Nowadays, being a step ahead is key to a company’s success. Having a clear idea of what to expect helps businesses make deliberate decisions and drive better revenue.
This is where sales prediction and integration with Salesforce come in handy. Accurate forecasting enables leaders to predict the required amount of leads, expected revenue, and whether the company needs to hire more to hit the goals.
We are to cover the need for sales prediction, the benefits it can bring in, and efficient methods with relevant examples on how to imply them.
Sales Predictions: Benefits for Business
The main aim of forecasting is not just telling the future but giving actionable insights into what’s coming for your company to act accordingly. Sales prediction reveals the operating rhythm of your company, enables you to make prompt decisions, and sets accurate goals.
Benefits of Sales Predictions
- Determine Issues. With sales predictions, you can recognize issues beforehand and асt upon them to either avoid or get rid of them. Exporting Salesforce to Google Sheets will give you complete data control and allow you to gain access to detailed analytics enabling you to track changes. For example, if your sales guys are not getting close to their quarter targets due to a lack of existing leads to convert, you can spot it on time and focus more on generating and bringing in more potential leads.
- Facilitate Growth. They say what can be measured gets quickly done. It’s the same with business. You can see your goals, potential risks, and possible changes by predicting sales. You are well equipped for anything coming your way, hence, getting a chance to make clever decisions. For instance, if your company’s ROI is 25% lower than anticipated, you will need to investigate the work processes to see what’s not working and eliminate it.
- Resource Planning. It is easier to manage resources and make more accurate decisions with sales prediction. If a forecasted increase in demand exists, you will need to increase the budget to get on board more team members. And vice versa, if there is an expected sales decline, you will get an opportunity to stop hiring new people and pay more attention to bringing more business rather than employees.
Aspects Affecting Forecasting
Internal aspects of impact forecasting usually occur inside the company and, if spotted on time, can be changed to avoid negative consequences.
- Product Alterations. A new feature introduction or bug removal can highly influence sales predictions. Your employees can use such changes to their benefit, reduce the sales cycle, and get more deals. Adding integrations with Salesforce into work will also create synergy for work.
- Stock Shortage. Due to the lack of products in stock, sales predictions can be relatively low.
- Changes in pricing. Product prices play a significant role when it comes to predictions. Any fluctuation can lead to decreased sales.
- Employee Work. Due to team burnout or employee shortage, the company can face labor issues, resulting in sales taking a dip.
External aspects usually happen outside the company and are out of its direct control.
- Economy Situation. The current condition of the country’s economy has a direct impact on businesses. With a strong economic condition, companies will succeed with people willingly investing. However, with the economy under depression, companies will be losing their money and not be willing to purchase.
- Regulation Change. Any amends in the regulations and policies and new law introduction can be beneficial or harmful for businesses. In predicting a company’s future sales, it is essential to consider such changes to understand how they can influence business shortly.
- Consumer Identity Shift. If your clients change their preferences towards your offered goods, it will impact sales and might result in its decrease. However, businesses can still nudge consumers to proceed with buying products when using the call to action.
- Natural Disasters. Situations that cannot be anticipated beforehand, like Covid, can cause issues for the business and will directly impact the work of sales operations.
Methods for Predicting Sales
There are many ways for sales predictions, and they all depend on your company’s needs. You can pick one or use several simultaneously to achieve the ultimate results.
Sales cycle length
|Great for companies tracking prospects coming into the sales pipeline.Objective and applicable to various sources of leads.
|Requires thorough data tracking to avoid mistakes.The cycle will be different depending on the companies you sell to.
With the help of such a method, you get a clear picture of your chances to close existing deals by predicting according to the length of your company’s sales cycle. Knowing the average length of the cycle, you can get more accurate sales predictions. Whenever you get a certain number of incoming leads, you will be able to calculate sales figures and see how successful the company will be in the coming months.
Example: Take the last three closed deals and how long it took your team to close them. Suppose the first one took 52 days, the second one – 50 days, and the third one – 49 days. Overall, to close three deals took you 151 days. The average cycle for your company’s sales is 50 days meaning your deals have a 50% chance to get closed.
Opportunity stage prediction
|Objective and simple.
|Doesn’t provide highly accurate results.Doesn’t consider the size and age of the deal.
This predicting technique is all about assigning a certain percentage of likelihood to each step within the sales period. The latter is usually divided into outreach, demo, trial, negotiation, etc. Each gets a percentage for evaluating the chances of a successful deal.
Example: According to your company’s sales pipeline, you’ve got the below stages with percentages:
- Incoming Deal – 7%
- Qualified Stage – 10%
- Demo – 25%
- Proposing – 45%
- Negotiating – 60%
- Finalising – 100%
According to the above model for predicting, a $2,000 incoming deal on the Demo step has a 30% success chance. The latter gets us to the predicted amount of opportunity worth $600.
|Beneficial for the company’s early stages. Helps get early predictions when forecasting on newer leads.
|Not a method that can be scaled or checked for accuracy.Unable to verify predictions.
The process is solely based on a salesperson’s intuitive sense.
Example: Imagine you want to predict sales for a new brand. The latter has been out for nearly two months and has no previous sales data to rely on. You ask your employees to make predictions for the next half of a year based on their experience. They examine all the opportunities for potential prospects and, based on the analysis, get their strategic roadmap and a $40,000 sales prediction for six months.
|Easy to implement and accurate.
|Doesn’t consider seasonability due to dynamic markets.It has a drawback of changing environmental demand.
This predicting method is relatively straightforward. You evaluate your company’s performance taking a particular time in the past and get an estimate for coming sales. Depending on the previous figures and other significant aspects, those numbers can be either equal, slightly less, or more.
Example: Your last month’s income equals $90,000. Besides, you get the records that your revenue has been increasing 10% monthly during the previous six months. Taking the above data, you anticipate that next month’s income will likely reach $99,000.
|Based on data, the method is proven accurate.
|Requires an analytics tool to get results.Not practical for small companies with a lack of budget.
One of the most complex yet efficient ways to predict sales is multivariate analysis. The latter works with predictive analytics and looks at aspects like the average length of the cycle, percentages of probability, historical data, etc.
Example: You’ve got two salespeople working on two different prospects. The first sales member, known as one of your best deal closers, is on the Demo step with a new consumer getting a deal worth $7,000. With a lower rate of successful deals, the other salesman is on the Negotiation step with a repeated client with a deal worth $10,000.
To get sales predictions, the system will look at deal stages, cycle lengths, the success rates of each salesperson, their recent performance, and how worth each deal is. As a result, you will be able to calculate approximate sales for each one.
Test Market Analysis
|Allows you to spot and fix issues before launching.Enables giving clients early product access, creating curiosity.
|Beta version releases are rather expensive. What is true for one market may not be the same for another one.
One of the popular methods is calculating the sales prediction based on the market test. The latter gathers data about how potential consumers feel about upcoming products to predict future revenue. The analysis is usually conducted during launching a product to see how people react to it and choose the correct market to attract the target audience.
Example: Divide the chosen market into several regions where you will be introducing your new product line. The test market will be where you launch without investing in advertising. The other one where you throw with advertising will be your control market. After analyzing how people react to your new product line in both markets, you will see whether the product succeeds, in which market, and the predictions for the sales.
Good and timely forecasts impact not only sales but also have a meaningful effect on the whole business unit. With the help of scalable predictions, company leaders get a chance to make more actionable business decisions, identify and eliminate internal issues, improve lead generation, and facilitate growth in the best way possible.
The latter needs to be utterly consistent with salespeople mapping their accounts and conducting estimates regularly when it comes to sales predictions. With the given prediction ways, you can evaluate using several different ways, depending on the pursued goals and existing tools.