There’s so much choice available that customers can pick and choose who they buy from and where, when, and how it happens. They want to discover, research, evaluate, and purchase on their preferred channel. Give them that option, and they’re more likely to choose you. That’s the whole point behind the multi-channel approach.
Westpac has partnered with data and analytics platform provider, Teradata, to tap into a new seam of big data within the organisation and further its customer engagement strategy.
Westpac is investing in Teradata’s Unified Data Architecture and Aster Discovery Platform technology to uncover patterns in very large datasets the vendor claims haven’t been possible using the banking group’s existing data analytics capabilities. The insights are being used to better Westpac’s personalised offers and services to customers.
The deal also sees Westpac developing new insights to reduce loss and fraud. The objective is to engage different parts of the organisation to draw on new analytics technology and data sources.
“Working alongside the Teradata team, we created a vision of the outcomes, quickly proved them and by engaging IT, defined the processes and architecture to ensure the technology swiftly delivered on the business promise,” said Rachel Rohlach, Westpac’s executive manager of CRM capability, CRM&D for AFS Strategic Marketing.
“We have been able to combine these new data sources with our existing ones and test new technology, such as Hadoop.”
Teradata general manager of advanced analytics, Alec Gardner, said its Unified Data Architecture was designed to allow IT to more rapidly test, process and provision new, large and disparate data sources that lines of business can then use for analysis.
He told CMO one of the key success criteria for the Westpac technology project was ease of use, and that business analysts could continue using the capabilities for further analytics initiatives across growing pools of structured and unstructured data.
Gardner said Westpac had been a Teradata data warehousing customer for many years and was drawn to the growing analytics product stack after interacting with the vendor’s US customers at its global customer conferences. The scope of the latest work was based on a business problem and how big data could be used to help investigate the issues on a larger scale, he said.
“As is the case with pretty much all of our customers, the first driver is marketing or communications, as they are looking at new channels to market and getting the new data sources,” Gardner said. “Marketing at Westpac was heavily involved here.
“But what the Westpac team was very conscious of doing – and the reason they have been so successful – is to ensure anything they did was easily deployed into production. Thus, IT needed to be engaged. The ‘steering committee’ for this project included IT representatives, and to ensure other people in the organisation benefitted from the data, a cross-section of different business teams were also sponsoring this including call centre, fraud and service delivery.”
While the “getting” part of the analysis work happened in a matter of weeks, and data insights were quickly available, translating these into actions does require an organisation to understand the context around that data and depends on the business domain deploying it, Gardner said.
“In marketing, you do want to be diligent and understand the context around the data. Just because someone is acting in a certain way in one digital channel, you don’t necessarily want to intervene without understanding the customer holistically,” he said.
Now that Westpac’s cross-section of business analyst teams can access further data streams, Gardner expected them to expand the types of questions they ask.
“The beauty of data discovery is that we’ve proven a capability for Westpac to let its analysts get new data, combine with existing data sets very quickly, and just keep asking questions,” he said. “Having introduced some new capability, there is now a kind of ‘community’ developing and a stream building up of new ideas, use cases and data sets. This should be a never-ending flywheel of constant analytical testing and development.”
Teradata’s big data capabilities expansion
Teradata has been ramping up its big data analytics offering in recent years, and acquired the assets of Revelytix and Hadapt earlier this year in a bid to broaden its Hadoop big data processing capabilities.
Earlier this week, the company announced an expanded partnership with enterprise data analytics management vendor, Cloudera, around technology integration and alignment, as well as a unified approach to go-to-market, sales and support under its Unified Data Architecture. Under the agreement, Teradata can also resell Cloudera's Enterprise Basic, Flex and Data Hub editions.
In September, the vendor scooped up US-based Think Big Analytics to bolster its big data consulting arm.
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