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Esquadgroup

10 May 202104:43

Summary

TLDRCláudio, the director of Factory Softwares, introduces the concept of 'predictable sales' in this video. He explains how analyzing historical sales data can forecast future outcomes, using the example of a company aiming for a monthly sales target. By understanding conversion rates at each stage of the sales funnel, one can calculate the number of proposals needed to meet sales goals. Predictive analysis also helps in estimating the time for proposal-to-order conversion and determining the average ticket size to calculate new customer acquisition needs. This approach aids managers in making informed decisions, enhancing sales processes.

Takeaways

📚 The video is about predictable sales, a concept in management to apply in the industry of scaffolding companies.
🔧 It introduces the concept of 'preventive maintenance of production' as an analogy to understand predictable sales, which is about regularly monitoring machine components to anticipate maintenance needs.
📈 Predictable sales involve analyzing historical sales data to anticipate adjustments or predict future events, aiming for a more controlled sales process.
🎯 An example is given where a scaffolding company has a sales target of 250,000 reais per month, and the sales team missed the target in the last month.
📊 The script explains how to use historical conversion rates at different stages of the sales funnel to determine if the current proposals will meet the sales target.
✅ With a conversion rate of 25% for proposals to orders, the script calculates that 1 million in proposals is needed to hit the 250,000 reais sales target.
🕒 Predictive analysis is also used to determine the time it takes for proposals to convert to orders, which can affect the timing of meeting sales targets.
💰 The average ticket size of customer purchases is identified as a key metric to calculate the number of new customers needed to meet sales targets.
📝 The script suggests using predictive analysis to calculate the number of new contacts that should be made, based on conversion rates and customer acquisition costs.
📚 The importance of understanding sales funnel concepts, conversion rates, average ticket size, and customer acquisition costs is emphasized for effective sales management.
🔗 The video encourages viewers to check out other videos for more information on these concepts and to subscribe for updates on future videos.

Q & A

What is the main topic of the video script?
-The main topic of the video script is 'predictable sales' and how it relates to the concept of 'preventive maintenance' in production, with a focus on applying these concepts to the management of a sales industry.
What is the concept of 'preventive maintenance of production' mentioned in the script?
-The concept of 'preventive maintenance of production' refers to the regular monitoring of the state of machine components to anticipate the need for maintenance, thus avoiding unnecessary maintenance actions.
What does 'predictable sales' mean in the context of the script?
-'Predictable sales' in the script means analyzing sales components based on historical data to anticipate the need for adjustments or even predict future events, aiming to make sales forecasts based on past performance.
What is an example scenario provided in the script to illustrate the concept of 'predictable sales'?
-The example scenario is a sales industry with a monthly sales target of 250,000 reais. The script discusses how, with historical data showing conversion rates at various stages of the sales process, one can predict whether the current proposals will be sufficient to meet the sales target.
What is the sales conversion rate mentioned for proposals in the example?
-In the example, the sales conversion rate for proposals is 25%.
How does the script suggest calculating the volume of proposals needed to meet a sales target?
-The script suggests dividing the sales target by the conversion rate to find out the volume of proposals needed. For instance, dividing 250,000 by 25% gives a proposal volume of 1,000,000.
What is the purpose of predictive analysis mentioned in the script?
-The purpose of predictive analysis in the script is to help determine how long it takes for a proposal to be converted into an order, to understand the average ticket size of customer purchases, and to calculate how many new customers or contacts are needed to meet sales targets.
What is the interval mentioned for the conversion of proposals to orders in the script?
-The script mentions an interval of 45 days for the conversion of proposals to orders based on historical data.
How can the average ticket size help in achieving sales targets according to the script?
-The average ticket size can help in calculating how many new customers are needed to achieve sales targets, based on the conversion rates and the historical cost of acquiring customers.
What is the script's stance on the value of predictive analysis in managing a sales industry?
-The script posits that predictive analysis is a valuable tool in managing a sales industry, as it can help identify demands, risks, opportunities, and strengths or weaknesses in the sales process, thereby assisting managers in making decisions.
How can viewers get more information on related concepts like sales funnel, conversion rate, and customer acquisition cost?
-Viewers can get more information on related concepts by watching other videos on the channel, as suggested in the script, and clicking on the provided link.

Outlines

00:00

👋 Introduction to Predictive Sales

Cláudio, director of Factory Softwares, introduces the concept of Predictive Sales. He asks if the viewers are familiar with it and encourages them to stay tuned for a five-minute video on management concepts applicable to the window and door industry.

🔍 Understanding Predictive Sales

Predictive Sales is explained through an analogy to predictive maintenance in manufacturing. By periodically assessing machine components to preemptively address maintenance needs, predictive sales similarly uses historical data to anticipate and adjust sales strategies, aiming to forecast future events.

📊 Example of Predictive Sales Analysis

An example is given to clarify the concept: if a company has a monthly sales target of 250,000 reais but missed it last month, they can use historical data on proposals, negotiations, and conversion rates (40%, 30%, and 25% respectively) to determine if their current proposals will meet the target. They need 1 million in proposals to achieve 250,000 in sales.

⏳ Predictive Analysis Timing

Predictive analysis can also determine how long it takes for proposals to convert into orders. If it typically takes 45 days to close a deal, even with 1 million in proposals this month, the target may not be met next month. The analysis helps understand the timing needed to achieve sales goals.

💰 Customer Metrics in Predictive Analysis

Using predictive analysis, companies can calculate the average purchase value and determine how many new customers are needed to meet sales targets. This involves assessing the number of new contacts required based on conversion rates and the necessary investment, considering the customer acquisition cost.

📈 Importance of Predictive Analysis in Sales Management

Predictive analysis is valuable in managing a sales pipeline. While statistics alone don't guarantee success, they help identify demands, risks, opportunities, and areas for improvement. This aids managers in making informed decisions. Viewers are encouraged to watch related videos for more information and to subscribe for updates.

Mindmap

Keywords

💡Predictable Sales

Predictable sales refer to a sales approach where the outcome can be anticipated based on historical data and trends. In the video, the concept is used to describe a method of analyzing past sales data to forecast future sales performance. The script mentions that by understanding the conversion rates at each stage of the sales process, one can predict the number of proposals needed to meet a sales target, exemplifying the application of predictable sales in a manufacturing industry setting.

💡Maintenance

In the context of the video, maintenance refers to the periodic inspection of machine components to anticipate the need for repairs and prevent unnecessary maintenance. The script uses the term 'preventive maintenance' as an analogy to explain the concept of predictable sales, suggesting that just as one would monitor machinery to predict maintenance needs, sales data can be monitored to predict sales outcomes.

💡Sales Funnel

A sales funnel is a visual representation of the stages a customer goes through from initial awareness to the final purchase. The video script uses the sales funnel concept to discuss the stages of contact, negotiation, proposal, and order, emphasizing the importance of understanding the conversion rates at each stage to predict sales and meet targets.

💡Conversion Rate

Conversion rate is the percentage of potential customers who complete a desired action, such as making a purchase. The script explains that knowing the conversion rates for different stages of the sales process is crucial for predicting sales outcomes and planning the number of proposals needed to achieve sales goals.

💡Historical Data

Historical data refers to past records or statistics that can be used for analysis. In the video, the speaker emphasizes the importance of collecting reliable historical sales data to make accurate predictions about future sales performance and to determine the sufficiency of current sales proposals.

💡Sales Proposal

A sales proposal is a document that outlines the details of a potential sales deal. The video script uses the term to illustrate how, based on historical conversion rates, one can calculate the volume of proposals needed to meet a specific sales target.

💡Sales Target

A sales target is a predetermined amount of sales that a company aims to achieve within a certain period. The script discusses a scenario where a manufacturing industry has a monthly sales target of 250,000 reais and how predictable sales analysis can help determine if the current proposals are sufficient to meet this target.

💡Predictive Analysis

Predictive analysis is a process that involves using data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical patterns. The video script mentions using predictive analysis to estimate the time it takes for a proposal to be converted into an order and to calculate the number of new clients needed to meet sales targets.

💡Average Ticket

The average ticket, or average order value, refers to the mean amount spent per transaction. The video script discusses using the average ticket to calculate how many new clients are needed to meet sales targets, based on the historical cost of acquiring a customer and conversion rates.

💡Customer Acquisition Cost

Customer acquisition cost is the expense associated with convincing a new customer to buy a product or service. In the video, the speaker mentions using historical data on customer acquisition cost to calculate the number of new contacts that need to be made to achieve sales objectives.

💡Sales Management

Sales management involves overseeing the sales process and team to ensure the organization meets its sales targets. The video script positions predictive sales as a valuable tool in sales management, helping to identify demands, risks, opportunities, and the strengths and weaknesses of the sales process, thereby assisting managers in decision-making.

Highlights

Introduction to the concept of predictable sales by Cláudio, the director of Factory Softwares.

Comparison of predictable sales to the concept of preventive maintenance in production, common in Minas Gerais.

Emphasis on the importance of using historical data to anticipate the need for adjustments in sales strategies.

Explanation of how predictable sales can help understand the sales funnel and conversion rates at each stage.

Example given: A sales industry with a monthly target of 250,000 reais and the importance of meeting this target.

Illustration of how to calculate the number of proposals needed to meet sales targets based on conversion rates.

Discussion on the use of predictive analysis to determine the time it takes for proposals to convert into orders.

Highlighting the importance of understanding the average ticket size of customer purchases for sales forecasting.

Insight on calculating the number of new customers needed to meet sales targets based on the average ticket size.

Explanation of how to determine the number of new contacts required to achieve sales objectives using conversion rates.

Discussion on the necessity of understanding the customer acquisition cost based on historical data.

Emphasis on the value of predictive analysis in managing a sales industry and its impact on decision-making.

Mention of the limitations of statistical calculations and the importance of analysis in identifying opportunities and risks.

Encouragement for viewers to subscribe for updates on future videos on the channel.

Invitation for viewers with questions to leave comments for further discussion.

Closing remarks with a warm farewell and anticipation for the next video.