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Machine learning / big data work is currently comparatively costly. This is a nice example of the kind of benefits that lowering its cost bring. I expect we'll

Machine learning / big data work is currently comparatively costly. This is a nice example of the kind of benefits that lowering its cost bring. I expect we'll see a lot more of this in the future in sales and marketing (and probably other areas but sales and marketing are particularly easy to measure). One example is lead scoring. This is the process of working out which leads (potential customers) to pursue. Currently most people do this in an entirely ad-hoc way. E.g. download the whitepaper = 5 points, sign up to the newsletter = 10 points. It's crying out for simple statistical modelling and validation, but currently that's too expensive (in time, $s, and mental energy) for most people to undertake.

danvoell 10y ago
But many companies are making it available at a much less costly entry point. If you are interested in lower cost options check out hopdata.com (work here), monkeylearn.com, algrorithmia.com, google cloud machine learning, Amazon machine learning...
dandermotj 10y ago
The only cost tied to these issues is the salary costs for a statistician/data scientist. The best tools of the trade are open source. You won't find lowering costs until more people are educated or trained up in these fields.
shostack 10y ago
The biggest one in marketing is cross-channel attribution and valuing hard-to-measure channels like display, video, etc. Better data lets you avoid wasting dollars and better allocating your budget by properly assigning the weight of how much revenue contribution a given channel/campaign/placement/creative/etc. should receive. This is arguably the toughest problem in the industry, and solutions by Google, Adobe, etc. are just starting to make headway, but are still very expensive and very custom with few exceptions (see the new data-driven attribution release for AdWords for example).

danvoell 10y ago

But many companies are making it available at a much less costly entry point. If you are interested in lower cost options check out hopdata.com (work here), monkeylearn.com, algrorithmia.com, google cloud machine learning, Amazon machine learning...

dandermotj 10y ago

The only cost tied to these issues is the salary costs for a statistician/data scientist. The best tools of the trade are open source. You won't find lowering costs until more people are educated or trained up in these fields.

shostack 10y ago

The biggest one in marketing is cross-channel attribution and valuing hard-to-measure channels like display, video, etc. Better data lets you avoid wasting dollars and better allocating your budget by properly assigning the weight of how much revenue contribution a given channel/campaign/placement/creative/etc. should receive. This is arguably the toughest problem in the industry, and solutions by Google, Adobe, etc. are just starting to make headway, but are still very expensive and very custom with few exceptions (see the new data-driven attribution release for AdWords for example).