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Sales Forecasting SoftwareSales Forecasting Tools: Phase One – A Resounding Success with Promising Rollout Potential

Our pioneering project with a renowned German family-owned manufacturer of liquid and air filter systems marked a significant milestone in custom sales forecasting software innovation. This initial phase culminated in the creation of a custom sales prediction software that not only met but exceeded client expectations, paving the way for an enthusiastic project rollout.

custom sales prediction software

Scope of work

  • Data Analysis

  • R

  • Python

  • AWS Cloud

Crafting a Superior Custom Sales Forecasting Solution

Challenge & Approach: Amidst the complexities of predicting sales for over 30,000 items, our team harnessed the power of advanced forecasting tools, including the Holt-Winters and Holt models, to navigate the intricate landscape of sales forecasting process. Our endeavor was not just to match but to surpass the predictive acumen of seasoned sales professionals. We navigated through limited historical data and unconventional sales patterns by integrating a suite of the best sales forecasting software tools.

Innovative Solutions: Our team employed a diverse array of forecasting tools, meticulously evaluating 11 different models such as AR, ARIMA, and Exponential Smoothing. This robust approach allowed us to deliver accurate forecasts, which is crucial for effective sales pipeline management. The chosen models excelled in their resistance to data anomalies, ensuring reliable forecasts essential for strategic sales plans.

custom sales prediction app

Forecasting Methods and Development Process

In our project, among different types of sales forecasting methods, we primarily used Historical Forecasting methods, analyzing past sales data to do sales forecasts and predict future performance, as seen in our application of the Holt-Winters model. Additionally, our approach mirrored aspects of Multivariable Analysis Forecasting, which considers multiple factors like seasonality and anomalies in sales data. This multifaceted approach, involving various sophisticated models, allowed us to generate comprehensive and accurate sales predictions and sales forecast report.

The development of the machine learning model for our project was a meticulous and iterative process aimed at delivering a custom and effective sales forecasting solution that bridges the gap between computational precision and human sales activities. We delved deep into the client's sales data, applying a variety of preprocessing techniques to clean and structure the data for optimal model training. The model was trained using historical sales figures, incorporating factors like seasonal variations and market dynamics to enhance its predictive power. By employing a blend of time series analysis and advanced algorithms, we ensured that the model could adapt to sales trends and provide accurate forecasts. Continuous testing and validation against accurate sales forecast allowed us to fine-tune the model parameters for improved accuracy. The result was a robust, self-learning forecasting tool that evolved with each sales cycle, providing the sales team with a powerful assistant to augment their decision-making and elevate their productivity.

The custom system’s dashboard showcases custom forecast by real-time sales analytics through bar charts and line graphs, essential for a clear depiction of sales trends and performance. A notable feature is the model selection functionality, offering a range of predictive models to cater to diverse forecasting requirements and empowering sales teams with unparalleled flexibility in their sales process.

custom sales prediction application
  • Expertises

    Data Analysis

  • Location


Elevating Sales Predictive Capabilities

Impactful Outcomes: The culmination of this phase was a groundbreaking custom ales forecasting tool that provided not only approximate sales forecasts but also seamlessly integrated with the internal sales cloud platform and sales CRM. This synergy augmented the existing sales process, significantly enhancing the sales team's productivity and performance. The client witnessed firsthand the transformation from traditional forecasting methods to a more predictive analytics-driven approach, resulting in more accurate sales forecasts and better-informed sales decisions.

Client Satisfaction & Future Prospects: The custom model's capability to support human decision-making and boost productivity led to the client's affirmation for a project rollout. Our sales forecasting software work not only met the client's immediate needs but also laid a strong foundation for future sales revenue growth and pipeline management. With our client eager to explore the next phase, we are poised to further refine our solution, incorporating insights from actual sales data and market trends.

custom sales prediction software development app development

Key Features of Our Sales Forecasting Software

Our sales forecasting software is a comprehensive tool designed to streamline the sales process. It integrates seamlessly with the internal sales cloud system, enhancing reporting capabilities and aligning closely with your sales targets. The software's robust pipeline management feature provides valuable insights into future revenues and forecasts, while advanced predictive analytics tap into historical sales data to project future market trends for sales reps. Tailored to meet the unique demands of your business, the software's forecast categories can be customized for various sales processes. Plus, its user-friendly interface is crafted for accessibility, ensuring that sales representatives, managers, and sales leaders can use the software with ease and efficiency to achive their sales goals.

custom sales prediction machine learning model

Embracing Advanced Sales Forecasting

As we embark on the next phase, our focus remains on delivering the best sales forecasting tool in the market. Our commitment to refining our sales forecasting methods and tools, along with our understanding of common sales forecasting mistakes, positions us uniquely in the realm of predictive sales forecasting. The success of this project underscores our capability to revolutionize the sales forecasting landscape, not just for our current client but for businesses aiming to achieve precision in their revenue goals and sales performance.

sales prediction machine learning model

Break the rules. Do it your way!

Request a call today and get free consultation about your custom software solution with our specialists. First working demo just in 7 days from the project kick‑off.

Matt Sadowski

CEO of Mobile Reality

CEO of Mobile Reality

Case studies

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Frequently Asked Questions

Our approach begins with a deep dive into your unique sales data and processes. We then customize the forecasting models to align with your specific business objectives, ensuring that the software provides targeted insights and predictions.
Yes, the software that we design and develop for our Clients has agility in mind, utilizing real-time data processing to adapt to market fluctuations swiftly, ensuring your business remains responsive and informed.
We typically start with historical sales data, including transaction records, seasonal trends, and any relevant market analysis data to train the predictive models effectively. The best way to start cooperation where the goal is to create a machine learning model is business workshops where the main business and technological aspects will be defined and pointed out. Moreover, during the workshops, Mobile Reality can initially analyze the data, get familiar with it, define the next steps, and plan to achieve the business objective declared by the Client.
Yes, we ensure our software can integrate with a wide range of business intelligence, such as HubSpot, Tableau, Salesforce Sales Cloud , Sales Hub, or PowerBI enhancing its functionality and providing a unified view of your analytics.
YWe offer ongoing support which includes software updates, troubleshooting, and additional customization as your business scales and evolves. Moreover, signing an SLA agreement with us after the app is in production is recommended for on-demand improvements and changes. As e example, we offer 24-36 hours of availability per month, with dedicated hours for critical and standard issues, with response and reaction times from 1 to 8 business hours of our sales and service team. The number of hours and response time is adjusted to the Client's needs and requirements.