{"id":8854,"date":"2015-12-12T12:54:00","date_gmt":"2015-12-12T12:54:00","guid":{"rendered":"https:\/\/tenjin.com\/?p=8854"},"modified":"2026-04-14T07:20:28","modified_gmt":"2026-04-14T07:20:28","slug":"building-for-the-marketing-scientist","status":"publish","type":"post","link":"https:\/\/tenjin.com\/es\/blog\/building-for-the-marketing-scientist\/","title":{"rendered":"Construir para el cient\u00edfico del marketing"},"content":{"rendered":"

As marketing goes digital, it starts to share a lot of common ground with data science. At Tenjin<\/a>, we are seeing people with backgrounds in these two seemingly distinct fields, marketing and data science, emerge with a new role: the \u201cMarketing Scientist\u201d.<\/p>\n\n\n\n

There are two main drivers for the rise of the Marketing Scientist:<\/p>\n\n\n\n

    \n
  1. New technology has lowered the barrier between marketers and consumers. With the increased ubiquity of smartphones and wearables, consumers now carry numerous marketing channels with them<\/li>\n\n\n\n
  2. Big data and its insights have become increasingly accessible and actionable. Data warehouses used to require massive contracts and multi-year commitments. Now, any startup can spin up a Redshift cluster and start processing terabytes of data in a few clicks.<\/li>\n<\/ol>\n\n\n\n

    These two trends are starting to build on each other in interesting ways:<\/p>\n\n\n\n

    First, marketers are responsible for reaching customers as effectively as possible, leading to better brand recognition, more sales leads, and higher user engagement. Historically, measuring marketing\u2019s effectiveness was an ad hoc process at best, governed by intuition and murky KPIs. Technology, specifically big data, has changed this. Metrics like ROAS (return on ad spend) and brand awareness can now be measured with accuracy and precision, making it possible to predict how future marketing campaigns will perform without even running them.<\/p>\n\n\n\n

    Second, marketers are also responsible for identifying segments of potential customers to target and re-target. It used to be difficult to figure out who your best customers are, relying again on intuition and maybe a survey or two. With organized big data, you can launch your app, run a query to figure out who your best users are, and tell any network \u201cget me more users like these\u201d.<\/p>\n\n\n\n

    It\u2019s becoming clear that these two fields, marketing and data science, have a lot of overlap. We expect to see Marketing Scientists leading digital marketing at forward-thinking companies in the years to come. And because we believe in this so strongly, we\u2019ve built Tenjin for this future.<\/p>\n\n\n\n

    At Tenjin, our mission is to create a service based platform for marketing scientists. At Tapjoy and Playnomics, I witnessed the struggle marketers face organizing big data in spreadsheets. My co-founder, Amir, and I built Tenjin so that mobile marketers could spend their time analyzing<\/em> data, not wrangling it. If you\u2019re a marketing scientist (or one in the making) we\u2019d love to hear from you.<\/p>\n\n\n\n

    Image credit: A Shed Load of Data<\/a> by dullhunk<\/a>, used under CC BY<\/a> \/ cropped from original<\/em><\/p>","protected":false},"excerpt":{"rendered":"

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