In the velociously evolving digital era, it is now common for retailers to have an Online, in-store and App-based presence. With millions of customers interacting in various formats, the data generated for the retail industry is massive.
IGT has observed that the data sources come not only from the customers, but also from various enterprise channels such as ERP, CRM and various sensory and IoT devices along with social channels considering the Audio/Video formats as well.
The disparate data sources, along with widely varying data formats and frequency of data generation from each of the sources, poses a challenge for systematically storing and then deciphering the data to make business sense to the Data Engineer.
To resolve these challenges faced by Retailers, the Data Engineering team from IGT provides extremely well-suited techniques to resolve this. To be able to explore the full capability of Data Engineering, the retailers can choose to host the data on the Popular Cloud service providers such as Amazon, GCP and Azure. This ensures that a Data Engineering suite available on the cloud platforms can be leveraged in either proprietary or open-source options.
According to the IGT Data Engineering team, the first challenge is to ingest the data sources whether Internal or External using data ingestion tools. The data sources can be Unstructured, Semi-Structured or Structured. Once the data is ingested, the next challenge is to verify the rules of data governance that include information catalogs, data privacy, data quality, etc. The data is then transformed into what is called Normalized data which is turned into what is called a Data Lake which creates and holds a data model that is structured.
Now that there is structured data available in Data Lake, this data can now be used to create application data services using Data Science Workbench, Analytics Workbench to name a few.
The end clients can acquire customized dashboards and AI solutions to gain insights on their numerous pain points such as:
- Uncertain buying patterns
- Emerging market trends like augmented reality, merchandising.
- Price optimization challenges.
- Sales and revenue
- Realtime data availability
The powerful outcomes of our data architectures result in intelligent apps which touch-bases the distinctive portrait of the buyer, highlighting all the buying patterns.
IGT has recently worked on one such case for a large retailer from the Caribbean region. IGT created a database for the customer using “Customer Sentiment Analysis”. Our analysts deployed algorithms to perform sentiment analysis which emphasized the improvement in line of products and the marketing strategies as well. This analysis was powered by models using online surveys on online tools. It also helped in monitoring and elevating the brand position. Powered with our Data Engineering and AI technologies, we helped our client make smarter decisions to boost overall customer service and satisfaction.
Reach out to us via www.infoglobaltech.com to understand how we can help.
Leave a Reply