8 Proven Sales Forecasting Methods That’ll Get You Closer to Your Sales Targets

It’s the end of the month (or quarter, or year). You’re at the drawing board, chalking out your sales strategies for the next check-in. And you ask the big questions. What should our pipeline goal be for the next quarter? How many leads does each rep need to bring in to hit our revenue targets? What impact will the new feature launch have on our revenue? You’d never be able to answer them without sales forecasting.

What does sales forecasting mean?
Why is sales forecasting important?
Factors that impact sales forecasting
8 proven sales forecasting methods
Conclusion

The future is uncertain. The market is unpredictable. But sales forecasting methods help you benchmark and prepare your resources, and set you up for growth and success. Are they a 100% accurate? No. But should you be making business decisions without them? That’s a bigger no. So before we head into breaking down sales forecasting methods and how they should define your strategies, let’s cover the basics.

1. What does sales forecasting mean?

Sales forecasting is the process of estimating future sales performance based on past sales, market conditions and other relevant factors. A variety of sales forecasting methods can be used to make projections that help you understand the current state of your business, provide insights into potential strategies for growth and success, and plan for upcoming sales goals. It is an invaluable tool for businesses in making informed decisions about their operations.

Whatever the sales forecasting method a business ends up using, there’s one thing no one can do without. Data. You can make forecasts for a rep, a squad or the whole sales team. But you can’t do it without data. Sales forecasting methods account for historic sales data of the business and the team, market conditions, analyst predictions and more. Sales teams often leverage tech that present advanced analytics in a single, accessible dashboard for their sales data.

2. Why is sales forecasting important?

Sales forecasting is a critical tool for any business that wants to stay competitive and profitable in their market - no matter what upheavals it sees. Accurately predicting your future sales allows you to make informed decisions about product development and production, manage your inventory, decide on your sales, marketing and general tech investments, staffing levels and more. It helps you plan for the future by providing visibility into what revenue will look like down the road. In a nutshell, it’s the closest thing you’ve got to a crystal ball. There are a lot of sales KPIs and metrics you can and should track (here are some of them). Based on the different sales forecasting methods, you’ll leverage them in some capacity to make your projections.

3. Factors that impact sales forecasting

Like we said, sales forecasting isn’t an exact science but a necessary one. Here are some things you need to keep in mind as you start.

1. Economic, legislative, and policy changes - This is an obvious one. External uncontrollable factors like these will directly impact your forecasts and there’s not much you can do about them. But you need to revisit and amend your forecasts to account for any changes.

2. Business maturity - The sales forecasting method you choose will rely on the size of your business (if you’re new, you won’t have historical data), the frequency of your tracking and the accuracy of the data you store.

3. Product roadmap - The features you roll out will obviously impact the desirability of your product. Hence your product roadmap will have a direct impact on your sales predictions and sales forecasting process.

8 sales forecasting methods that’ll help you hit your sales goals

1. Length of Sales Cycle Forecasting Method

The Length of Sales Cycle method is one of the most reliable sales forecasting methods around. It is a sales forecasting technique that takes into account the duration of sales cycles, or the amount of time it takes for a customer to make a purchasing decision after being contacted by your sales rep. Since this depends on historical customer and sales data, it is likely to be more accurate than your rep using just their objectivity. This does rely on your reps inputting their data religiously and for your sales stack to be seamlessly integrated with each other.

Example	If your average sales cycle is 6 months and your rep has been in conversation with their contact for 3 months, there’s a 50% probability of deal closure.
Pros	Objective and more accurate than relying on a rep's gut. Can account for sales cycles of different lead sources (cold outreach leads will have different cycles than a referral lead and so on).
Cons	Data has to be logged religiously. All sales tools have to sync to ensure accuracy. And if doesn’t happen, your reps have a lot of manual entry to do.

2. Lead-Value Forecasting Method

The Lead-Value method is another one of those sales forecasting methods that is a great starting point if you have the right historical data. This method involves analyzing your lead sources, assigning a value to them and predicting your revenue-generation potential from there. You’ll need to make sure that you have data on your average sale price and conversion rates for each data source.

Example	If you leads from demo request form-fills spend about $1000 dollars on your offering, and they convert at the rate of 5%, their lead value would be $1000 * 5% = $200 per lead. So now you can work backwards from your sales revenue target to figure out how many leads your sales team needs to generate.
Pros	If you have the historical data to back it, this is a great way to get a pretty accurate forecast.
Cons	Conversion rates can change if your marketing strategies do (in response to any change in current trends). It’s important to account for these changes as soon as possible in the forecast. Sometimes it isn’t easy to identify a lead source. When this happens, a new “other” bucket has to be created.

3. Opportunity Stage Forecasting Method

The opportunity stage sales forecasting method that takes into account the stage in which the deal is. You pick a reporting period, assign a probability value for conversion at each stage, multiply that value by the deal size and get your prediction. For illustrative purposes, let’s try this -

Example	If your rep is working on a deal worth $1000 and the decision-maker just got brought it, at an assigned conversion rate of 35%, your forecasted deal amount is $350 dollars.
Pros	It’s easy and predictable to establish a forecast using this method if you have properly analyzed historical data.
Cons	It’s highly dependent on the accuracy of your data. Incorrect data = predictions that are way off. It doesn’t take into account the age of your deals.

4. Intuitive Forecasting Method

This is one of those sales forecasting methods that work best for a newly incepted business that doesn’t have historical data to track back to. Just as the name suggests, the Intuitive Forecasting method relies on the instinct of each rep working on their deal. Your reps are in regular (frequent, even) contact with the lead and are likely to be able to assess where they’re headed and how fast. However, the subjectivity of this method is also detrimental as it doesn’t account for a rep’s potential (and understandable) over-optimism.

Example	Each rep just provides a dollar estimate of the deal value they’re likely to close by the end of the reporting period based on their efforts and current statuses.
Pros	Based off of inputs from those closest to the deals, accounts and contacts The best solution in the absence of historic data
Cons	Deeply subjective, which might or might not be accurate. Research says that removing human bias actually drives up forecasting accuracy by 76%. Cannot be scaled or standardized

5. Historical Forecasting

This method is a simple one. It just takes the sales data of a prior reporting period and assumes consistency, along with a predictable growth rate to arrive at a forecast. This is a simple, yet extremely static method that doesn’t take into account the internal and external variables of a sales and business cycle.

Example	Let’s say your monthly recurring revenue last month was $45,000. Your current month’s forecast would be $45,000 + your average annual growth rate, let's say 15%. Which would bring your current month’s forecast to $51,750
Pros	It’s easy to calculate If your industry observers predictable growth and trends, this will be super accurate
Cons	Doesn’t work for all industry-types as it doesn’t take into account demand or seasonal changes

6. Test-Market Analysis Forecasting

This method involves rolling out a new service, product or feature to a test user-base first, before a wide public release. The result of the test market roll-out (this could be a specific demographic like a geography or specific feature users) can then be used to make accurate predictions about a full launch.

Example	Say you divide your test market into two. You release your product or feature to one post a series or ad campaigns, and to the other without advertisement. The sales gap helps you draw inferences that you can factor into your launch.
Pros	It helps you course correct after observing a smaller cohort, and is likely to help you final launch get more successful
Cons	This is heavy on investment - both time and cost. This is suitable for big businesses with multiple launches to roll-out. It might not consider the variables between every demographic.

7. Time Series Forecasting

This sales forecasting technique leverages years and years of product data to establish patterns and trends, and use those as the basis of your forecasts. In this method, you gather data for your product or service line, draw parallels between timelines and trends, calculate change-rates and apply those to make forecasts.

Example	Let’s say you sell winter clothing. On studying your sales data every year, you notice a 45% increase in sales during fall and an 85% increase in sales during winter proper. These are the numbers you’ll in making your projections,
Pros	For businesses that experience a static product and demand life-cycle, this is a great tried and tested method
Cons	This won’t work for businesses without far-reaching historic data. This isn’t applicable to business lines that experience high volatility and no definable trends

8. Multivariable Analysis Forecasting

This one is the most complex of them all. It incorporates the approach and data sets of many of the sales forecasting techniques we listed above. It accounts for everything from opportunity stage to individual rep performance to provide you what is likely to be the most accurate forecast.

Example	Let’s say rep A and B are working on an account. The first rep has made contact for a deal worth $5000. At a rate of 15% (as assigned by our Opportunity Stage method), your forecasted amount is $750. Rep B a proposal of a deal worth $1,000 and has a 20% chance of closing the deal based on how long they’ve been working on it, your forecast amount is $500.Which brings your total for this account to $1250.
Pros	Accounts for all sales variables and hences presents the most accurate forecast of all methods
Cons	Because of the sheer volume and complexity of data, you’ll need to invest in a tool to be able to arrive at accurate forecasts. That will not come cheap. Likely to be unsuitable for smaller businesses

Conclusion

No matter what method you pick, remember that the integrity of your data means everything. Find a candance to make sure that your reps are on top of updating everything they need to (AND everywhere they need to). You should also make sure that if that involves a lot of manual entry, that’s something you should think about changing. Outplay offers out of the box integrations for a whole marketplace of sales tech - including the widest host of CRMs - to make sure that data flows from one place to another without your reps having to do it manually. You should give it a shot. It’s free.