November 17, 2011
In the digital wild west of the 21st century, targeting seems to have fallen by the wayside. Marketers want to optimize their websites, but the technical means to access and acquire targeting data has remained out of easy reach.
What’s standing between marketers and the data they need for targeting? The pain point of silos. For most companies, data flows from a variety of sources:
Legacy web development platforms usually lack the infrastructure to aggregate data in a meaningful way. For example, a retailer we’ll call Online-Mart might mine data on product purchases from their transactional database, but then not be able to combine it with online activity such as email promotion history and returning customer traffic to create actionable insight for targeting—say, promoting the items featured in emails that drove customers to click but still haven’t been purchased. Or, more simply, recommending other products purchased by customers who also bought the same item as returning customers. Without enough reported or inferred data that’s relevant to Online-Mart’s business goals, segmentation is impossible.
Of course, consumer intelligence is just one side of the targeting equation. Ecommerce firms also need content (products, banners, badges, etc.) that is properly tagged to deliver targeted messages, which usually turns into a back-breaking amount of work in a content management system. And once the consumer data is available and the content tagged, now the marketing team needs to be able to execute its campaigns. So, it’s back to IT to build or procure the engine, because most content management systems are not geared to support agile commerce.
As companies try to cobble together disparate systems to market to online audiences, they fall deeper down the rabbit hole of being committed to procedures and tools that are sub-optimal at best and dysfunctional at worst. To justify the initial investments—and tease an acceptable level of performance out of targeting efforts—companies then allocate more spending to this convoluted mess. It’s understandable why frustrated marketers simply scale back their targeting efforts, or skip targeting altogether.
But marketing can break free from its technical constraints. Next-gen targeting platforms that run in the cloud streamline the process of integrating visitor/customer data from various channels, connecting it with relevant content and then leveraging both to create personalized website experiences. And by giving users autonomy—i.e., no waiting in line at IT—these platforms unleash marketers’ and merchandisers’ pent-up creativity, which so often gets lost in IT/database development queues and pushback from the execution side of the house.
So, the practice of targeting is just as relevant as it’s ever been. The cumbersome legacy platforms that don’t support data-driven, agile commerce? Their days are numbered.