10 May How to Overcome the Challenges of Data-Driven Digital Energy Marketing
by: David Engfer
Today, the retail energy industry seeks novel ways to differentiate, build and maintain personalized relationships with prospects and customers through digital channels. The goal is to lower acquisition and retention costs while also improving the customer or prospect’s experience. Organizations trying to achieve the ideal customer “segment size of 1” are drowning in a rapidly growing marketing technology (“martech”) landscape, leaving them scrambling to both control and drive value from their most important asset – data.
Recent advancements in marketing technology surfaced new ways to drive value and differentiation for energy retailers. Customer/prospect segmentation, web/e-mail content marketing, social media campaigns and web search optimization are all examples of powerful capabilities at the disposal of the digital energy retailer. The martech arena, however, has experienced an explosive 5x fold growth over the past 8 years, both overwhelming marketers with tool sprawl and creating data integration challenges for technologists.
The abundance of tools in use within organization creates data silos, further splitting and stretching the customer profile across the enterprise. This data problem leaves organizations challenged with applying personalization while still maintaining marketing agility. So, what’s the silver bullet?
Unfortunately, no silver “one-size-fits-all” bullet exists. There are, however, three key considerations to addressing the challenges presented by hyper-fragmentation of marketing technology in your organization. Tackling these will get you well on your way toward a cohesive digital marketing strategy that supports higher online conversion:
1) Prioritize Product Personalization – According to market research, a 5% increase in customer intimacy and retention can yield a 25-90% increase in revenues. Therefore, energy retailers must build loyalty and rewards programs that target customer benefits over time. Metrics and KPI’s should focus on increasing customer lifetime value – not just new customers. Automation campaigns must be constructed with personalized behavior-driven content. Companies must offer creative products and services that are founded in customer retention and the unique/ individual needs of your customers. Consider how accident forgiveness reshaped the auto insurance industry when first introduced.
2) Acknowledge You Have a Data Problem – 87% percent of marketers consider data their organizations most underutilized asset; however, over 60% of marketers claim they don’t have the technology required for personalization. Traditional methods and technologies are not able to solve the personalization problem in a rapidly-changing and fragmented technology landscape. When you consider the boxes and lines in a graph of integrated technology, complexity and effort comes not from the number of boxes (technology), but from the lines that connect and integrate their data together. It’s time to consider novel approaches to tackling this data pipeline problem.
3) Target a Data Strategy That’s Right-Sized – There are an array of solution options across the dimensions of personalization and integration agility. However, to select the solution that drives the greatest ROI, you must consider a series of questions. How much personalization is needed for your organization? What portfolio mix of customers are you targeting? Residential? C&I? Brokers? All of the above? Will either best-of-breed (Salesforce, IBM, etc.) marketing toolchains or traditional IT methods suffice? Are both marketing and IT organizations poised to handle the pace and data agility required? All these questions center around requirements for maturity in your marketing data strategy and is largely driven by operational context; certain options for personalization will suffice in some organizations and not in others.
The data value is there for personalization; therefore, organizations need a good strategy to capitalize on the differentiation offered by martech. If data is truly the “new oil”, then a solution for marketing data and technology must revolve around the pipelining, processing, and refinement of possible data products. Which begs the question: what are you doing about your data problem?