Systems that scale with intelligence
Turn repetitive work into reliable flows and turn scattered data into useful decisions. We set up marketing automation, sales automation, data warehousing, predictive analytics, and cross team workflows that improve speed, accuracy, and ROI.
What is Automation and Analytics?
It is the use of software, data pipelines, and predictive models to automate routine work and deliver trusted insights so teams act faster and leaders make better decisions.
The Promise
One stack, one source of truth, one simple operating rhythm. Your tools connect, your data is clean, and your teams act on the same numbers. You save hours each week and spot growth opportunities faster.
What do you get?
A complete automation and analytics system that includes
- A discovery report with a clear automation map and data blueprint
- A ninety day rollout plan with quick wins and owners
- A twelve month roadmap for scale and advanced use cases
- A central data warehouse with reliable pipelines and models
- Decision ready dashboards and alerts for leaders and teams
- Predictive models for churn, lifetime value, and pricing
- Cross team workflow automation with approvals and SLAs
Our four pillars of Automation and Analytics
Marketing and sales automation
Problems
- Leads leak between marketing and sales
- Manual follow ups slow down responses
- Drip journeys are inconsistent and hard to measure
- Ad budgets do not sync with funnel performance
- Data sits in silos across forms, CRM, email, and ads
How it solves
- Build end to end journeys for capture, qualify, nurture, and hand off
- Add lead scoring and routing with simple rules and SLAs
- Run email and WhatsApp drips with behavioural triggers
- Automate ad rules, remarketing, and budget pacing
- Sync data across forms, website, CRM, email, and ad platforms
Outcome
- Faster responses and higher conversion from lead to opportunity
- Fewer missed follow ups and cleaner hand offs
- Better return on ad spend and clearer attribution
Data warehousing and reporting
Problems
- Reports conflict and teams do not trust the numbers
- Data lives in many tools and exports are manual
- Leaders cannot see contribution by channel or segment
- Analysts spend time cleaning data instead of analysis
- Access and governance are unclear
How it solves
- Design a simple architecture with sources, schemas, and governance
- Build ETL or ELT pipelines into a central warehouse such as Big Query, Redshift, or Snowflake
- Model a single source of truth for customers, orders, revenue, and spend
- Create self serve dashboards for leadership and functional teams
- Add data quality checks, roles, and scheduled reports
Outcome
- One trusted view of the business
- Faster analysis with less manual work
- Clear visibility into revenue, margin, and payback by channel and segment
Predictive models for churn, LTV, and pricing
Problems
- Risk of churn is spotted too late
- Lifetime value is guessed and pricing is inconsistent
- Campaigns treat all customers the same
- Models, if any, never reach the tools that teams use
How it solves
- Frame the problem with clear KPIs and success thresholds
- Prepare features from clickstream, CRM, and transaction data
- Build and test models for churn, lifetime value, and pricing
- Deploy scores into CRM, email, and ad platforms for action
- Monitor drift and performance and update playbooks
Outcome
- Earlier saves for at risk customers
- Smarter spend based on predicted value
- More confident pricing moves with evidence
Cross team workflow automation
Problems
- Approvals and hand offs slow down delivery
- SOPs are on paper and rarely followed
- Tickets and requests get lost in email and chat
- Finance and HR operations are manual and error prone
- Integrations are brittle and create duplicate data
How it solves
- Map SOPs and remove bottlenecks across marketing, sales, operations, finance, and HR
- Build no code and low code flows in tools such as Zapier, Make, or Power Automate
- Add intake forms, SLAs, and escalations to keep work moving
- Automate invoice capture, PO approvals, payouts, onboarding, and offboarding
- Integrate core systems with reliable sync and real time alerts
Outcome
- Faster cycle times with fewer errors
- Clear ownership and better visibility for all teams
- Hours saved each week and lower cost per task
How we work
Discovery and diagnostics
We review the current pipeline, win loss data, CRM health, and outreach motion. We meet your sellers to understand objections, cycle time, and hand offs. You get a short list of quick wins and a clean baseline of KPIs.
Design and architecture
We create a practical automation map and a data blueprint. This includes a ninety day rollout with owners and weekly priorities and a twelve month roadmap for scale and advanced use cases
Build and enable
We set up pipelines, models, dashboards, and workflows. We connect your CRM, analytics, ads, email, support, finance, and HR systems. We run pilots, document how to use each asset, and train the team.
Run and optimise
We review performance each week and run a monthly KPI board. Scores, alerts, and flows are tuned based on real outcomes. Each quarter we add new use cases, retire clutter, and keep the system fast and simple.
Success scorecard
Metrics we track and report
- Automation hours saved and cost per task
- Lead response time and lead to opportunity conversion
- Campaign payback period and return on ad spend
- Churn risk distribution, save rate, and upsell rate
- Data freshness, pipeline success rate, and dashboard usage
- SLA compliance for approvals and ticket resolution
Proof and consent policy
We publish only consented automation and analytics results with clear time frames and source systems. Until we have permissions we use neutral examples for education.
-
1. What problems does this service solve?
Lack of a clear growth plan, slow decision making, weak visibility on KPIs, unclear unit economics, poor pricing logic, manual processes that slow teams, and scattered tools that do not connect.
-
2. Who should use this service?
Founders and leaders in startups and small and medium businesses in India who want faster execution, reliable numbers, and better ROI from existing tools.
-
3. Do we need a big data team to start?
No. We begin with light pipelines and simple models. The goal is useful outcomes with minimal overhead.
-
4. Will you work with our current tools?
Yes. We work with your CRM, analytics, ads, email, support, finance, and HR tools. New tools are suggested only when the business case is strong.
-
5. Can you support compliance and access control?
Yes. We set roles, policies, and audit trails. We also add data quality checks and error alerts.
-
6. How soon can we see results?
Quick wins can land within thirty to forty five days such as response time cuts, cleaner dashboards, and working automations. Compounding gains build over three to six months.