Monday, February 15, 2016

Landscape of Machine Intelligence Systems for Marketing

I’ll be speaking next month at the MarTech conference on How Machine Intelligence Will Really Change Marketing. This required assembling a list of marketing systems using machine intelligence, which pretty much inevitably led to the logoscape below.

I wasn’t initially enthusiastic about the idea – could there by anything less original?—but have found the result surprisingly useful. In particular, it illustrates several points that would otherwise have been hidden or much harder to convey. These include:

  • Lots of systems. You may think that machine intelligence is still a pretty rare thing. Not so. I found 23 categories with 140 systems, and know there are dozens of other products I could have included.
  • Some categories are already crowded. Boxes with a lot of logos have a lot of competitors. This doesn’t make them mature in the sense of having a widely accepted standard approach. But it does mean that many people have recognized they are a successful use for machine intelligence. Conversely, categories with few competitors are more speculative – although a few strike me as pretty sure to succeed in the end.
  • Few systems for marketing strategy. Some research I’ll cite at MarTech suggests that marketers split their time roughly equally between strategy and planning, program design and content creation, and data management and analytics. I’ve classified vendors into those categories. I then make a further distinction between systems that help marketers with decisions and systems that make decisions without marketer involvement. This distinction is very loose, but that’s a topic for another day.  What’s immediately obvious is there are very few systems to do strategy and planning, and none of those are actually deciders. My take on this is that CMOs aren’t ready to delegate strategic decisions to machines, although another explanation is that CEOs aren’t ready to delegate marketing strategy to the CMOs.
  • Decider systems for design. The design category is crowded with systems for the established applications of personalization and programmatic ad bidding. Perhaps more surprising, there is also a rapidly growing number of products to create contents such as copy, email dialogs, and even Web pages. Nearly all of these are deciders – perhaps because they work with volumes of choices so huge that only computers can handle them. Helper systems aren’t much use in those situations.
  • All kinds of systems for data. This is the most populated area, with roughly half the categories and half the total vendors. It's also the group with the most vendors I didn’t include – for example, there are probably 100 social media monitoring systems alone, most of which use at least some basic machine intelligence for language processing. This group is about evenly split between helpers and deciders, reflecting the variety and complexity of data-related tasks.  One reason this group is so large is that many of the applications, such as data extraction and predictive model building, are also used for purposes outside of marketing.

I’ll draw some other lessons from this chart in my MarTech talk. You can still join us by registering here. In the meantime, I hope this chart helps you realize the scope of machine intelligence applications in marketing today and inspires you to explore more deeply how they can help in your own work.

4 comments:

Justin Norris said...

Hi David,

A very useful logoscape, and timely too.

One category you may wish to also think about including is predictive demand generation, aka lookalike modelling of ideal customers and providing net new accounts and contacts that fit the bill.

A number of the lead scoring vendors (everstring, lead space, lattice) have moved in this direction and made it a prominent part of their offering.

I'm interested to see how this evolves particularly with respect to predictive campaigns, something vendors have hinted the future will contain for some time now.

David Raab said...

Thanks Justin. I see predictive demand gen as part of the lead scoring space, so it probably doesn't need a separate category. But it's true that some vendors do the one without the other. Predictive campaigns, as you know, are a topic close to my heart. Mintigo has made an announcement along those lines and, as you say, others are moving in that direction too. Interesting times indeed!

David Arnoux said...

Hi David,

Thank you for this. Extremely helpful and time saving as I wasn't trying to make sense of the landscape.

Would you agree that IBM Watson Analytics falls under "Natural Language Query"?

David

David Raab said...

Hi David. Watson does many things, and Natural Language Query is among them.