In my last blog series, I explained the challenges companies face when attempting to combine and analyze data from different sources within Hadoop, and why a source-agnostic approach to analytics is needed. Today, I’d like to introduce you to Novetta Entity Analytics, the new release of our advanced analytics application that connects structured, semi-structured and unstructured data within Hadoop, and enables powerful analytic queries that weren’t possible before.
Gain Unparalleled Clarity into Enterprise Data and Actionable Business Intelligence
Novetta Entity Analytics performs large-scale data integration and entity resolution and analysis to form multi-dimensional views of persons, organizations, locations, and events enriched with the complex relationships between these entities. With Novetta Entity Analytics, organizations gain unparalleled clarity into enterprise data, and are able to obtain actionable business intelligence to better understand and connect with their customers.
Novetta Entity Analytics can add tremendous value to customer analysis by enabling new data sources to be added to existing business processes, so that combined data sets can be segmented or grouped based on additional parameters.
For example, a manufacturer may want to know which customers to target for special offers while minimizing the number of untargeted offers it sends them via email or mobile device. The goal of the special offer might be to direct customers to channel retail partners to help them reduce inventory. Analysts at the manufacturer might want to look for customers who:
- Completed at least four transactions in the last year, worth more than $500 in total purchases, either direct or through channel partners.
- Abandoned at least three transactions within the last 3 months, after placing items into their online shopping cart.
- Are within five miles of a retail partner that offers those abandoned products.
Without Novetta, analysts could get this information today, but it would require tying together data stored in enterprise data warehouse, master data management, and log analysis systems, and then querying that data. This approach is extremely complex and expensive.
Easily Create a Unique View and Relationships for Enhanced Customer Analysis
With Novetta, the data would already reside on a Hadoop platform, so analysts could easily create a unique view of customer, channel, location, and product entities, and connect those back to transaction data. These profiles could be quickly enriched with the relationships between these entities. Business segmentation rules in Novetta Entity Analytics could then be applied to distill the billions of records into the subset of customers that should be targeted with the new offer. An example of the type of business logic represented in these segmentation rules is as follows:
Is the customer in a specific geographic area? If yes, do they meet the minimum number of completed transactions of at least $500 via any channel? If yes, have they abandoned their online shopping cart three times in the last 3 months? Are any of the abandoned products available at a retail location within 5 miles of this geographic area? If so, add this customer to the group that meets these criteria.
Gain Additional Insights Through Campaign Analysis
Once this segmentation is complete, analysts could provide these customers with a special incentive. If analysts do not have a good understanding of which offers these types of customers have responded to in the past, they could perform a campaign analysis to determine the best incentive to offer. Since these customers have recently abandoned several online transactions and are within 5 miles of a store that carries those abandoned products, the company might offer the group a special promotion to visit the store and make a purchase. Customers are more likely to purchase high-priced and high-touch merchandise, such as jewelry, consumer electronics or furniture, in a store where they can see or touch the products. And, since the manufacturer is already carrying inventory costs on the items in the store, this type of offer could help to increase revenue and lower costs for the company.
Without Novetta Entity Analytics, this type of customer analysis is extremely difficult and cost prohibitive. With Novetta Entity Analytics, running on Hadoop, companies can easily and affordably connect all of their data from internal and external sources, and segment the data to precisely target the individuals or locations they need to reach to achieve specific business goals.
Stay tuned for my next blog post, where I’ll discuss how Novetta Entity Analytics makes these types of advanced analytics possible through a combination of its source-agnostic entity model, data characterization, relationship detection, built-in intelligence and knowledge transfer, and scalable and parallel architecture.
For more on Novetta Entity Analytics or NEA, visit www.novetta.com/entity-analytics.
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Novetta Entity Analytics: Industry Use Cases