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Custom Analytics Model

Interested in leveraging machine learning for your business? We'll work with you to create a customized plan and explore the best ways to bring the power of ML to your business.

Fill out the form below to let us know your requirements. We understand that machine learning models might not be the right fit for everyone, so feel free to contact us for a free consultation.

Features

User friendly data analysis platform, allows you to build all types of charts, analysis, stats, and machine learning models for prediction.

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Case Study

For small business inventory, sales or other data, several types of machine learning (ML) models can be built to optimize operations, improve decision-making, and forecast future demand. The specific type of ML model depends on the goals of the business and the available data.

Here are some common use cases and ML models that can be built using inventory data:


Demand Forecasting

Use Case: Predict future demand for products to optimize stock levels and reduce overstock or stockouts.

Data Needed: Historical inventory levels, sales data, seasonality, promotions, and other time-dependent factors.

Example: Predicting how much of each product will be needed in the next month or quarter.

Sample Dataset
Date Product Units Sold Price Promotion
2023-01-01 Product A 150 10.5 No
2023-01-02 Product A 170 10.5 Yes
2023-01-03 Product A 160 10.5 No
2023-01-04 Product A 180 10.0 No

Inventory Optimization

Use Case: Optimize the inventory levels by predicting the ideal stock quantities for each product based on demand and other factors.

Data Needed: Inventory levels, sales, delivery times, costs, storage limits, and demand patterns.

Example: Recommending optimal reorder quantities and reorder points for each product to avoid stockouts.

Sample Dataset
Product ID Product Name Category Unit Cost Selling Price Historical Demand Current Inventory Reorder Point Lead Time Holding Cost Shortage Cost Ordering Cost
1 Tennis Racket Sports 50 100 200 30 10 20 5 2 10
2 Tennis Ball Sports 2 5 1000 500 200 2 1 0.5 2
3 Tennis Shoes Sports 40 80 300 20 10 7 3 2 8

Image Classification

Use Case: Identify and categorize images into predefined categories based on visual content.

Data Needed: Labeled images for each category, including examples with different lighting, angles, and backgrounds.

Example: Automatically classifying product images by category (e.g., clothing, electronics) to streamline cataloging for an e-commerce platform.

Sample Dataset
Image ID Category Resolution File Size (KB) Format Color Mode Aspect Ratio Brightness Level Contrast Level Tags Source Upload Date
1 Clothing 1920x1080 450 JPEG RGB 16:9 Medium High Shirts|Summer|Fashion User Upload 2023-07-15
2 Electronics 1280x720 300 PNG Grayscale 4:3 Low Medium Phone|Gadget|Mobile Online Catalog 2023-06-10
3 Home 1024x1024 500 JPEG RGB 1:1 High Low Furniture|Interior|Modern In-house Photography 2023-05-05
4 Sports 800x600 200 JPEG RGB 4:3 Medium High Football|Outdoors|Active User Upload 2023-08-22
5 Clothing 1920x1080 480 PNG RGB 16:9 High Medium Jackets|Winter|Fashion Online Catalog 2023-09-10

Customer Segmentation

Use Case: Segment customers based on purchase behavior, which helps with targeted promotions and stocking relevant products.

Data Needed: Customer purchase history, demographics, and transaction frequency.

Example: Grouping customers into categories such as "frequent buyers" or "seasonal buyers" to adjust inventory levels for specific groups.

Sample Dataset
Customer ID Age Gender Location Income Level Marital Status Total Spend Purchase Frequency Average Order Value Recency Website Activity Product Categories Purchases Channel Loyalty Points
1 25 Female New York 60,000 Single 1,500 10 150 30 5 Clothing|Electronics Online 200
2 35 Male Los Angeles 80,000 Married 3,000 8 375 15 10 Sports|Clothing In-Store 150
3 45 Female Chicago 75,000 Married 2,500 12 208.33 7 8 Electronics|Home|Clothing Online 300
4 30 Male Houston 50,000 Single 1,200 5 240 60 6 Sports Online 100
5 40 Female Phoenix 90,000 Married 4,500 15 300 10 12 Home|Electronics In-Store 400

FAQs

Dapptics is a user-friendly data analysis platform designed for small businesses. It allows users to upload data files, automatically analyze them, and generate charts, regression analysis, and predictive models without the need for a dedicated data scientist or specialists.

Dapptics is ideal for small businesses that have data to analyze but lack the resources or expertise in data science or IT. Our app simplifies data analysis, making insights and decision-making accessible to non-technical users

No! Dapptics is designed with simplicity in mind, so even if you have no background in data analytics, you can still easily access and understand your business data. Our user-friendly interface ensures that anyone can utilize powerful analytics tools without needing specialized training.

Currently, Dapptics supports data files in common formats such as CSV, and Excel. We recommend organizing your data into structured formats for the best analysis results. More formats are coming like pdf, doc, xml, hl7 and others.

For optimal performance, Dapptics works best with small to medium-sized datasets. If you have a large dataset, you can contact us, and our team can help you build models off-site for deeper analysis.

Dapptics can generate visual charts, perform regression analysis, and create predictive models based on the data you upload. It provides businesses with actionable insights to support decision-making.

If you have questions or need additional assistance, our support team is here to help. For more complex or custom analysis, you can reach out to us directly for consulting services.

Dapptics takes data security seriously. We ensure that all data uploaded to our platform is handled securely throughout the analysis process.

Simply upload your data file, and the app will automatically analyze it, generating visual charts and models within minutes. No complex setup or technical knowledge is required.

Yes, Dapptics is currently free to use! We’re offering the platform at no cost for a limited time to help small businesses experience the benefits of data analysis. Take advantage of this opportunity to explore our features and unlock insights from your data.

When you upload a PDF or Word document, our system uses a Large Language Model (LLM) to automatically summarize the content and generate questions and answers. This allows you to quickly and easily extract the most important information from your documents and use it to inform your work or decision-making.

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