For this reason, brands should ensure their data teams not only have all the right data “ingredients” but also the tools and talent necessary to separate the actionable data from the data with less relevance to the marketing strategy.
A good data-based targeting strategy starts with understanding the brand marketer’s knowledge and expectations, which have increased in recent years. For example, it is now general knowledge among marketers that personalized, targeted advertising drives a higher response rate. A recent Forrester report tells us that 77% of consumers will choose, recommend and pay more for a brand when the advertisement is targeted and personalized. Armed with this proof point, marketers know they are more likely to exceed their revenue goals by having a documented personalization strategy.
But unfortunately today, many marketers are concerned about the quality and accuracy of their data. Thirty-four percent tell us they face challenges due to inaccurate data.1 And nearly two-thirds of marketers express concerns over the quality of the data available to them.2 How the data is sourced is critical to the success of an omnichannel marketing strategy. Data should come from in-market signals, site visitation, redemption, category purchases, brand sales and CRM systems. The data pool should include as much information about consumers as possible as well as sources that can discern affiliations, interests and in-market purchase behavior. Multiple sources of this data are required to get a clear 360-degree view of each consumer. A talented data “mixologist” will mine the data to help a brand reach specific consumers with relevance and timeliness.
It’s also important to understand that consumers do not stand still: what’s true about a consumer today may not be true tomorrow, which means that running a data strategy from compiled data snapshots will not suffice. As consumer affiliations, loyalty and interests change, the data solution needs to keep pace. A constantly connected view of a consumer ensures that targeting is accurate and driving the most relevant experience possible.
Maintaining a constantly connected multi-sourced data pool comes with significant capital investment. Many providers will short cut this process to save on storage and processing costs. Only companies with a commitment to driving results from data will take the necessary steps to ensure the clearest consumer-level view of an audience as possible.
An example of using data to drive an omnichannel experience is evidenced through the Valassis Consumer Graph™. Consumer Packaged Goods (CPG) brands have used Valassis print media for the delivery of coupon advertisements to targeted geographic markets, and today can overlay digital media advertising to amplify and augment print distribution. The amplify tactic is used to drive greater performance in areas where the print channel is already performing at acceptable standards, while the augment strategy can be utilized to drive digital conversion in markets where print is underperforming with regard to brand sales and coupon redemption. This print-plus-digital approach has helped advertisers achieve sales lift higher than 15% in some categories.
When a brand evaluates its data strategy, it’s important to consider the quality of the data, the source of the data, the depth of the data pool and the currency of the data. Equally important is an understanding of how the data team put the data to work. Data science should be applied to interrogate the data and analyze the results. The combination of a rich set of data “ingredients” and talent level of a data “mixologist” will drive the perfect cocktail of omnichannel media performance for your brand.
(Marc Mathies recently presented on this topic at the Association of Coupon Professionals (ACP) annual conference. The presentation was centered on the value of using data to drive greater media performance for brands.)
- Forrester “Pursuing the Mobile Moment,” June 2017
- Forrester, “Current State of Marketing Measurement and Optimization” Sept. 2018