CMO roundtable: How machines will make or break your customer engagement success

At this Sitecore sponsored event, marketing and CX leaders discuss how they're working to personalise customer experiences, the role of data strategy and analytics in their success, and what machine learning will do to further CX aims


There aren’t too many Aussie marketers right now who aren’t trying to connect the experience dots and turn their customer acquisition craftsmanship into retention and advocacy. To get there, however, there’s a growing complexity of digital channels to navigate, increasing swathes and types of data to stitch together, and ever-rising consumer expectations to contend with.

Just how brands are faring in this quest to meet modern customer engagement expectations, and the machine learning and artificial intelligence (AI) will play in helping them reach such expectations, was the subject of a recent CMO roundtable and panel discussion, sponsored by digital marketing and experience management platform vendor, Sitecore.

In an initial panel presentation, Sitecore strategist, Anthony Hook, outlined the current and future state of AI and machine learning application and what marketing teams must have in place in order to harness their potential. This led to a whole-of-table discussion, focused on what’s helping and hindering marketers and CX leaders from customer engagement success

Excerpts of the roundtable and AI panel are featured below. You can find a slideshow from the Melbourne event here.

Building a personalised approach

Personalisation is a key element to customer experience success, and roundtable attendees reflected mixed levels of maturity when it comes to achieving it. Bendigo and Adelaide Bank head of customer voice, Ian Jackman, for example, rated the bank highly in relation to face-to-face interactions, and relatively low - but rapidly evolving – in relation to the personalisation of digitised and outbound communications. 

“For us, personalisation implies the ability to present highly customised content to customers that is relevant, valued and ‘in the moment’,” he said.

One way Bendigo Bank is looking to better understand what customers experience when they engage with the bank, and what opportunity exists to improve them, is a new customer metrics framework. This tracks key success measures across the categories of ‘attract’, ‘please’ and ‘grow’. 

“Many of the metrics are sourced directly from customer surveys and feedback,” Jackman explained. ”We have also recently implemented the IBM Watson Customer Engagement platform to leverage the customer insights and analytics, and enable us to respond to customer behaviour with relevant content across channels.”

Over at retail property owner, Vicinity Centres, two key areas of focus took precedence in 2017, general manager of data science and insights, Genevieve Elliott, said. The first has been a 12-month project identifying and understanding key drivers of shopper satisfaction nation-wide. 

Genevieve Elliott
Genevieve Elliott


“We have identified seven different shopper segments and are now using these to inform how we develop our shopping centre product,” she said. “The second area of focus has been on actual customer behaviour in our shopping centres, collected via our Wi-Fi network.”

There’s no doubt consumers are in the driving seat, something Vicinity has recognised in its corporate strategy, Elliott said. This puts consumer understanding at the heart of ongoing product development. However, historically, we have had an intermediated relationship with our consumers.

“Vicinity has had to develop a program to gather information about our shoppers in order to inform our new customer-led approach. This has meant significant investment in audience segmentation around shopping drivers, and the beginnings of an NPS [Net Promoter Score] program,” she said.  “But the greatest change has come through investment in data gathering technology.”

At Village Cinemas, investments into CRM and customer loyalty programs have been the data collection step driving personalisation improvement.

“To build on the loyalty data set, we on-boarded a customer data platform [CDP], and ingested all our key data sources into one pool, enriching our view of customer. That’s informing all customer communications and tactics,” GM of sales and marketing, Mohit Bhargava, said.

“The challenge is to ensure we maintain the balance between becoming too mechanical and placing an equal emphasis on tone and delivery, both digitally and physically. True customer experience is human and emotionally led in our business.”  

The PAS Group head of digital and loyalty, Anna Samkova, said the role of personalised messaging in near real-time has been highly impactful building engagement around brands such as Review.

“We moved from top-down conversion to personalised engagement,” she said, noting the use of the Oracle Marketing Cloud platform, Responsys, to assist. “With the help of LiveClicker software, we then took personalisation to the next level and now include dynamic content in our email communication.”  

Tapping data for insight

As a way of elevating data’s role in customer recognition and engagement, Vicinity Centres has been working to create a data philosophy and environment that will allow teams to better leverage existing and new data sets, Elliott said. Vicinity has also built a cloud-based data environment that includes a data lake, team of data engineers and data scientists. “This environment, coupled with robust governance, means we are in a position to surface data and insights that haven’t been available to us historically.”

At Bendigo Bank, a single customer view brings together core customer data and product relationships from a range of source systems, and includes 98 per cent of the group’s customers, Jackman said.  This underlying data platform feeds into our engagement systems. 

“We are continually extending this customer understanding through external datasets, interaction data, and analytical modelling,” he continued. “Most of the event-driven customer interactions we have automated so far relate to service or experience outcomes, alongside some sales-based interactions.”

Further steps being taken include bringing phone, digital and branch interactions data into the mix.

“This also involves connecting the new automated customer engagement platform into these channels to enable personalisation of these experiences,” Jackman said. “And we are transforming our underlying data architecture, which supports our digital and engagement platforms, to improve the speed, consistency and scalability.”

Jackman made the distinction between a single view of customer and a single view of customer experience.

“The former is an aggregation of what we know about the customer across our various products and brands. The latter extends this into an understanding of how and why the customer is interacting with us and the experiences that we are creating from the customer’s perspective,” he said.

“Achieving the latter is much more complex yet much more valuable when seeking to deliver personalised and relevant experiences. Customer voice is an important input into this deeper level of understanding, as is having technology to aggregate these experiences and an integrated set of capabilities across customer analytics, engagement and marketing teams.”

Staying relevant to customers has also become an overarching priority at The PAS Group, especially as customers expect continuous personal experiences that connect mobile Web interactions with brick-and-mortar ones, Samkova said. “We’ve integrated our IT platforms and created a central repository for our customer data which helps us to easily access and understand our data.”

However, Samkova said the group spends a lot of time focused on the creative and customer need, rather than just asking questions of data. “You have to have humans asking the right questions. The customer is at the centre of what the business does,” she said.

“Sales and profit are the outcome of this centricity. We use analytics to create unique user experiences by predicting the best offer, offer or content for each individual customer based on their profile, transactional and Web data. The next stage for us is to look at how we can get data about attitudes, behaviours and lifestyles.”

The challenges

As technology further pervades the engagement process, Jackman warned digitisation and automation can lead to a lack of empathy and customer connection. Another challenge industry sectors such as banking have to still overcome is a traditional product-focused versus customer-centred approach in relation to organisational structures, systems and processes.

Today, it’s about working on understanding customer needs and the ‘context’ of the experience, based on all of the interactions they’re having, Jackman said.

A challenge Village is working on overcoming is singularity in data analysis and decisions, Bhargava said.

“Only a few years ago, various business divisions were using different data sets and sources for their analysis, often diluting credibility of information stemming just from CRM data or marketing dashboards,” he commented. “It’s critical the data source being used by marketing departments are not seen as marketing analysis but rather as  accountable and acceptable to the whole business.”

As this journey has progressed, marketing has embraced metrics that matter to the business and product owners, Bhargava said.

“That said, we have a company wide NPS measure is place which ensures there is a clear focus on the customer across the board,” he said. “This shift in our language and reporting has helped garner stronger relationships and alignment across the leadership group.”

Elliott is another who believes measuring customer satisfaction in a robust and reliable way is key to driving any valid focus on customer experience.  Having just kicked off its own NPS program, Vicinity’s vision is to develop this into an experience index correlated to traditional financial success metrics. 

“In addition to this, our investment in Wi-Fi technology is providing metrics we haven’t previously seen, such as dwell time and frequency,” she added. “Once we understand the relationship between these metrics and commercial success measures, we will be able to deploy strategies and tactics that influence these.”

Up next: Getting a grip on AI and machine learning

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