Computers and artificial intelligence have come along at an exponential rate over the past few decades, from being regarded as oversized adding machines to the point where they have played integral roles in some legitimately creative endeavours.
Brands ramping up their analytics capabilities need suitable frameworks in place to translate data into business insights that can be actioned by the right teams for maximum benefit, Bupa’s strategy leader claims.
Potta Findikidis, the healthcare provider’s head of market strategy and planning, told CMO one of the big challenges organisations face with the rise of data-based decision making is the operational connection between analysing and interpreting.
Findikidis will join a panel of Australian brand representatives to debate the best ways of unlocking big data at the forthcoming Consumer Intelligence and Analytics event in Melbourne on 22-23 August, at the Park Hyatt Melbourne.
“You can have a lot of analytics effort going in and pieces of information coming out, but if these outputs are not delivered or interpreted in the right way, they’ll either end up in the wrong part of the business where action is taken that didn’t need to be taken, or fail to get to the right decision makers,” she said.
“The more you can wrap the data mining and analytics around a structure and have it aligned to strategic priorities of the business, the more traction you’ll get.”
Findikidis boasts of a strong background in strategy and marketing, including 16 years at Telstra working primarily on customer segmentation and execution. She joined Bupa in 2011 to oversee the new planning and strategy team, which sits within the marketing function.
From a planning perspective, staff are responsible for pulling together the annual integrated marketing plans from across its product, marketing, digital, retail and customer acquisition functions, governance, reviewing business performance, and creating strategic priorities to execute against.
The Bupa team’s second, growing focus is building deeper customer segmentation and profiles using data analytics and research. Findikidis said its ambition is to not only improve existing relationships, but also drive customer acquisition by better identifying the markets Bupa needs to play in.
The catalyst for developing a strategy team was the merger of HBA, Mutual Community and MBF under the Bupa brand, and its repositioning as a healthcare-oriented business. “Now that the rebrand has been done, it was time for the business to take that to the next level and better engage with the customers – not only existing members moving from the old to new brand, but also how we provide more reasons for potential customers to choose us,” Findikidis said.
As a first step, the team has spent the past year building a deeper understanding of the reasons why consumers choose and leave Bupa using data and research. This work has since been used to develop firmer segment-level propositions for each of Bupa’s target marketers, such as youth and elderly consumers.
“We fed the core insights and data we uncovered through doing this research into emotional and rational drivers, which help us create those customer-level propositions,” Findikidis explained. These are being used to develop more relevant marketing campaigns, as well as product offerings.
While it’s early days, Findikidis said the team will measure its efforts against improving its net promoter/advocacy scores, as well as its ability to make Bupa top-of-mind in terms of brand consideration with consumers.
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For Findikidis, big data is about uncovering sizable insights and pieces of information her team can draw conclusions from. This could be around improving satisfaction, increasing customer service, putting something new into the market, or an untapped opportunity.
As a result, data is only effective when it’s pulled into a “story” that presents an opportunity for growth. Findikidis pointed out a data point is not an insight in itself, but one of many different dots organisations need to join up.
“If you don’t centralise how you manage data, you can get caught up going after something tactically and not have a strategy behind it,” she claimed. “Actioning data may then not be the right thing to go after because it hasn’t been sized up appropriately. You could wind up spending a lot of time and effort on data that makes no commercial sense to the business, or has no impact, or has no positive outcome for customers.
“To look at data in isolation is dangerous. Unfortunately, we do sometimes look at data in a fragmented way and don’t draw the right conclusions. You need to create the right strategy before you start actioning the data.”
While the right approach is dependent on the type and size of business, Findikidis advocated business units working with analytics team in a client-supplier model. In the case of Telstra and now Bupa, analysts feed their data outputs into the strategy team, which is then responsible for collating those into actionable insights.
“Having a team to tell the story in alignment with business priorities is a much more successful model,” she added. “If there’s one thing that motivates analysts as well, it’s producing something and uncovering data that is then used.”
The other thing Findikidis warned against was trying to achieve to an absolute data point before making a decision. “An ex-Telstra CEO once gave me a great piece of advice: ‘If you have 60 per cent of the answer, go for it’,” she said.
“For me it comes down to getting that balance of data-driven decision making, and ensuring you’re still being agile in your approach to market. You really need to understand your customer as well as use data points to support what you’re going to do.”