TL;DR

Your revenue problem is actually (probably) a data problem

Most revenue leaders struggle with the data science expertise and/or bandwidth to wrangle the heaps of data they are sitting on.

e:cue is a data science service built on the belief that hidden in these heaps of messy data are intent signals that identify your most valuable customers earlier to improve conversion rates, prioritize outreach and drive down CAC

Our rapid prototyping approach reduces risk - you will see results in weeks (not years like that IT consultant told you), within your existing workflow (no new platforms to onboard) and for far less than you probably spend in a month of Facebook ads you can't measure value from.

Our expert data scientists handle the hard work of extracting, aggregating, and cleansing data, along with building custom predictive models—like LTV models for confident bidding and lead scores for sales prioritization—to solve your revenue challenges.

sales : how can I identify a good customer earlier?

Most data stacks consist of various platforms—CRM, call recordings, email, and website data. We extract, cleanse, and connect this data, creating custom metrics and predictive models to help your teams identify key customers and respond to early behavioral cues effectively.

Let's talk

how can I identify a good customer earlier?

marketing : who are the right (and wrong) customers for my business?

Creating an ICP for your business is challenging. Key customer data often lies buried in messy systems. We turn the customer journey into clear data points, revealing who your successful customers are and why—helping you optimize marketing and refine messaging.

Let's talk

who are the right (and wrong) customers for my business?

management : what's my ROI?

We understand the challenges of long conversion and revenue cycles that complicate forecasting. We collaborate with you to identify early predictors of conversion, retention, and revenue in your existing data. By operationalizing this data across key teams—marketing, sales, and finance—you align faster and boost confidence in your forecasts.

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Meet the Team

Harsha Mokkarala : Founder and CEO

With over 20 years of hands-on experience in marketing, analytics, and strategy, Harsha has firsthand experience navigating both the obvious difficulties and hidden opportunities businesses encounter while leveraging data to build lasting growth engines. He spent 10 years in a variety of leadership positions at Capital One, where he was instrumental in building their approach to online marketing while overseeing digital marketing for the credit card group. He then spent over a decade at 2U, Inc., where he served in C-suite roles including Chief Marketing Officer, Chief Data Scientist, and ultimately Chief Revenue Officer. Harsha enjoys advising and consulting across global sectors to help business leaders build data-driven marketing and revenue operations.

Abdel Alfahham : Data Science Engineer

Abdel is a data engineer with extensive experience designing, building, and deploying scalable and reliable data pipelines that utilize generalizable data validators to guarantee high data quality. With over five years of experience as a data engineer, he has worked at early-stage climate tech unicorns and revenue-generating AI-driven fintech startups, helping startups rapidly transform complex datasets into actionable insights in high-stakes settings. His expertise spans data pipeline design, geospatial data analysis, and predictive modeling.

Jeffrey Partyka, Ph.D. : Generative AI Engineer and Technician

A seasoned and extremely technical data science leader with 10+ years of battle-tested experience, leading cross-functional teams of data scientists, ML practitioners, business stakeholders, software engineers, and SMEs across dozens of AI projects at four different companies, including Raytheon and Xactly Corp. Jeff has created seven different open-source projects relating to GenAI and ML, including a football game simulation that can be viewed publicly within his GitHub repo.

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Your revenue problem is actually (probably) a data problem

sales : how can I identify a good customer earlier?

marketing : who are the right (and wrong) customers for my business?

management : what's my ROI?

FAQs

Data is always challenging. How can you help?

My data is a mess and I am not sure we collect enough. Will this still work?

I can't handle another platform/tool/integration. How do I get value fast?

We've tried predictive modeling before. Why will this work?

What kind of business challenges can you help solve?

Your revenue problem is actually (probably) a data problem

sales : how can I identify a good customer earlier?

marketing : who are the right (and wrong) customers for my business?

management : what's my ROI?

FAQs

Data is always challenging. How can you help?

My data is a mess and I am not sure we collect enough. Will this still work?

I can't handle another platform/tool/integration. How do I get value fast?

We've tried predictive modeling before. Why will this work?

What kind of business challenges can you help solve?

Before you add another static form, chatbot, or AI platform to your stack; let’s talk about how you can get more out of the data you already have.