Success Stories

Using Data Science to Improve Revenues and Demand Forecasting

Through data science, we helped our client uncover a potential $2 million revenue uplift and better understand demand seasonality.

Holographic images of data visualization float over a tablet that a person is drawing on with a stylus

Project Overview

Our client, a national manufacturing and distribution company, sells hundreds of products through multiple channels. With so many SKUs to manage, they needed a better method for understanding pricing curves and demand fluctuations. Data science seemed like a possible solution but wasn’t something they had experience with. The task was clear – build a proof of concept with data science models to identify areas of significant revenue opportunity while gaining experience and expertise with data science.

Client Challenge

While the client had a desire to invest in data science, they had no clear path to doing so. And, like many companies, they wanted to ensure there was a significant ROI before making an investment.

Massive amounts of data

With so many lines of business, compounded by several distribution channels, the client had a mass of data that made getting started on any sort of modeling project very difficult.

Starting from scratch

As the client had little experience in data science, they had yet to develop a clear vision and approach to running data science projects.

Extreme focus on ROI

Because this was their first time running a data science proof-of-concept, the client had an even keener focus on finding a tangible ROI than for other initiatives. It was crucial that this first experience gave a positive impression of the usefulness of data science.

Approach

We decided to build two different models to tackle the two largest concerns: Pricing analysis and demand forecasting. The RevGen data science team then used AWS Athena and AWS Sagemaker as well as a data subset to build their elasticity and forecasting models.

Solution

With clear business goals in mind, we were quickly able to turn around the two proof of concept models to yield real value.

Identified and cleaned data subset

Because of their large product array and long history in the industry, our client had too much data to use in a proof of concept. We began by selecting a subset of current data related to their more popular products and cleaning it to prep for modeling.

Built new models

For each of the workstreams – pricing elasticity and demand forecasting – we used the cleaned datasets, along with Sagemaker and Python to build the models, and then used Tableau to create data visualizations of the models’ output.

Uncovered key insights

Both projects returned specific, actionable recommendations that could be operationalized to increase revenue and optimize product inventories.

Results

The proof-of-concept successfully returned insights that could be used to improve both revenue and demand forecasting, lending weight to the idea of investing further in data science.

Potential $2M+ revenue uplift

Even within the small subset of data we tested, we were able to identify 29 SKUs (out of 200 analyzed) that showed price responsivity, indicating an opportunity to adjust or experiment with pricing. This led us to a conservative estimate of around $2M in revenue uplift within a year.

Proved significant seasonality

Our model also showed that several products had significant seasonality in their demand. This improved forecasting will better allow the client to optimize ordering, inventory levels, and staffing levels.

Clear next steps for data science

Given this was a first proof of concept project at the client, we ensured they were left with actionable recommendations, project documentation, and concrete next steps such as automating data imports and expanding the dataset to find additional revenue opportunities.

Success Stories

Businessman points to a holographic report of a financial growth line

Growing Revenues through Data-Driven Pricing Strategy

Analytics & InsightsCustomer Experience

Through a combination of data science and business expertise, RevGen devised a strategy that would grow our client’s revenues by more than 20%.

Read More About Growing Revenues through Data-Driven Pricing Strategy
A young white man presents data on a large TV to a board meeting.

Crafting a Data & Analytics Strategy and Proof-of-Concept Dashboard

Analytics & Insights

Our client, a national construction firm, needed a clear, detailed path to resolving their data availability, quality and reporting confidence issues. RevGen stepped in to craft a holistic Data & Analytics Strategy to give them a way forward.

Read More About Crafting a Data & Analytics Strategy and Proof-of-Concept Dashboard
A woman gives a presentation to her colleagues while a report is displayed on the monitor behind her.

Streamlining Tableau Reporting for Cloud Migration

Analytics & Insights

We helped a Fortune 500 telecom client improve their data and analytics capabilities by enhancing and streamlining their Tableau environment in preparation for a migration to the cloud.

Read More About Streamlining Tableau Reporting for Cloud Migration

Subscribe to our Newsletter

Get the latest updates and Insights from RevGen delivered straight to your inbox.