Macquarie Bank has raised the possibility of a ‘next-best action’ suggestive system for its sales, marketing and customer service teams, using tools from Salesforce and Tableau.
Chief data officer Ashwin Sinha told the Tableau Live Asia Pacific summit that the bank, as a longtime Salesforce user, hoped to take advantage of new ties between Salesforce and Tableau; Salesforce acquired Tableau back in 2019.
In particular, Sinha said he saw potential in the use of Tableau CRM, a rebrand of what used to be known as Salesforce’s ‘Einstein Analytics’.
“One area [of opportunity] we are really excited about is we are an extensive user of Salesforce, and what we would like to do is make sure that our sales, marketing and servicing team have more real-time insight and analytics using capabilities like Tableau CRM,” Sinha said.
“[Tableau CRM] combines Salesforce and Tableau capabilities together, and makes that information available to a lot of the users across the Salesforce community in real time, instead of taking that through Salesforce into a data lake or data platform and then into a Tableau dashboard.
“That is something which we are looking forward to, and it could drive things like next best conversation and next best action for this user community.”
It takes what an organisation knows about its customers - such as via their activity or the products they use - and uses analytics to suggest the most effective way to engage with that customer.
In addition to wanting to make better use of closer Salesforce and Tableau integration, Sinha said the bank saw opportunities more broadly to increase its use of machine learning models, although he did not go into detail on where specific opportunities lay.
“I think we can achieve a lot more as a bank with better use of machine learning and analytics in a number of functions,” he said.
Both activities fall broadly under an ongoing data transformation that Sinha is leading at Macquarie Bank, which is part of Macquarie Group.
“A data transformation really never finishes so we continue to learn, adapt and look at new opportunities across the bank where we could drive data-driven decisions and improve our business processes,” he said.
Sinha noted the bank had established a “strong data foundation”, albeit one that was flexible enough to support new tooling if required.
“The technology and approach in the data space is changing very rapidly so the tools and tech which we use are going to change in a couple of years time,” he said.
“It is important that when you think about the data architecture: it is flexible enough to accommodate and adapt to these changes?”
Other efforts were focused on talent acquisition to support the ongoing works, on meeting user expectations, and on keeping things simple.
“Question the purpose of every data asset and artefact, and what actions and decisions these artefacts are going to support, otherwise you could create a lot of unnecessary assets,” Sinha said.
Sinha added that Macquarie Bank’s data transformation had produced strong “commercial outcomes” in areas such as customer service, sales and marketing and fraud prevention.
“But the thing which I feel really proud about is the empowerment of users,” he said.
“What I feel really proud about is when we are running leadership meetings at Macquarie Bank, in a lot of these meetings we have got live dashboards, which are being used to drive those discussions.
“In these leadership meetings, we are looking at Tableau dashboards and looking at our performance, key improvement opportunities as well as risk drivers to understand what are the steps and actions which we could be taking.”