Marketing Governance

Forbes Insights. Forbes surveyed 250 marketers and 2000 consumers about the perception of brand engagement from both sides. For example, 49% of marketers consider forwards or shares of ads or other content online as a strong influence on their engagement measures, whereas just 15% of consumers say they feel engaged or invested in a brand when they share an ad.

Data from The New Rules of engagement: Measuring the Power of Social Currency reveals that there are numerous similar instances of disconnect between what marketers measure and what consumers feel is important. One that stands out relates to brand recommendations. 45% of marketers say that consumers’ proactive efforts to recommend a brand is a strong measure of engagement for them. But, just 24% of consumers report feeling invested in a brand when they convince others to use it.

The only measure in which both groups agree concerns opt-in messaging (subscribing to email alerts, newsletters, or other loyalty programs), which marketers think is the most influential engagement measure. At the same time, signing up for special deals or email updates ranked as the top way that consumers feel engaged with brands. Read More

Publishers and marketers are aggregating more data, from more sources, than ever before. And in order to realize the full value of that information, they require a technology-driven solution — a central hub — to collect, integrate, manage and activate those large volumes of data. The data management platform (DMP) emerged just a few years ago as a response to this need.

As the promise of Big Data plays an increasingly significant role in the digital marketing landscape, the Interactive Advertising Bureau (IAB) and Winterberry Group published The Data Management Platform: Foundation for Right-Time Consumer Engagement, a whitepaper revealing that DMPs could potentially serve as a principal technology solution for multichannel data aggregation, integration, management and deployment. DMPs are technology tools that normalize disparate data sets so that marketers can better understand and utilize data from multiple sources.

Read More

surveyed by Capgemini, a consultancy, for the report, two-thirds said they believed they worked for a data-driven company. A similar total (65%) said the proportion of corporate decisions taken on the basis of hard analytic information was rising.

By contrast, a clear majority (54%) said that decisions taken due to a managers personal intuition or prior experience were suspect. The strong support for data also came despite almost half (42%) of respondents agreeing that data analysis made decision-making slower, and 67% expressing concern about the accuracy of the data they used as a basis for their decisions. Just over half (51%) also complained about the lack of qualified data analysts available to corporations.

According to an earlier report by Gartner,

Business executives and IT managers are increasingly referring to information as one of their organization’s most critical and strategic corporate assets. Certainly there is a sharp rise in enterprises leveraging information as a performance fuel, competitive weaponry and a relationship adhesive. Read More

The amount of data being generated is expanding at rapid logarithmic rates. Every day, customers and consumers are creating quintillions of bytes of data due to the growing number of customer contact channels. Some sources suggest that 90% of the worlds customer data has been created and stored since 2010. The vast majority of this data is unstructured data.

It is not surpring, then, that study after study shows that the majority of marketers struggle with mining and analyzing this data in order to derive valuable insights and actionable intelligence. A recent report by EMC found that only 38% of business intelligence analysts and data scientists strongly agree that their company uses data to learn more about customers. As marketers we need to learn how to leverage and optimize this flood of data and incorporate it into customer models we can use to predict what customers want. Read More