Big Data ‘Equals’ Big Things for Energy Providers Across the Globe

Published: Fri 30 Oct 2015
A blog entry by Brad Langley

Contributed by:

Brad Langley
Director of Corporate Marketing
Tendril

Brad Langley's Blog

Brad Langley, Director of Corporate Marketing and Communications, Tendril

Big Data is revolutionising consumer engagement and creating new revenue streams for businesses across many sectors. But, where does the opportunity lie for utility companies and how does it apply to our sector?

To start with, let’s take a look at how Big Data analytics was embraced by Netflix, and how energy companies can take a similar approach to help develop and serve customers more efficiently.

Learning from Netflix

Before Netflix succeeded, it predicted it would. According to Tata Consultancy Services 2012/2013 Big Data Study, Netflix analysed reams of customer data to develop its proposition. For instance, it scrutinised a range of factors including: what customers watch; how they rate content; what they stream; their location and their social media discussions. All this information helped inform and define their product and go-to market strategy.

One specific TV series that Netflix delivered to the market was the remake of the 1990 BBC miniseries, House of Cards. It delivered this based on data that revealed customers had a high interest for the series to be remade, starring Kevin Spacey in the lead role of Frank Underwood. This revelation resulted in the successful comeback of House of Cards, which grew to become Netflix’s most streamed web content in the US and 40 other countries.

As a consequence, after its premier in February 2013, and during the first quarter of the same year, Netflix increased its subscriber-base by 7 per cent (2 million) over the previous quarter.

But, what does House of Cards’ success have to do with the energy industry? The point is: energy providers can use a similar Big Data analysis model that Netflix used to improve their own bottom line and develop better products and marketing campaigns.

The same Tata study revealed that the energy industry is one of the least advanced when it comes to Big Data immersion and application. This means there is a massive opportunity for the industry and energy providers to reconsider their approach to customer management and take a leaf out of Netflix’s book.

Naturally this is easier said than done. So, what should energy providers consider if they would like to explore developing more personalised offerings for customers?

Let consumers take centre stage

Energy providers have access to terabytes of consumer data. They need to put it to use and make it work for them. Typical data records include: billing histories; past program participation records; demographics; home construction details, as well as several other key pieces of data.

As with our Netflix example, energy service providers need to establish how to use this information. The way to achieve this is by placing the consumers – and their data – at the heart of everything, and use that shift in focus as the catalyst for transforming product development, marketing and implementation. So, the requirements are: consumer-centric technology platforms that drive consumer-centric operations.

The problem with regression modeling and averaging

When offers were developed in the past (even now), data analysis systems relied solely on regression-based modeling and averaging. However, the problem with these approaches is that they don’t single out consumers for specific, relevant offers.

Therefore the crucial missing piece of the puzzle in these old data crunching systems is the analysis of actual home data (home simulation models). Which is why newer home simulation models are better. They can assess an array of data such as the impact of a particular home’s insulation; window design; heating configuration; and thermostat set points.  

Based on these findings, the home simulation models can offer specific alterations that advise individuals on how to achieve energy saving goals and enable utility companies to determine what types of products and services would best meet their needs.

Your technology platform is key

A strong technology platform should form the basis of these actions. Typically, these should combine all the pertinent home data with behavioural metrics and enable energy providers to micro target, segment and personalise programmes and services to individual consumers.

Micro targeting narrows down offers

Micro targeting enables utility companies to narrow the pool of consumers designated to receive particular offers. And the aggregation of home and behavioural data generates propensity scores—numbers which indicate how likely consumers are to respond to specific energy programs.

So energy providers are then able to reach out only to the consumers with the highest propensities to respond to their marketing campaigns, avoiding wasting precious marketing investments on uninterested audiences, resulting in immediate increases in response rates.

Segmentation leads to better messages

Micro targeting segues into segmentation and it is at this crossroads where data analytics enables energy providers to break down target groups further; so that even more tailored messaging can be developed.

For example, within a designated target group green-minded consumers may receive one set of messages, while young parents trying to reduce costs may receive different messages. Segmentation ensures all communication is relevant and personalised to their intended audiences.

The power of personalisation

Therefore, since the ‘home simulation model’ enables personalisation on an individual level, energy providers can offer more detailed, customised, and attractive deals for potential customers.

It is these predictive models that can make the difference between successful customer engagement campaigns.

Engage more and lose less!

Furthermore, when Big Data is used to micro target, segment and personalise energy providers’ offerings, customers will also almost certainly take an interest in reducing their consumption and consider purchasing other energy-related products and services.

This means there is more opportunity for energy providers to cross-sell and up-sell additional products and services that add value to their individual consumers. Energy providers, in turn, see better financial results, retain existing customers and add new ones more seamlessly.

Conclusion

Netflix proved it is possible to build an organisation and its offerings on data, and there is no reason why utility companies can’t do the same.

Therefore, to benefit from integrating Big Data analysis, energy providers must adopt the technology platform that, above all else, puts the consumer first and which enables the utility to personalise everything, from analysis to offerings.

Tendril will attend European Utility Week in Vienna, 3 – 5 November and will provide insight on how energy providers can leverage dig data analytics to develop more customised propositions for customers. Please visit stand: B.b53.