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Published April 18th 2016

Interview: How EDF Energy Turns Big Data into Actionable Data

We spoke with EDF Energy's John Hunter to understand how social data helps the energy giant measure success and inform business strategy.

EDF Energy is one of the UK’s largest energy companies and the largest producer of low-carbon electricity.

The company supplies gas and electricity to 6 million business and residential customers and is the biggest supplier of electricity by volume in Great Britain.

We sat down with John Hunter, the digital and social media manager at EDF Energy, to understand the role that social intelligence plays at one of the UK’s largest energy suppliers.

In such a large enterprise, a decentralized approach is taken in which John is part of a team of five who oversee all digital communications across six business units, with teams ranging in size.

EDF Energy

John spoke of the main challenges in his role at EDF Energy. Firstly, ensuring teams are able to measure success; to have a proper measurement framework in place to understand the ROI of social media and digital.

Secondly, to ensure they have the right tools for the job.

And finally, to ensure the right strategy and processes are in place for effective use of social media and digital in general.

Measuring success

To address the first challenge, the team has to define how to measure success and then be able to handle the scale of the information they have at their disposal.

“The evolution of social media has changed everything for business, we now have a great opportunity for dialogue and creating relationships.


The scale of that is the biggest challenge… and how to best serve our audience in the right way. From delivering social customer service or making sure that the facts are represented correctly in large media announcements.”

In order to measure success, EDF Energy developed a digital communications strategy, called the playbook, “which anyone in the business can pick up and understand what we’re trying to achieve within social”.

It breaks down both the audience and the team’s social outputs, making the data more manageable.

EDF Energy places a high importance on its audience trusting it as an energy supplier and generator.

Trust and trustworthiness are hard things to measure, but the team has overcome this challenge by developing a measurement framework.


Metrics include customer service efficiency, sentiment and reputation, audience growth, content performance and general social discussion.

The framework has been designed to measure each of these different aspects of its digital strategy, based on KPIs. These five social metrics and the total index score allow the teams to fairly benchmark and position themselves within the market.

The dashboard is exported to a spreadsheet, allowing the team to create an index that can be presented to the business. Movements can be reported on, and the regularity and index score add visibility to the work of the social team.

Data in context

Social data is also given context by segmenting the audience it reaches, splitting online activity into subsections of the audience, media, and industry landscape.

Further context is added by not taking any one data source in isolation. Data from Brandwatch is combined with web statistics and sales data.


Scale and context were recurring themes during the interview.

There is so much social data available that it can be difficult to gain insights from the huge volume of information, or alternatively, fixate over the miniature and fail to see that it does not represent the wider picture. Providing context to the data makes the scale manageable and allows better decisions to be taken.


This categorization allows for an immediacy provided by automation.

By setting up Categories and Tags in Brandwatch and using Alerts and Signals, the segmented data is available straight away. Whether that’s someone in the social team or a senior stakeholder, they can quickly bring up a Dashboard that delivers real-time information.

“That’s really powerful for the business to be able to make the right decisions at the right time because a lot of problems can arise where people don’t have the context.”

Robust decisions can be made at the optimum moment when real-time information is delivered in context. John advocates doing the hard work early on, allowing anyone to quickly access the information when it’s needed.

A senior manager might go onto Facebook or Twitter and see something that will alert them and have them worried. The social data allows them to see the bigger picture. Without that context, there is a risk of an overreaction.

Without categorizing what is being said, the data can be overwhelming.


As John himself says, “Everybody talks about big data, but it’s actually not about big data, it’s about finding the valuable data, the useful data.”

Categorized data

Mentions can be split into broad, top-level Categories such as media related mentions, power station related mentions, environmental mentions and so on.

Within those main topics they can segment again, to pull out sub-categories. So the consumer mentions will be further subdivided into different types of complaint and different queries.

These smaller amounts of data can then be analyzed in real-time, as the data comes in manageable, related chunks.

This has allowed the team to feed this specific knowledge into areas of the business, such as improving customer experience.

Even smaller issues, such as a number of people complaining on social media that they didn’t like the hold music when calling customer service – this sort of insight is something that would never have been known without social data, and is highlighted by segmenting further and further from consumer related mentions to environmental and campaign based mentions.

Social customer service

Granularization of the data has also been able to demonstrate the growing need for social customer service. This evolution of customer care has been felt by a lot of brands and has been driven by demand from the customer side.

John’s work has highlighted that social customer service is growing, but also moving away from direct questions from consumers to brands.

Flossy buttlet in the form of question mark

Some forms of conversation, such as @mentions or questions posted directly to brand channels, are easy to pick up and respond.

However, there is a lot of talk about the brand that is not directly aimed at their social channels, but good customer care should pick up these mentions and engage.

Listening out for these mentions has allowed EDF Energy to demonstrate the need for a full-time social customer service team, which has seen response times halved and response rates go up to nearly 100%.

Reputation management

As part of the digital communications plan, EDF Energy has created a reputation comms plan.

By brainstorming any potential event or crisis and their solutions, EDF Energy developed a severity matrix for a large number of scenarios that inform the appropriate actions should an event be triggered.

When an incident begins, inputting the numbers from Brandwatch into the matrix will tell them the level A-D. There is a large number of scenarios mapped out, and suggested responses based on certain situations.

“Using those processes and the data that we get from Brandwatch, about eight out of ten online situations that would have been classed as a crisis are now not a crisis situation anymore, because of Brandwatch and because of the severity matrix that was put in place.”

That change has again come about from the ability to measure and categorize.

Sometimes an incident will be highlighted by a stakeholder. While the post or topic was quite sensitive or had the potential to increase in severity, plugging the numbers into the matrix allows the team to place it in context, looking at average mention counts and so on, and establish that it isn’t going viral and doesn’t represent reputational damage to the brand.

By segmenting data into smaller packets that can be measured against the framework or plugged into the matrix, big data becomes manageable data, and useful insights are revealed.

By doing the heavy lifting early on and setting up automation, these insights are available in real time, allowing an agile approach that helps drive a successful digital strategy.

John is very positive about the future of social media and cannot wait to see what new developments happen this year and how to analyze and draw insight from the new activity.

“Working in an ever changing world is great for me, as I am constantly developing and no day is ever the same. There is definitely no time to be bored!”

Thank you to John for speaking with us. This interview is one in a series with industry experts – you can expect more every week.

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