Move faster with advanced analytics, we do the heavy-lifting.

Augment your data analytics team with our Data Scientists and get your advanced and predictive analytics projects off the ground faster.

Let's talk about your project

Why you should hire our Data Scientists?

If your company doesn't have a dedicated data science team or lacks resources to develop complex machine learning models - we're here to help!

Our Machine Learning experts are not only Data Scientists, but they also are Qadatra experts with extensive experience across various industries.

Let us handle the complexities of machine learning so you can focus on what you do best—running your business.

How do we work together?

We work closely with your team to ensure our models integrate seamlessly with your existing systems and deliver actionable insights

We start by scoping your advanced analytics project to understand the business goals you want to achieve and gather the necessary data.

We do a extensive data exploration and come up with tailored recommendations: models, timeline, key milestones.

We then develop, test, refine the models and deliver data in the form of your choice: output table, in a report or dashboard.

Predictive analytics projects to stay ahead of the game

Sales forecasting

Why do you need sales forecasting?

✔ Establish realistic data-driven sales objectives

✔ Anticipate customer demand and maintain customer satisfaction

✔ Reduce your product inventory holding cost

What do you get?

Using advanced statistical and machine learning models in Qadatra, we will help you identify patterns in your data and forecast sales for the next 6 to 12 months.

What data do we need?

At least 2 years of historical sales data.

Prospect conversion

Why do you need prospect conversion forecasting?

✔ Clearly identify converting factors across the sales funnel

✔ Targeted outreach campaigns focusing on top prospects

✔ Identify your revenue-driver personas

What do you get?

A clear understanding of the factors influencing the conversions and the list of prospects that are most likely to convert.

What data do we need?

Demographic data, geographic data, lead data, sales funnel data, interaction data, and conversion metrics.

Marketing ROI forecast

Why do you need marketing campaign result prediction?

✔ Establish realistic data-driven sales objectives

✔ Anticipate customer demand and maintain customer satisfaction

✔ Reduce your product inventory holding cost

What do you get?

A clear and actionable preview of the expected results and ROI by marketing acquisition channel.

What data do we need?

Campaign data, sales data, customer engagement metrics, conversion rates, and more to perform comprehensive A/B testing and performance analysis.

Churn Prediction

Why do you need churn prediction?

✔ Identify key factors leading to customer churn across your user base

✔ Proactively target high-risk customers with retention strategies

✔ Optimize customer experience to reduce attrition and boost loyalty

What do you get?

A clear understanding of the drivers behind customer churn and a list of customers most likely to leave, allowing for timely interventions.

What data do we need?

Customer demographic data, transaction history, interaction data, subscription or usage data, customer support data, and satisfaction metrics.

Know your customers on a deeper level

Customer feedback

Why do you need customer feedback analysis?

✔ Precisely pinpoint areas for improvement in your products or customer service

✔ Develop products and services that your customers really need

✔ Increase customer satisfaction and lifetime value

What do you get?

A summary and detailed report of your customer feedback categorized by sentiment and a clear view of the areas for improvement.

What data do we need?

Customer reviews, survey responses, support tickets, and social media feedback. We can incorporate your activity planning, product features, and customer experiences for a more holistic analysis.

Customer segmentation

Why do you need customer segmentation?

✔ Precise grouping of customers based on large volumes and complex behavioral and purchase data

✔ Improve the impact of your marketing strategies with highly personalized messaging

✔ Higher customer engagement and retention

What do you get?

A better understanding of your customer segments, what they like buying, where and when.

What data do we need?

Customer demographic data, geographic data, psychographic attributes, technographic segmentation, e-commerce and purchase history, behavioral data, and customer interactions

What are the steps of a machine learning project?

Step 1

Discovery and scoping

This is a collaborative step between you and our Data Science team. We gather your requirements and assess the necessary data sources. We also set project goals, and develop a project plan together.

Step 2

Exploratory data analysis

Our Data Scientists will come up with custom options and recommendations on how to proceed with your project. We establish clear objectives and deliverables based on a thorough analysis of your data.

We do the heavy-lifting: cleaning your data, building visualizations, identifying patterns, for instance.

Step 3

Delivery and training

Once we identified the best type of model for your project, we develop, train and optimize it to deliver the most accurate and reliable analysis.

We also document everything we do: how the model works, how did we train it, what data is being used to ensure complete clarity. We also train your team to maintain it properly.