Working Tools Built on Your Data

Custom data products, decision systems, and intelligence platforms your team actually uses

Your team makes critical decisions every day. Some of those decisions live in spreadsheets one person understands, manual workflows that break when someone leaves, or gut calls because the data is too scattered to trust. Analytics Intelligence turns those pain points into working tools. Pricing engines. Management dashboards. Operational platforms that pull from your actual systems and put answers where your team needs them.

The Spreadsheet Ceiling

Every growing company hits a point where spreadsheets stop scaling. The pricing model one analyst built becomes the company's most critical and most fragile system. The weekly report takes two days to assemble. Leadership asks a question and the answer takes a week because nobody can query the data directly. These are the problems Analytics Intelligence solves.

Manual Workflows

Critical processes that depend on one person's spreadsheet

Scattered Data

Decisions delayed because information lives in five different systems

No Self-Service

Leadership can't get answers without asking the data person

Fragile Systems

Tools that break when the person who built them leaves

What Gets Built

Custom tools designed around your specific data and decisions

💰

Pricing Intelligence Platforms

Custom applications with suggested pricing engines, historical analysis, win/loss tracking, and management reporting. Replace Excel-based pricing workflows with tools the whole team can use.

📊

Operational Decision Systems

Dashboards and tools that connect to your ERP, CRM, and operational systems. Surface the metrics that matter and put them where decisions happen.

⚙️

Automated Data Products

Turn manual reporting and analysis into automated, self-updating tools. AI, machine learning, and automation are capabilities deployed within these products to solve specific problems.

How We Build

Discovery

Map the decision, the data, and the people. Understand what tool your team actually needs before we build anything.

Data Layer

Connect to your systems, establish the data foundation. If the data isn't clean, we fix that first.

Working Prototype

A functional version your team can react to. Not a mockup, a working tool with real data.

Production Build

Refine based on feedback, harden for daily use, train the team, and hand over.

Iteration

Tools evolve as your business does. Ongoing support available through Analytics as a Service.

Success Story: Service Contract Renewal Prediction

The Challenge

An automotive service contract company with 200K+ customers needed to:

  • Predict customer renewal rates to optimize retention strategies
  • Identify at-risk customers before they churn
  • Improve renewal campaign targeting and effectiveness
  • Optimize resource allocation for customer success
  • Improve customer lifetime value predictions

Our Solution

We built a custom analytics intelligence platform:

  • Customer behavior models using historical data and engagement patterns
  • Renewal prediction models with 99% accuracy
  • Real-time customer health scoring and risk stratification
  • Personalized retention strategies based on predicted behavior
  • Automated alert system for at-risk customers

The Results

45%
Reduction in Churn Rate
$450K
Additional Revenue
200%+
ROI

Investment

💰 Investment

$75,000 - $150,000

Based on tool complexity and scope

⏱️ Timeline

6 Months+

From discovery to production

📈 Expected Impact

40x Faster

Delivery went from 3 weeks to 3 hours

Tools and systems your team actually uses, built on data you already have

Discuss Your Use Case

Frequently Asked Questions

What kinds of tools do you actually build?

It depends on the problem. Recent examples include pricing intelligence platforms, management reporting systems, and automated data pipelines that replaced manual Excel workflows. The common thread is: something your team uses daily to make better decisions.

Do we need clean data first?

Not necessarily. If your data needs work, that's part of the engagement. We often start with a data layer build before the tool itself. The Analytics Strategy tier is designed for exactly this situation.

How is this different from buying software?

Off-the-shelf tools solve generic problems. Analytics Intelligence builds custom tools around your specific data, your specific workflows, and your specific decisions. The pricing engine we build for an aviation parts company looks nothing like what a SaaS distributor needs.

What role does AI play?

AI, machine learning, and automation are capabilities we deploy where they add value. A suggested pricing engine might use ML under the hood. An automated report might use AI to flag anomalies. But the headline is the tool, not the technology.

Ready to Replace That Spreadsheet?

Custom tools built on your data, designed for your team