Jailbreak Your Data

Create Informed, Adaptive Audience Segmentation: Context is a critical element of consumer data analysis. A platform that simply spills statistics without connecting them to levels and frequency of consumer engagement and how they relates to conversions is wasteful. Audience segmentation isn’t so much a science as it is an art of skillfully blending metrics with real-world contexts and creating an aggregate snapshot of consumers relevant to the brand. That segmentation process should be adaptive to ever-changing data portraits. Those portraits ought to include more than traditional demographic data and purchasing behavior. Analysis that connects audience-targeting models with real-time data as well as multi-platform social and multi-device information helps companies create audience segments that don’t depend too heavily on one social media site or device to create responsive strategy. The resulting information will be relevant to most segments of any company, from product lines to marketing, to customer service.

Connect Real-Time Data to Long-Term Marketing Strategy: Look at immediate results as well as long term processes in the context of the brand’s method of data analysis. Methods that rely on buying or device data exclusively might skew marketing planning invisibly towards a limited outlook, if social media and regional consumer differences are not taken into account. Audience segments with irregular behavioral patterns might be reacting to variables not included in current data parameters and sources. Incorporating mechanisms to analyze unexpected demographic and purchasing behavior shifts is as important as integrating data results into the marketing strategy development process and overall business intelligence.

Access Untapped Data Pools: Create strategy that offers carrots to consumers to volunteer data on and offline. This might include the use of single-sign on social media content sharing and user-generated content syndication to increase the flow of personal, opt-in information that can be used to help fine-tune audience segmentation and to contextualize aggregate data.

Data shouldn’t live in a marketing silo. The strongest analytics won’t help a company’s bottom line if it follows limited rules of engagement within a company’s business processes. Analytics also need to derive from multiple sources, and companies need to constantly review the way that audience segments and data relevance are defined. While the parameters and sheer amount of consumer information alter continuously, companies can’t afford to be left behind.