Elizabeth Moore is a senior professional marketer, specialising in the use of customer insights to drive business profitability. She joined Telstra Corporation in September 2011 as Director of Research, Insights and Analytics, where she runs the functions of market research, competitive intelligence and customer and product analytics with the goal of driving customer centricity into business decisions and turning the data assets of the business into profit and customer advocacy.
Liz will be presenting at ADMA's Data Day 2018 in Melbourne and in Sydney on Exploring Telstra's data-driven through-the-line (TTL) marketing measurements.
1. What is the most exciting development Telstra has worked on in 2017 regarding analytics?
For Telstra this year it has been about machine learning for marketing. We rebuilt our Market Mix Model (MMM) using machine learning techniques – this has allowed us to extend our detailed understanding of channel performance completely “through the line”. We now know the impact of every dollar that we have spent by channel, by segment, by campaign – at both a total level and at a marginal level. This allows us to make fine and detailed adjustments to our marketing spend to drive the right outcome. The model has allowed us to drive experimentation through every channel in marketing not just 1 to 1 channels. For us, it’s exciting because it allows us to take that disciplined approach to optimising what we are doing from direct channels and apply this capability in mass market channels, as MMM gives us the measurement tool to know whether the experiment is working. This work is applying artificial intelligence in a way that delivers very practical outcomes for us marketers.
2. What processes help Telstra extract and utilise the data to derive value for its customers?
Everything we do starts with our customers. And that’s how we provide the right experience for them. You start with your customer and look to optimise the customer experience around our products and services, you then start to think about what is the data and analytics that you need to make the decisions to drive the right customer outcome. What is really important to us is to understand how customers are using and buying our products, as well as the decisions that the customers are making along the journey, and then to identify what data and analytics we need to help support a great customer journey. So it is really about starting with the customers and then working back, rather than starting with the data.
3. Having worked in banking, communications and research, did you observe specific industry-related needs to develop best approaches to utilise data?
The industries I’ve worked in are predominantly service industries. They will inherently generate data through the way customers use and buy the products. There are similarities and differences. From a telecommunications perspective, I’m working with different types of data, because the industry has different products compared to banking and finance. I think what is interesting for me personally, and why I love telecommunications and technology, is that people love their technology and what it brings to them. People are waking up with their phones beside their bed, they’re not waking up with their mortgage beside their bed. You’re not necessarily excited about your mortgage. Whereas the technology that is enabling people to do lots of different things also enables innovation within the financial services. One of the big differences that I saw when I made the switch from financial services to telecoms is the real excitement that you get when you talk to customers about their telco and technology products.
4. What is your approach to the relationship between a business problem and data and analytics?
My approach is to be really clear about the problem we’re trying to solve, starting with what we are trying to achieve from a business perspective, then looking at the problem through the customer lens, and then identifying what analytics and data would be needed to help solve the problem. Our first port of call is to always look at the existing assets. Can we answer the problem by using the existing frameworks and models in our kit bag? If not, it’s then that we would look to build out new data and analytic assets. There’s always a vendor with a new technique or a new way of doing something or new kit which is interesting – but unless you’re grounded in helping to drive the business forward, then it’s very easy to spend money and time on interesting techniques which don’t add much value to the business.
5. Where do you see the biggest challenges and opportunities for Australian businesses related to the use of data and analytics for 2018?
For me, I think it is what I had just said about too much data. It can be seductive and easy to run off and buy cool kits and interesting techniques and different things that have been offered to you or arranged from different vendors. I would recommend having a data and analytics strategy which is aligned and focused on the business problems you are trying to solve, the customer experiences you are wanting to deliver and drive this back to that analytic strategy, and therefore the data strategy.