Cisco's Amazing Marketing Stack

Take a look at this unbelievable Marketing stack from Cisco.  I’m assuming that this all stands behind and is representative, but not exhaustive.  Even so, have you ever seen anything so well thought out, open, and cutting edge – let alone so well laid out?  Can you imagine the infrastructure budget that Marketing Ops team has – mercy!

As Scott Brinker rightly calls out, it’s entirely customer-centric as well as being organized along two primary dimensions: by phase of the buyer’s journey (“I’m aware,” etc) and by type of technology (“Data and Ops,” etc).

What’s not surprising is what sits at the top of the stack: there’s ubiquitous Tableau as well as Domo – I wouldn’t have been surprised to see GoodData thrown in there as well, though; it seems more nimble.  And seeing Demandbase for account-based advertising (we use Terminus) isn’t a shocker, either.

What is surprising is what’s not in the stack.  Google, for example, is noticeably absent.  (I hear your thoughts – but why should Google be taken as a given, any more than SFDC or Eloqua?)  I also expected to see Bombora for intent data and Reachforce for db appending - perhaps those services come from elsewhere…?  And it’s great to see personalization engines like bluekai, which enables Marketing types to drive cross-device campaigns.

Perhaps not too surprising, what interests me most is the guts of the thing, the “I’m aware” and “I shop and I buy” layers; they are the belly of the beast – the foundational customer data layers - where the intelligence initially accrues.  There is where the lifeblood of digital marketing springs from.  If you boil everything away, what is most essential at that layer?  What must happen at the core if the rest of the stack is to function as envisioned?  At the root of it all is simply finding the right information, regardless if it’s structured data sitting in a db or unstructured content residing in Sharepoint or a file share.  If you can’t connect a customer’s account data with their transaction data and join all that with the text-based notes that were generated from the customer’s last support call, then nothing else really matters.  At that foundational layer is where the real magic happens.  Not because it is easy today, but precisely because it is still so hard.  That’s right, in this age of IoT, of snazzy visualizations, and of Alexa and other AI-ish assistants, everyone still struggles with the basics – of joining the right information across silos to create a unified 360 view of the customer.  Not sexy.  Not new.  But definitely still not easy. initially used Google Search Appliance and Fast to help them find that information, but switched years ago to Attivio’s cognitive search and insight platform.  I invite you to read more about Cisco’s journey here.

It’s interesting to consider that in today’s day and age, when entire conferences are now dedicated to the Marketing stack (could we have imagined this 10 years ago?), we still struggle with the basics of search, a market that’s measured in decades.  Nowadays, search is not about submitting keyword-driven queries to get back the most relevant results list.  Instead, today’s best of breed digital marketing relies on a foundation of best in class search.  Cognitive search, specifically.  It’s “cognitive” search because it’s about presenting answers (not just results) to explicit queries as well as proactively pushing personalized but unsolicited information based on behavioral intelligence.  That is, what you searched for previously, where you were when you were searching, which answers you clicked on, etc.  Cognitive search is predicated on machine learning, which is about closed loop feedback.  A continuously learning solution that knows as much about the user as it does about the information that the user is seeking.  Cognitive search ultimately serves as the basis for AI.

No doubt, it’s a very cool stack for a very forward leaning company.  It’s great to see that at every layer of the stack, Cisco employs the most cutting edge solutions.

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