Headache Or Opportunity? The Profusion Of Marketing Data

Marketing data is flowing all over the place these days. Research from Teradata this year shows that 78 percent of marketers now use data systematically, versus 36 percent in 2013.

The proliferation of data from a continuously expanding number of sources is creating headaches and opportunities — depending on your perspective. Those who see opportunities will thrive in this new tech-driven marketing environment.

The myopic few who fear change and learning new skills — well, they’ll probably be looking for a new job within a couple years.

Many changes are currently shifting the marketing industry. And each development revolves around an unprecedented profusion of information, providing marketers with the opportunity to connect data sources to piece together comprehensive narratives on individual buyers.

Integrating Martech And Adtech

A pivotal step in connecting all this vital information in a coherent way is integrating the heretofore disparate categories of marketing technology (martech) and media channels/advertising technology (adtech).

With the influx of customer information from a growing number of media channels (and the adtech tools that leverage them), marketers are now receiving more data and richer data.

Well beyond recording “clicks,” this data increasingly provides rich context for each interaction, and therefore, insights into the effectiveness of marketing messages and valuable clues about the identity, characteristics and interests of prospective customers.

But all this data must come together in the right way if it’s to be beneficial to marketers.

Integrated media/adtech and martech stacks enable demand marketers to consolidate typically fragmented first- and third-party data in order to construct a more detailed prospect/customer identity and engage audiences with customized, relevant messaging.

Moreover, having visibility into all data sources allows marketers to attribute conversion rates and sales performance to specific marketing channels, data sources, persona characteristics, content and many other marketing variables.

Predictive analytics software is a prime example of merging media/adtech and martech data. It compiles known ID data (e.g., prospective customer data acquired via lead generation tactics) and anonymous data (e.g., cookies dropped during website visits) from numerous first- and third-party sources and identifies patterns, resulting in testable predictions.

The validity of these predictive models can be monitored based on outcomes, which, in turn, inform the models likely to acquire quality prospects that convert to more customers and revenue.

This sparks a virtuous cycle, whereby the predictive models are iteratively refined, resulting in ever-more targeted efforts and higher marketing ROI.

Other Ways To Blend Martech And Adtech

Further applications of combining adtech and martech data include:

With these benefits and applications in mind, it’s inevitable that adtech will gradually become more integrated within the wider martech industry. This shift is essential in order to gain a full view of the customer narrative.

Moreover, it’ll enable marketers to better compare what’s working and alter marketing programs and media spend accordingly.

To connect the data dots, organizations must begin thinking about how they can better integrate their advertising tools and media partner programs into their marketing automation and CRM systems.

Adtech is already becoming part of martech — numerous acquisitions by the big marketing cloud providers attest to that.

The marketers who follow this path to full system and data integration will understand their customers better than the competition. And their ability to serve their customers at a higher level will ensure their continual business growth and success.