estimate of which product or service you need to focus your marketing efforts on.
  • Diagnose product issues: Sales forecast can show whether the demand for a product or service is stable, increasing, or decreasing. Basis this prediction, product issues can be diagnosed and early intervention can resolve product/ market fit failures.
  • Plan product launches or releases: Sometimes the market is not ready for a product and at other times you could be too late to launch a product if your competitor launches a similar offering. Sales forecast helps you in determining the right time to launch a product.
  • Streamline operations: Much before you launch a product, you need to decide how much raw material to procure, assembly lines, licenses, etc. Sales forecast gives you an early insight into the numbers you need to produce.
  • Streamline hiring: Sales forecasts are good indicators to plan for expanding dedicated account managers & customer support teams. In addition, the deployment of additional technical capacity required to support these clients can also be planned.

Traditional techniques of Sales Forecasting:

There are various ways in which sales forecasting can be done. The most commonly used approaches for sales forecasting are listed below:

1. Intuition based sales forecasting

This is one of the most valuable methods for sales forecasting for a newly formed sales team with no access to historical data. In this approach, the sales representatives, estimate the probability of closure and value of a deal in the future. This estimation forms the basis of the sales forecast. For this approach to succeed, skilled sales representatives with a high level of sales intuition are required.

2. Sales cycle length based forecasting

This method helps in creating a sales forecast basis how long a deal has been in the pipeline. For example, if it takes 3 months to close a deal on average and a 10000 USD deal has been in the pipeline for 1 month, there is a 33% probability of its closure and its value will be forecasted as 3300 USD. Further analysis of the correlation between the length of the sales cycle and the win-loss status can provide critical feedback on the efficacy of a specific channel in sales. For example, leads earned through inbound and referral marketing programs may have a shorter sales cycle length than outbound reach outs.

This approach in forecasting isn’t always accurate as it does not take into account the sales cycle stage in which the deal is. A deal that has been in the sales pitch stage for 2 months will be valued the same as a deal that has been in the purchase order placed stage for 2 months.

3. Sales cycle stage based forecasting

This approach takes into account the stage in which the deal is in, to account for its probability of closure. For example, the stages could be defined as:

Sale cycle stage

Probability of successful closure

Cold/warm call or email


Sales pitch call


Solution Demo




Purchase Order placed


Purchase Order payment realized


If a 10000 USD deal is in the solution demo stage, its value will be 40% x 10000 = 4000 USD. If a 5000 USD deal is in the purchase order places stage, its value will be forecasted as 90% x 5000 = 4500 USD. This approach does not take into account how long has the deal been in a particular sales cycle stage. For example, a 1000 USD deal in the Solution Demo stage that has been will be valued the same as 400 USD in the Purchase Order payment realized stage. Thus, this method of sales forecasting does not take into account whether the deal has turned cold.

4. Historical data-based sales forecasting

If you have sales data from the past couple of years, you could very well use the same to create your sales forecast. For example, if your sales for last October were 10 million USD, your sales forecast for this October could be the same multiplied by your growth factor. If your growth is 10%, your sales for October could be forecasted as 11 million USD. However, this approach does not factor in other macro-economic factors and other changes that could have occurred over the said time.

5. Pipeline based sales forecasting

Pipeline-based forecasting is a more advanced approach for creating sales forecasts. This approach takes into account multiple variables to create the forecast such as the sales cycle stage, weights for different stages, time to close the deal, deal size, win rate, etc. This forecasting is done using CRM (Customer Relationship Management) tools. CRMs act as the hub for all the information related to all the deals and use this data to create sales forecasts. The accuracy is quite high but such analysis is not available cheap and is highly dependent on accurate & timely data entry by sales reps.

Are there any tangible gaps?

The answer is yes.

A. Distorted incentives to have accurate sales forecasts:

While there are well-intentioned processes set up to ensure that sales reps update data on CRM, it may not be religiously followed. This is because of distorted incentives. With the pressure of hitting quotas, sales reps would prefer spending more time on actual customer reach-outs than manual data entry.

B. The lack of actionable insights from sales forecasts:

The common problem across most sales forecasts is that they don’t really nudge you to take any concrete action. So, a sales leader is almost hitting in the dark if he/she finds that sales forecasts are way off the mark from that month’s quotas.

The new-age technique of sales forecasting

With a multitude of smart remote sales tools coming into the market, there is great potential in addressing the prior gaps highlighted in sales forecasting. Take the example of video meetings replacing physical meetings as the norm in B2B SaaS sales processes. In a smart video meeting tool like, data around lead qualification, objections raised by the customer throughout the pitch, customer interest, and dates of next follow-up meetings are automatically captured and updated in CRM. Now, analysis of these data points throws up tangible risk factors that can derail deals. In turn, they also indicate what can be done to course correct.

For example- The absence of C-level decision-makers in critical meetings substantially reduces the probability of successful closure in a certain sales cycle. The sales rep may take the word of the attendees involved and be optimistic about deal closure but he/she needs to be proactively reminded of the risks in that optimism. A lagging correlation of data around the presence of C-level attendees in meetings (from meeting tools) and win-loss ratios (from CRM) over a period of time can be good leading indicators of success in future deals.

It’s time to reimagine the way sales forecast is done and stop second guessing!

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