Analytics 2.0: New vendors, New customers?

Published By : CIOL

The rise of predictive genre and thus new players to fill some nooks and corners of the city called Analytics is hard to ignore. The plot turns another new page as CMOs enter the stage too.

What’s new about new

IBM Research – India started putting its capability into Edge Analytics, which it tags as a lightweight, non-intrusive and pluggable technology that connects a bank’s customers with contextual information on the go and in real time, it cross-references where the customer is with what he or she is doing to provide useful insights and location-based recommendations, such as offering a discount at a specific store.

“It could also alert the bank about customers who use a competitor’s credit cards (causing “capital leakage” in bankers’ terms) and offer incentives to use their credit card, instead. Or, the technology can identify customers with home or auto loans with other banks (more “capital leakage”), and offer them refinancing options. Edge Analytics is embedded within participating banks’ customer channels, such as Net Banking, ATM, SMS, Phone Banking, etc.

When the bank’s customers access their account on these channels , Edge Analytics uses transactional and other contextual data feeds to better understand the customer’s transaction behavior and preferences, for example to detect customer’s transaction location in real time or infer the transaction category and spend pattern, preferred shopping location, preferred restaurant or cuisine, etc. These insights help the Bank understand their customer transaction behavior and priorities better. After all, one needs an environment that should have a ready-to-use system , with good data quality and no conflicting data sets or incomitant data,” explains Vishal Batra from IBM Edge Analytics.

“Then, users who are the consuming end of analytics are usually business people with no background or inclination for complex SQL queries. Data is structured in tables and retrieving it is a task. It can become slow for business users to dice and slice this data with no real-time mechanism whatsoever to analyse customer behavior.”

That made the company work on and come out with something that it calls easy to deploy, agile with business scenarios and something that can work on good integration. It is useful when an enterprise customer wants recommendations usually capable only from in-house systems even as most only use third-party boxes.

Another attempt with a new angle at analytics space can be spotted with Fractal Analytics.

It has a Customer Genomics solution, which as it states, helps marketers learn complex customer behavior at an individual level. “The proprietary pattern recognition and machine learning algorithms underlying Customer Genomics learn from every transaction and customer interaction including from social media helping marketers build a dynamic 360 degree view of the customer across attitudinal and behavioral dimensions. Customer Genomics has enabled a major US retailer in doubling coupon redemption and driving significant incremental store traffic.” A confident Natwar Mall, Senior Vice President, Fractal Analytics explains.

The company shows up a report card of y-o-y growth of 70 per cent working with top 30 Fortune 500 companies. Its users vary with 51 per cent from FMCG/CPG and retail; 44 per cent from Financial Services and Insurance/BFSI and five per cent from Technology.

“We believe analytics is critical to develop a deep understanding of consumers and earn customer loyalty, and make better data-informed decisions. We help businesses to understand, predict and shape consumer behavior through advanced analytics; improve effectiveness of marketing, pricing and supply chain management; and harmonize data, tell visual stories and forecast business performance.” He adds.