"We were pleasantly surprised at how quickly it was possible to create an AI
Accurate forecasting using Neuton models allowed our clients to correctly push the sales of
products to retail outlets and reduce lost revenue. Such services open up very wide
opportunities for quick completion of their IT products for all companies who want to
augment their ML expertise.
— Sales Force
Automation CRM Software. This easy-to-use & easy-to-deploy system is used by 150+ CPG & BFSI
Enterprises to achieve high-impact, goal-driven digital sales transformation across channels.
The Sales Force
Automation Software (SFA App) for FMCG & Consumer Goods Companies
is one of BeatRoute’s
primary products. BeatRoute’s customers use FMCG Sales Force Automation software to manage the
relationships between retailer, distributors, wholesalers and traders, and related inventory,
orders, returns, schemes, etc., as part of their retail distribution execution. The system is
also used to enable sales executives to improve their individual performances.
For retail distribution to work efficiently, it is important to predict the demand for each
product at each point of sale, in advance. Accordingly, there is a need to make predictions for
thousands of products, at potentially millions of retail stores. BeatRoute had set a goal for
their Sales Force Automation software to provide FMCG companies with an opportunity to make such
forecasts in advance & nudge the sales executives to push the product sales accordingly during
visits, for all outlets and across a selected range of products - and they utilized Neuton to
make this goal a reality, by the fastest means possible.
To develop such functionality, a machine learning model that can learn from historical data on
sales of certain items of goods, and at certain points of sale, needed to be built.
BeatRoute had collected data over 37 months from more than 22,000 outlets, and relating to 127
product names. The data for building the first model was a CSV file with 883 thousand lines. The
factors that were used to build the predictive model were:
name of the product
point of sale ID
period of sale
In addition, Neuton generated new factors in automatic mode (more info below).
All aspects of building the model took place in Neuton’s fully-automated mode, and the process
was relatively simple:
First, historical sales data was uploaded to the Neuton AutoML platform through a simple
The complete model training process then took less than 80 minutes.
Finally, it was necessary to integrate the Sales Force Automation software with the created
model. To do this, BeatRoute utilized the option Neuton provides of implementing a model in
one click and making requests through the API. Neuton now transmits the data in real-time in
the following format: date, point of sale id and product name. Neuton then calculates a
prediction and sends it to BeatRoute’s Sales Force Automation software, where it is
displayed to the user.
Vinay Singh, CEO, BeatRoute:
«We were pleasantly surprised at how quickly it was possible to create an AI solution and
integrate it into our software.
It took us hours to build the model, not weeks. Thus, we have reduced the time and cost of
development and implementation. Accurate forecasting using Neuton models allowed our clients to
correctly push the sales of products to retail outlets and reduce lost revenue.
Such services open up very wide opportunities for quick completion of their IT products for all
companies who want to augment their ML expertise.»