In this week’s DatoRoundup catch Dave Helmreich for VentureBeat on the difference between AdTech and MarTech being more than the billing structure; Leslie Hancock for Dun & Bradstreet discussing the biggest irony of the MarTech explosion; Harvard Business Review (HBR) giving you better questions to ask your data scientists; Deren Baker for Entrepreneur on how to beat your marketing competition with data analysis; and finally, a Contently interview with a perrenial DatoRoundup favorite, Scott Brinker, on the pitfalls and promise of MarTech.
You don’t need to look any further than DatoRoundup each week for the best summary of AdTech, MarTech and Data-related content!
By Dave Helmreich
Dave Helmreich says that it seems like the bifurcation between AdTech and MarTech is finally getting the attention it deserves, and like so many nuanced topics, it is being grossly oversimplified by the media. While he goes on to give real examples of this, Helmreich also admits that most of the articles cited — like the WSJ piece he cites “Why Venture Capitalists Are Betting on Marketing Tech over Ad Tech,” which has been getting significant attention — are interesting and thoughtful reads. It is interesting to see where he feels others have fallen short in this MarTech vs Adtech discussion.
By Leslie Hancock
Dun & Bradstreet
MarTech tools are meant to help make sense of a complex marketing organization. Yet the rapid proliferation of applications and tools within marketing departments is fuelling chaos instead. In fact, Leslie Hancock, Founder and CEO of CreativeCafeHQ, likens it to creating more chaos by trying to tame the gnarly beast.
The challenge of managing many siloed data sources and systems makes it very hard to perform advanced customer analytics, which Hancock says marketers need in order to identify a businesses’ most valuable relationships and to personalize their interactions with customers. Interestingly, she notes that cutting down the number of tools may not actually be the answer, which is a unique perspective in today’s environment.
By Dillon Baker
For the second week running we are highlighting Scott Brinker in our DatoRoundup. This time “Chiefmartec” is featured in an excellent interview with Contently’s Dillon Baker. Brinker’s interview, predictably, centers around the ins and outs of MarTech. Considering he is responsible for cultivating the famous ‘supergraphic’ showing the marketing technology landscape, you can be sure that he is a reliable source for some insights. Some examples include:
- How marketers can up their strategy game when strategy can’t really be “solved” with technology
- Whether the MarTech industry is expanding or contracting
You will have to read the whole interview to get all the answers. We promise that you won’t be disappointed.
By Michael Li, Madina Kassengaliyeva, and Raymond Perkins
Harvard Business Review
Although we try to keep this curation of stories focused on the marketer, once and a while we like to get a little technical. This next piece is one such example. This story highlights better questions you may want to ask your data scientist. The authors say that first you need to know what questions you should ask. Saying, “As you begin working with your data analysts, be clear about what you hope to achieve. Think about the business impact you want the data to have and the company’s ability to act on that information. By hearing what you hope to gain from their assistance, the data scientist can collaborate with you to define the right set of questions to answer and better understand exactly what information to seek.”
There’s plenty to consider here for both the seasoned data marketer and newbies alike.
By Deren Baker
Many of today’s businesses mistakenly think, “The more data, the more insight.” But Deren Baker, CEO of Jumpshot, sets the record straight by saying that diving into a sea of unexamined data can actually harm more than benefit an organization. Baker says that the most important thing is collecting the right data and analyzing it effectively. Knowing how to collect and conquer is key and than gathering every piece of data a business can, start ups should focus on a few key data sets. In fact, two of the most important data sets to analyze, according to successful start up founders, are real-time customer behavior and web activity. Looking for the next steps? Check out Baker’s post to learn more!
Thank you for reading this week’s DatoRoundup.