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Thoughts on the MarTech conference, the explosion of marketing data and how companies are attempting to manage this data from a variety of sources.
Hopefully by now you’ve read Joelle Andrews’ most recent blog post recounting our visit to MarTech East. I don’t want to spoil it for you, so go check it out here. The event was excellent, as expected. The speakers were a superbly relevant balance of industry rock stars and behind-the-scenes marketing magicians. The exhibit hall was a who’s-who of bleeding-edge martech vendors that didn’t fail to dazzle this marketer’s imagination. By the end of the event, my brain was spinning with all the possibilities on display for achieving campaign greatness.
I was also a bit overwhelmed with all the ways in which marketing data is being consumed, used and output from these dazzling new apps. Each excellent technology on display both consumed existing campaign data and then created its own new campaign data. Finally, each would spin out its own beautiful dashboard to analyze results. And while each of these data factories were impressive, I was struck with a question. How do they work together? Or better yet, how do I put all this data together? I posed this question to several exhibitors at the event and their responses were in line with my own experience…you can access the dashboard data via an API or you can export it out to a CSV.
But, will it scale? At the individual app level, this solution is perfectly fine. At the stack level, it quickly becomes cumbersome, and borders on untenable. According to an eMarketer study from 2017, nearly 70% of companies have 6 or more separate marketing technologies in their tech stack. That is either a lot of API connections to build and manage, or a lot of spreadsheets to export and import. Honestly, do we really have time and resources for that? While we’re swimming in metric tons of data, we’re quickly going to tire out from dashboard fatigue. How do we stop this fatigue and find a way to make sense of all this data?
Interestingly, DataDirect has been solving this problem in IT for decades with ODBC and JDBC drivers. Only, now data access isn’t just an IT issue…it’s an enterprise level issue with enterprise-level inefficiencies that come along with it. We can apply these same connectivity solutions to help you connect your marketing automation platform or customer data platform (or other martech tools) to the BI and Analytics tools that you use across the enterprise…and we can make it available in real-time!Want to learn more?
James Goodfellow is a Senior Product Marketing Manager at Progress and focuses his efforts on the DataDirect suite of solutions. Through his tenure at companies like Progress and SAS, he has spent the bulk of his career launching successful marketing campaigns for data and analytics products. James blogs here and around the web on topics such as data connectivity, analytics, IoT, visualization and machine learning. You can follow him on twitter at @jcgoodfellow.
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