Despite what some may believe, SMBs (small and medium-sized businesses) are not simply smaller versions of enterprise organizations. The size of a company has a deep impact on how a company is organized, but most importantly, it impacts the purchase processes. Since we are talking about different sales processes, we also need to define a different forecasting approach for each type of company. In the following post, we will go through the most important factors that dictate the differences between enterprise and SMB forecasts.

The sales cycle

The complexity of the sales cycle is the main factor that affects the differences between enterprise and SMB sales forecasts. For starters, enterprise sales have more complex sales processes and longer sales cycles. This happens because the decision-making process is often divided between several stakeholders, not to mention the fact that decision-makers are harder to reach in an enterprise. Moreover, each enterprise can have its own purchase process, which can be more or less complex, affecting the length of a sales cycle. On average, an enterprise purchase decision requires the consensus of 7 stakeholders. The longer a sales cycle is, the harder it is to predict its outcome. SMBs have shorter cycles because their needs are more urgent, and their purchase processes are less complex. On the other hand, with enterprises, a cycle can take more than 6 months, so it will be harder to make quarterly forecasts for these companies.

The accuracy of historical data

Historical data is the heart of a forecast, but the accuracy of this indicator can vary based on the size of the company in question. The reason for this is very simple: smaller companies tend to have shorter and less complex sales cycles, which leads to more concise and more accurate historical data. Enterprises, on the other hand, have complex sales cycles which can be affected by numerous variables such as the availability of decision makers, internal purchase processes or last-minute budget cuts. Due to the complexity and volatility of enterprise sales, enterprise forecasts need to be more complex and include as many variables as possible to increase the accuracy of their historical data.

The sales reps

As the sales processes differ for enterprises and SMBs, so do the skills and the goals of the sales reps. Enterprise sales representatives are often more analytical as they use more market date to state their points and stay ahead of the competition. Moreover, enterprise reps are also farming sellers, which means that their end goal is not just to make a sale, but also to get as much business as possible out of a new or existing client. SMB reps, on the other hand, are more aggressive, they deal with less competition, but they also have less experience and less data to make informed predictions. Since there are several forecasting methods which consider the predictions of the sales reps, it makes sense that the different skills of the sales rep will impact the final predictions.

Another way in which sales reps can impact forecasts is by abandoning leads in the middle of a sales cycle. This has a bigger impact on enterprise sales which can take months to finalize. Having an enterprise sales rep leave in a middle of a deal will not only impact the morale of the whole team, but that rep will take with him all the business relationships that he nurtured, relationships which will have to be rebuilt from scratch.

The complexity of the deals

Enterprise sales are far more complex than SMB sales. When selling to SMBs, you could close a deal from the first contact with a new lead, but this would never happen with an enterprise client. The more people there are in a company, the more complex the deal will be. Enterprise sales also leave more room for upselling or cross-selling, not to mention the fact that most enterprises prefer customized products.
Conclusion: As you can see, enterprise and SMB sales deal vary greatly. The differences in the sales processes require a different set of indicators which will affect your options in terms of forecasting strategies. To know which metrics, you need to track and to increase the accuracy of your forecasts, it is essential to understand the needs of your clients and the complexity of your deals.

In sales forecasting, mistakes are to be expected. However, with each mistake that you make, you should learn something, in order to refine your forecasting methods, and improve the accuracy of your forecasts. As a rule of thumb, the more metrics you track and include in your forecast, the more accurate the forecast will be. In the following post, we will discuss some key metrics that all businesses should track.


Accuracy is not only a characteristic of your forecast but an actual metric that you need to keep track of. There are several ways in which you can measure the accuracy of a forecast.
By the measure of error
Each sales team should measure the error of the forecast which is calculated by taking the absolute value of the difference between your forecast and your actual sales, and divide it by the divisor (the largest value between the forecast and the actual numbers)
Measure of error = (F-A)/F
F – forecast
A – actual sales
By product type
Accuracy can also be calculated by product, a strategy which can be a lot easier for your sales team to implement. This strategy is best suited for off-the-shelf products that don’t have customization options that can complicate the sales cycle. When it comes to complex products, you can simplify the process, by breaking the prediction down into several parts.
By size of the deal
For this strategy, you will start with a less accurate forecast in the early stages of a deal, which you will refine along the way. In the later stages of the sales cycle, you will have a better understanding of the needs of the buyers, which will help you refine your numbers.
By time period
There are two critical stages where you can measure accurately. The first stage is 90 days out, a stage at which your accuracy should be quite low, as the deal is a long way from closing. Nonetheless, there are a lot of early signs that can help your sales reps predict the chances of closing a deal. The second stage is 30 days out. At this point, the sales cycle should be at the final stages, and your accuracy should be above 90% at this point.  


When it comes to complex transactions, it is not uncommon for planned close dates to be pushed back. It is important to track these types of sales and discover indicators that show a deal’s chances of getting postponed. A pushed deal is not a lost deal. In most cases, it is just a deal that is postponed into another quarter, but this will heavily impact your predictions.  Moreover, pushed rates can also indicate a problem with certain sales reps.


The variance is calculated as the distance between the commit and the pipeline upside. This indicator will help you understand how an initial forecast can change from the beginning to the end of a quarter. To improve the accuracy of your variance, you need to be very involved in the deal activity of your reps, but you must also consider their gut predictions. In the long term, tracking the variance will not only help you understand the changes in your forecast, but you will also be able to narrow down the factors that influence these changes.


Depending on your business, and the complexity of your sales cycle, a sales forecast can be balanced throughout a quarter, or it can weight more heavily towards the end of the quarter. To measure the linearity of your forecast, you will have to track the stages of a sales cycle and the close dates. The point of tracking this metric is to adjust your sales strategy so that in the long run you can rely on an accurate and linear forecast.


As most of your forecasting strategies rely on historical data, it is important to keep an eye on your team’s commitment to recording all valuable data. The compliance numbers will show you if all the members of your team have submitted accurate forecasts for the relevant opportunities. Obviously, the sales rep forecasts are refined by a team leader, but unless all the members of your team are committed to tracking all relevant metrics, you won’t be able to improve the accuracy of your forecast

Accurate analytics and up-to-date statistics are some of the most valuable assets in a marketer’s toolset. They help you understand consumer behaviors, refine your marketing strategies and make accurate sale predictions. Today, it’s a well-known fact that the consumer journey begins online, but according to the latest statistics, that journey can end in numerous ways, from store visits to phone calls or online conversions.
Read on to discover the most relevant retail statistics from the last few months, and learn exactly what you need to do in order to increase your conversion rate and improve your inventory predictions.

Everything starts with online research

As mentioned above, online research is (in most cases) the starting journey for most consumers, as over 80% of consumers do online research before buying anything. And you shouldn’t be surprised to learn that 77% of consumers do their research from mobile devices.

Video marketing is vital for conversions

For the past few years, marketing experts have been predicting that video marketing will eventually be the most efficient marketing strategy, and now we finally have the data to back this prediction. According to a study conducted by the Aberdeen Group, video content delivers up to 66% more qualified leads as well as a 54%increase in brand awareness. Not only that but 46% of consumers watch more video ads online than they do on the TV. All this data shows that videos are the consumer’s preferred type of content. However, keep in mind that consumer’s attention span is now much shorter than it has ever been. It’s estimated that you now only have about 2.7 seconds to capture the attention of your audience, so use that time wisely.

Modern consumers rely on automatic deal finders

We did mention above that the consumer journey starts online in most cases, but traditional research is proving to be too time-consuming for modern customers who are now turning to apps and browser extensions that automatically find deals for them. 72% of consumers say they do this to save time, while 63% do it because they are more confident to buy a product whose price is recommended by an automatic deal finder.

E-commerce continues its slow but steady evolution

For the past few years, e-commerce sales have been growing by approximately 15-20% per year. Despite this obvious evolution, over 40% of small businesses still don’t even have a web presence, not to mention an online store.

Mobile retail is growing

It’s not only the research that is done via mobile devices, as today’s consumers are finding it easier and easier to also shop from mobile devices. According to a study performed by OuterBox, 79% of smartphone users have made at least one mobile purchase in the last few months. The holidays seem to be the busiest time for mobile consumers. Over the 2018 winter holidays, more than 40% of all ecommerce purchases were made from a mobile device.

Consumers want personalized shopping experiences

Making customers feel valued has always been an efficient marketing strategy, but this is not more important than ever. Based on a survey done by Accenture, 75% of modern customers are more likely to buy from a brand that addresses them by name and uses their purchase history to make shopping recommendations.

Flexible return policies build trust

Trust for online store recommendation continues to grow with consumers, that being said, some purchases are oblivious to the fact that online purchases are not as safe as store purchases. As such, it is no wonder that 60% of online shoppers review a retailer’s return policy before making a purchase, favoring brands with flexible and easy to understand return policies.

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Free deliveries have a high impact

No one likes to pay shipping fees, so it should come as no surprise that 90% of online consumers are more likely to make a purchase that comes with free delivery.

Physical shops continue to lose terrain

For a long time, consumers used to say that they prefer to try something before buying it, but according to the latest data, the popularity of physical shops is decreasing at a dramatic rate, with only 23% of retail consumers still declaring that they prefer a traditional shopping experience.

Search engines reclaim their top position on traffic and conversions

Social media has certainly made an impact in online shopping trends and behavior, however, you shouldn’t count out consumers that are turning back to search engines for both research and purchases. According to the latest data, search engines generate over 300% more traffic than social media posts. Moreover, the second page of search engine results is still the best place to hide a body, as over 75% of people don’t read past the first page.