A visit to the cinema, a browse across the breaking news pages, a purchase on an ecommerce site: all interactions that can be converted into data or metadata and then processed and analysed. Yet data is only numbers without the right systems, processes and people behind it. Without these ‘intelligent’ elements, a marketer ends up with a wealth of figures but no real insight.
At Marketing Week’s Data Storytelling conference in November, brands such as Disney, eBay and The Telegraph will explain their approaches to these business-critical issues. We asked for a preview of their presentations.
Disney: deriving consumer insight from unstructured data
If anyone knows how to tell a good story, surely it is entertainment behemoth Disney. Behind the scenes Richard Ellwood, EMEA head of audience strategy at The Walt Disney Company, surveys the brand’s many different data sources to understand consumers, answering questions around what their motivations are.
He works to contextualise and extract the most relevant aspects of that data. It is then about using these data points either proactively to try to inspire some thinking, or to validate strategic moves.
“Data on its own is not intelligent. The intelligence comes from recognising what are the appropriate variety of sources to include and for each of these, ensure you work with the data specialists,” Ellwood argues. “To be really effective, you need to understand what are the strengths or the quality of different data points and really importantly, what are the limitations of the different data points.”
For the teams at Disney, this means being very selective about the data sources it integrates For example, with Star Wars the strategy is to use data points from the box office, trailer, social media and TV ratings alongside engagement figures so that they are not necessarily looking only at relationships but using data points to understand different audiences.
Ellwood’s preferred approach is a combination of big data and qualitative exploration. If he was looking at Star Wars data, he would be focused on understanding what people are talking about, what is resonating, what is driving behaviour. He then builds on that to ask the right audiences the right sort of questions to establish marketing strategy. This exploratative data is rich and helps answer the ‘whys’ behind the ‘whats’.
Getting the best out of the data requires the right data specialists at both the input and analysis end. It is crucial that marketers working closely with data can contextualise it by working with the experts to ask the ‘so what?’ questions and validate hypotheses.
“It should be that by going through that process you find the inspiration for a new route or opportunity,” says Ellwood. “The whole point of using this data is to hopefully drive positive change. If you are able to use data intelligently, you can deliver more benefit to consumers particularly in terms of greater personalisation, content or product.”
Ebay: using shopper signals to segment by purchase stage
Rather than being constrained by big data, brands that learn how to harness it intelligently can provide an offer that is much more compelling and personalised. Ebay’s director of EU advertising strategy, product and operations Phuong Nguyen argues that intelligent data is made up of two parts. “First and foremost, it is driven from a quality data source,” he says. “Secondly, it is the ability to use that data to make accurate predictions.”
Nguyen thinks about intelligent data as a combination of observed and inferred data, married together by people with skills for understanding shopping signals and the ability to make predictions around future shopper intent.
“At eBay, we have one of the most prolific digital shopping experiences across our various platforms and as a result, we are empowered with – what we believe to be – one of the greatest consumer depositories of data on the web,” says Nguyen.
Ebay’s targeting tools break down audiences commonly grouped together as a whole into niche segments, allowing brands to identify exactly where shoppers are on their purchase journey, and target them with products accordingly.
For example with the consumer segment of new parents, eBay has analysed signals based on different purchase behaviours in order to make predictions on what stage of pregnancy or parenthood a new parent might be in. With the knowledge that a shopper bought clothes for a newborn 12 months previously, eBay can predict when these customers are likely to be in the market for clothes for one year olds and target accordingly.
In order to spot the best stories within data and find the really tangible insights, eBay takes a combination of two approaches. First is the hypothesis-driven insight, which is always an important – and logical – way of developing stories. Nguyen then argues there is value in a serendipitous approach to data storytelling, which is especially important to help realise things that you are not expecting to surface, and which your competition is not spotting.
“It’s often helpful to go ‘data-foraging’,” Nguyen says, “jumping into the data to mine the unexpected nuggets and unusual fluctuations before you can wholly understand the stories the data is telling.”
The Telegraph: bringing data together to build new processes
The quest for providing a profitable product through engaging with consumers in a relevant and personalised way is one familiar to The Telegraph. The news brand harnesses data to help give a deeper understanding of its audience and content.
“Businesses are drowning in data, but intelligent data is about knowing which is the right set of data for a given question, and that it can be accessed at the right time by internal systems, to facilitate a valuable interaction with your customer,” agrees Mazelle Siton, director of audience insight at Telegraph Media Group.
There are four key uses of data internally that help maximise opportunities. The first of these is ‘exploration’ – looking at what audience behaviours and trends are being signalled. The second is ‘investigation’ and is about using existing data in the business for audience intelligence. The third area is ‘monitoring and performance’ and is about timely release of structured data via reports and dashboards. The final area is ‘development, testing and optimisation’, where hypotheses are generated through the exploration, investigation or monitoring and performance stages about what could be improved.
Another story familiar to many is the need to determine the right material from all the big data available. “Getting to that valuable view is about making sure you are bringing as much of your data together, so the different views of your audience and customers that live across the business help enrich each other,” says Siton. “The other [key challenge] is about operationalising it all, turning it into models and rules that are plugged into your different systems so it can happen automatically.”
In order to work intelligently with data, organisations need to adhere to some key principals, argues Siton. The first is about big data storage. To be able to store and work with data you need a big data platform but also skilled data engineers who can help build and maintain the platform. For The Telegraph this covers things like very granular on-site behaviour, content metadata, known and declared customer attributes, purchase data or advertising performance data.
Skills and resources are crucial to doing the necessary analytics work to find the really tangible insights, help answer the key business questions and turn this information into models, rules and predictors.
This work is then put into action. “The next step to working intelligently with data is making those rules available in systems that allow actions, and setting them up so that they can happen automatically at the point of interaction with a customer,” explains Siton. “For us, this could be something like making sure the most appropriate content is recommended to a reader whilst they are on site or key audience segments receiving certain communication and relevant advertising.”
It pays to put on the thinking cap. Ultimately, harnessing and bringing the data to life in this way can really make a difference to the business, brand and bottom line.
Richard Ellwood, Phuong Nguyen and Mazelle Siton will be among the experts delving into the biggest data marketing topics at Marketing Week’s Data Storytelling Conference & Awards on 1 November. Click here for more information, including how to book tickets.