The complexities of building and developing a business mean that managers reach out for any tool that will help them be successful. Sales forecasting models are a key tool in helping sales managers and senior executives navigate their way around their sales territories, their markets, and their opportunities so that they can guide their business to greater success.
Let’s explore some simple sales forecasting models and tools that will help you manage your business and achieve your objectives.
- What are Sales Forecasts?
- What Factors will Impact a Sales Forecast?
- A Methodology for Sales Forecasting
- What's the Best Way to Create Accurate Sales Forecasts?
- How to Implement a Sales Forecasting Model
What Are Sales Forecasts?
A sales forecast is an analysis of what sales revenues a business will generate over a quarter, a year, or a longer period, for up to five years. Depending on the time horizon, it can be created by an account manager, detailing the deals that will close over the coming month or quarter. This’ll be a compiled listing of fully qualified opportunities that’ll close, as well as those opportunities that might close in certain circumstances – known as upside.
Sales forecasts covering longer time periods – up to five years – are typically the responsibility of the marketing function as well as senior sales management. The longer-term forecasting models utilize industry and market data insights to provide actionable analysis that can build a business case for investment in sales and marketing activities, which can drive sales revenues in the longer term.
What Factors Will Impact a Sales Forecast?
Before we go into the detail of sales forecasting models, let's look at some factors that will impact a company's sales forecasts. What factors will influence whether your sales go up or go down or remain broadly constant?
1. Product Launches and Upgrades
The most significant single influence you have over your sales forecasts is your company’s ability to launch new products or upgrade existing ones. Launching new products that meet the needs of your target audience should increase your revenues. Upgrades and updates to your existing product set should also maintain, if not increase, your revenues and the forecasts of your sales team in the short- and medium-term.
2. Competitor Activities
Like you, your competitors won’t be idle, and they’ll launch or upgrade their products and services too. These developments may make them more competitive, which could impact your competitive strengths and affect your pricing power. Equally, market disruptors – that offer similar services to yours but potentially use new platforms – can emerge swiftly to provide you with a competitive threat that can destabilize your business if you’re not properly prepared. If nothing else, these developments can cause your existing customers to reassess your value and possibly slow their business decisions.
3. The Economic Environment
The overall macroeconomic situation can also have a significant impact on your business. A booming economy will stimulate many sectors, drive more demand, and drive investment in new products and services, both for you and your competitors. It may also increase the number of new entrants in your market.
Equally, a slowing economy will reduce overall demand, but it may be an opportunity for organizations that can take advantage of situations where there are fewer players in the market and who can offer a compelling value-based proposition.
4. Changes in the Market
While these boom-and-bust cycles may come every 5–10 years, other macro-issues can take many more years to come to fruition. The classic example is population changes, which often take 20 years to impact the economy, but which drive waves of change in demand and consumption patterns for the next 50 years. These changes can drive demand for homes, leisure opportunities, or competition for jobs, for example. Climate change is a similar long-term driver for developments across vast swathes of economies worldwide. It will change consumer buying habits, drive new infrastructure projects, as well as the need for new and diverse types of insurance products, to name a few examples.
5. Changes in the Industry
Another driver for a changing sales forecast is developments in how industries operate, whether driven by technology innovation, widely accepted working practices, or the impact of legal changes. Most recently, the widespread adoption of remote working has created challenges for businesses in city centers around the world. But equally, it has been a boon for suburban venues and other retail outlets near to people’s homes. Virtual meeting businesses have benefited from this situation too. Companies offering shared working venues will thrive as a result in the future from these developments as well.
6. Legislative Changes
Changes in the law can also significantly impact long-term buying patterns. New environmental laws can change the business case for wind power or coal extraction overnight, for example. Laws that mandate changes in working practices for employees can create opportunities for manufacturers of safety equipment or office equipment, for example. Regulatory changes can affect the kind of products that are needed in financial services or the type of pharmaceutical products that can be sold over-the-counter. Legal changes can be few and far between, but the changes they mandate can be significant.
7. Seasonality
The changing seasons also have an impact on a sales forecast. Ice creams and garden furniture sell better in summer than winter, but a poor summer may result in slower sales for both compared with a scorching one. Equally, turkey sales peak in November and December, compared with other months.
A Methodology for Sales Forecasting
There’s a range of techniques you can use to produce a sales forecast. The level of accuracy will decline the further you look out. Sales forecasts for next month are likely to be more accurate than those for sales in 18 months.
Sales forecasts for the next quarter will be the responsibility of sales reps. These will be a listing of deals that will close as well as some upside deals. For longer-term sales forecasts, the practical approach may be to utilize several forecasting techniques simultaneously to generate a rounded view of the opportunity potentially open to your business.
1. Sales Rep Forecasts
In B2B sales, the classic sales forecasting approach uses the sales pipeline forecast that sales reps provide to their managers weekly or monthly. A forecast from a sales rep is their commitment to the business for revenue they’ll close that week, month, or quarter. It’s a key information source in helping senior managers make key business decisions.
For longer-term forecasting, their value lies in highlighting those businesses that comprise your “sweet spot” – those which are most likely to buy from you – whether it be by size, by geography, or by segment, for example. It shows you what your likely revenue floor is and also gives you pointers for areas where you can grow your business in your next phase of growth. There is even value in understanding those situations where you lost opportunities. They can highlight areas where you might not renew your sales and marketing efforts or where you should re-package your offering to meet the specific needs of the types of prospects that chose not to work with you.
2. Leveraging Historical Data Points
Another way to predict future sales is to use historical data to understand the market dynamics that will shape your business’ revenue stream. For example, like-for-like sales for the previous 12 months will be a good guide for some products such as ice cream or garden furniture. What happened last year will be repeated this year, with some variation caused by changing weather patterns or economic changes. With a sufficient array of data, it’s possible to understand the dynamics of a market, for example, its growth rate, typical margin levels, or the market size. These can help you better understand the trends and dynamics that might influence the future success of your product or service.
3. Forecasting of Pipelines
We’ve already discussed sales rep forecasts, which can be used to assess revenue potential over the coming months and provide valuable insights about areas for business development.
However, a sales pipeline isn’t the only “pipeline” a business will have access to. The marketing team will have its own pipeline of leads, contacts, and prospects who’ll potentially buy from your company over the next 12–18 months. Again, this’ll provide insight into those segments and geographies that can offer you the best scope for future growth.
From a management perspective, analyzing current and historical pipelines can give you a sense of what size and composition of pipeline you need to meet your growth targets.
4. Forecasting of Leads
The level of leads generated by the business can also be a valuable proxy for forecasting future revenues. Again, you’ll know how many leads it took to generate this year's revenue, so you can extrapolate what your current lead generation model is providing to assess your future revenue levels. Hopefully, an uptick in leads today will generate a proportionate increase in revenues further down the line.
But be careful. Lead generation campaigns evolve, and lead quality can change for many reasons. Different lead generation models can create different lead quantities but drive similar revenues.
5. Multivariate Analysis in a Custom Forecast Model
In complex markets, with potentially millions of buyers and with many different variables involved, a business case for launching a product into this market may use a complex, multivariate model to create the insights you need to make your management decisions. These models capture an array of complex data sets and utilize complex regression analytic techniques that can generate valuable insights about potential revenue levels, drivers, and sources.
This can be practical if a business has the time and skills to develop this expertise, using data scientists to create the results it needs. Sadly, historically, the reality is that very often, companies outside of large multi-national corporates don’t have access to that level of knowledge, expertise, or resource.
6. Predictive Intuition
For all the talk of big data analytics and multivariate analysis, there’s always room in forecasting models for using old-fashioned and hard-won commercial experience. There are situations where “gut feel” can be a useful guide for estimating growth. The ideal situation will be in a small market with a limited number of buyers and suppliers. Players in this market will be familiar with the drivers, dynamics, and trends they’re all exposed to, and managers can predict the future growth rates with a satisfactory level of confidence.
However you approach your sales forecasting, applying a “gut check” to review the results created by other forecasting techniques is entirely reasonable. These models aren’t perfect, and an experienced eye can apply an extra level of confidence to the results.
7. Forecasting Based on Marketing Testing
Test marketing can be a good indicator for potential revenue opportunity, especially where this is combined with market research analytics. Market testing can help to predict future revenues, as well as provide real-world feedback on a product or service. A combination of qualitative and quantitative insights has the potential to create sophisticated and compelling forecasting models.
That said, not all companies have products that lend themselves to this type of research, but it does offer the potential for companies looking to sell into the consumer market primarily.
What's the Best Way to Create Accurate Sales Forecasts?
So, you want to be more successful, and you think this approach may help you. What steps should you take to implement a forecasting model that’ll help you beat your competition?
1. Define Your Sales Process
There's no one-size-fits-all sales forecasting model that will work for all businesses – you’ll need to create one that’s right for you. The best place to start is to define your sales process, which should reference how your customers make their buying decisions. Defining this will give you very solid foundations for an effective sales forecasting model.
The elements involved in your buying process might include:
Customer Buying Behavior
This can cover how they research purchases, what research sources they typically use, and whether their decision-making processes are ad hoc or highly formalized.
Lead Generation and Prospecting
This addresses questions such as how many leads do you need in a funnel to close a deal, and what is the average length of your sales cycle?
Qualification
This looks at how much time and effort are needed to qualify a prospect and all those involved in the decision-making. Is it minutes, days, weeks, or months?
Proposals
This will look at what steps are needed to put forward a proposal. Will it be a simple presentation, or will a more complex proof of concept be required? Can proposals be standardized, or do they need to be tailor-made for every engagement?
The Close
Is closing a transaction straightforward, or does it require extensive negotiation of the specifications and terms?
2. Define Your Key Sales Metrics
With a solid understanding of your sales process, you can select the metrics that will help you form your forecast model using various data sources.
Based on historical data, these revenue intelligence metrics can cover, for example, the number of leads needed to generate a defined revenue level, your lead-to-opportunity to conversion rates, your average deal size, and the duration of an average sales cycle. The list is endless, but these metrics will be unique to your business and offer the potential for unparalleled insight into your business, your market, and your prospects.
3. Consolidate Your Data
With your metrics and sales process defined, you’re now positioned to capture a range of data that’ll help you determine your forecasting model.
Information about who your customers are – how they buy, which personas are involved in the decision-making, where your growth hotspots are located, and much, much more – are available. This information will reside in a host of internal sales, marketing, and finance systems. External data sets can give you the insight you can use to successfully build a forecast model that can take your business to the next level.
Bringing all this data into a unified data platform will help you apply a host of analytics capabilities that can yield valuable insights. AI capabilities can help do much of the heavy lifting, with graphical tools helping you make sense of large volumes of highly diverse data sets. It also helps to make sharing information and insights with your peers far easier.
4. Define Your Forecasting Model
Now combine your sales process, our metrics, and your data to build your forecast model. It’ll help you understand what your sales opportunity will be over the next 6 –24 months, how long the sales cycle will be, and how much effort you’ll need from a sales and marketing perspective to realize this plan. It’ll help you define your investment and shape your quota and sales territory plan and your sales incentive plans.
As we've already touched on, your final “model” may well be an amalgam of models, both formal and informal. The key is to have a model your feel comfortable with and whose results you can justify.
5. Review the Results
With the results in your hands, the next step will be to share them with a broader audience. A sales forecast isn’t the sole preserve of the sales team or even the marketing function. Plenty of other people in the business will want to review a sales forecast and see how it will affect them. If your forecast suggests you’ll be able to deliver thousands of units, but you only have the capacity to produce or deliver a fraction of that, then the conversation needs to pivot towards investing in additional capacity. Equally, reviewing your results will help you judge whether you have sufficient sales capacity and skills to meet the challenge.
6. Integrate the Results into Your Sales Management Process
A sophisticated sales forecast model allows you to develop your sales operation more fully so you can use the insight to develop your business further. It helps you focus on the right salespeople, the right territories, and the right products and messages to deliver the results you seek. Use better long-term forecasts to drive better short-term sales forecasts, featuring larger deal sizes and shorter sales cycles.
7. Check Your Forecast Models Against Reality Regularly
Sales forecast models aren’t predictions. They’re designed to help you better understand your business, market, and customers.
Review your real-world results alongside the forecast results to see where the differences emerge and what might be driving them.
How to Implement a Sales Forecasting Model
This scale and depth of analysis were once only within reach of large corporates with huge budgets, extensive IT departments, and many data analysts.
However, cloud computing, AI, and big data capabilities have reduced the price point of comprehensive forecasting significantly, to the point where sales and marketing teams can now deliver this capability using their current levels of expertise and headcount.
The first step is to adopt a centralized data platform that can quickly, easily, and seamlessly capture data from a range of environments. Data analytics tools can use AI capabilities to develop insights and themes that can start to build the sales forecast picture.
Graphical capabilities allow sales managers and marketing managers to understand these themes and analyze them in greater detail.
These capabilities also lend themselves to developing sales territories that meet the needs of your business forecasts. Meanwhile, your sales incentives plans will guide, direct, and motivate a sales team to fully meet the expectations of managers and the business.
Get the insights and capabilities to deliver high-quality sales forecasts that can equip senior managers to make the right call at the right time. Watch our latest vlog to learn how to build a great AI strategy to improve your sales forecasting to learn more.
