Tracking customer behaviour and optimizing operations for better performance

About client

A US based business with a significant presence nationwide provides its customers a full range of architectural metals, gate hardware, and metal finishes. They offer a vast array of quality metal products from the premier manufacturers in Europe including wrought iron components, forged steel balusters, posts for railings & balconies, aluminum hinges and more.


The client noticed that it required much time and attention to establish firm control over multiple products under different departments.  

The key driving factor behind the poor resolution of issues was the lack of not having enough information on customer buying pattern and behavior which affected their estimation for production in the following year’s probable orders. Which means, having limited control over stocking.

The client was looking at a way out to efficiently handle its orders, manage stocks and increase quick sales in order to achieve its monthly sales targets.

They also felt the need to make quick decisions with pricing and promotions of their various product categories. Basically, a long-term solution that can indicate the company’s growth through data and manage this situation without compromising on sales.  Social DNA Labs was tasked with creating, developing and executing a robust predictive strategy to help quantify the future risk at a prospect-level.

What did we observe?

We first evaluated the client’s database landscape, and the existing workflow involved sales, logging, categorizing, and warehouse stocking. We found that there is a repository of fixed data under the control of various department which is isolated from the rest of the organization. A robust solution that can curate data across multiple channels could solve this Data Silo problem. Thus, freeing the enterprise from most of the critical complications.

How did we achieve it?

Using an intelligent Database Management System, we defined, manipulated, retrieved and managed the data in the database system. The rule to validate, update and manipulate this data was done using the autorun services in a timely manner.

Using the fourth-gen technology, the data was uploaded to the data warehouse, that is the central repositories of integrated data from one or more disparate sources. This was done for reporting and data analyzing. This process is considered as the core component of any business intelligence procedures.


There is an overwhelming number of stock valuation techniques available today.  For this industry, we required different valuation approaches. Hence, the profit per transaction calculation algorithm was implemented.

After collecting the Data from various sources, the process of inspecting, cleaning, transforming, and modeling the data with the goal of discovering useful information, suggestive conclusions, and to support decision making using Data analysis tools was applied.

The inventory database was updated using the past sales data to reflect in the current report system.

The reports that were finally generated after an elaborate processing and intelligent analyzing helped in decision making, relating to Inventory management, Store performances, Sales and Purchase Patterns of the customers.

What was the outcome?

The primary concern of tracking the customer buying behavior was overcome. Not only did time to time reports generated reflected the buying pattern, but also this helped in the decision making of the forecast orders.

The most frequent and profitable customer was identified too by viewing its frequency of buying products and services.

Controlled pricing and profitability to improve top- and bottom-line financial performance

Also helped in optimizing operations, improving service levels, and streamlining the IT

More benefits earned

Detected and prevented fraud in order to help the management avoid various risk within the organization.

Increased the effectiveness of the supply chain by aligning the purchase orders, production, and delivery schedules to consumer demand

Also, it helped in improving collaboration with customers, merchants, market, and suppliers as our approach gave them a holistic, dynamic result based on the latest market trend.


We can help your enterprise to do a lot more. Let’s talk and create a progressive technology roadmap for you.