Send in the Clouds: Martech Moves to Cloud Platforms

Last weekend brought the intriguing rumor that Salesforce
is in late stage talks to acquire data integration vendor Informatica.   This
followed the previous week’s rumor that Google-parent Alphabet is consideringan offer for Salesforce-competitor HubSpot, and came the same week as a slew of
partnership announcements tied to Snowflake’s Marketing Data Cloud Forum.

You don’t need a crazy wall to see how these events are connected.  Cloud database vendors including Google and
Snowflake are expanding into marketing applications.  This poses an obvious threat to customer
cloud vendors like Salesforce, in good part because it expands the ability of
IT and data teams to build their own solutions rather than buying them.  Viewed in this light, Informatica helps
Salesforce to compete by strengthening its ties with IT and data teams.  Of course, this is the same benefit that Salesforce sought with its Tableau, Slack and Mulesoft acquisitions, although you could argue those were all primarily tools for business users while Informatica is used primarily within IT and data teams.

A stronger strategic argument is that an Informatica that is properly
integrated with Salesforce Data Cloud would help those teams build more
powerful databases within Salesforce. 
This would make Data Cloud a more viable alternative to Google Cloud or
Snowflake as the company’s primary customer data store.  In Salesforce’s wildest dreams, Data Cloud
might even replace data warehouses.

Let’s put aside the question of whether Salesforce could
or should become an enterprise data warehouse supplier.  The immediate question is whether it can
retain its position as a primary platform for customer data and customer-facing
applications, or that role will be taken over by cloud platform vendors like Google
Cloud, Amazon Web Services, and Microsoft Azure and cloud database specialists
like Snowflake and Databricks. 

I don’t know the answer. 
But what does seem clear is that customer systems will run on platforms,
whether from Google, Salesforce, Snowflake, or someone else.   

The platform approach isn’t particularly new
but it’s not the way things have always been. 
Remember that most customer systems – even today – are stand-alone,
self-contained products that maintain their own databases.  These are the dreaded silos we keep
hearing about.  The trick is to connect
these silos, initially at the data level by copying their data into a central
warehouse or Customer Data Platform, and ultimately at the decision and delivery
levels through shared journey orchestration and messaging. 

Platforms solve the data problem, since all systems run
on a common data store.  They don’t
necessarily unify the decision and delivery layers, since those functions are
handled by applications built on the platform. 
Those boundaries are not clear: platform vendors sometimes add decision and delivery
functions.  Indeed, the risk that the platform vendor will incorporate your application
is one that application developers must accept as the price for accessing the
platform vendor’s customers.  Data clean
rooms are a good example: once independent applications, they are now offered
as core platform services.  Machine
learning and artificial intelligence are following the same path.

The transition from silos to platforms is far from
complete, but the industry direction is clear. 
The entry of cloud and cloud data platforms as alternatives to customer
clouds is likely to accelerate the change. 
As we’ve already seen, platforms are a mixed blessing for application developers:
they gain access to a larger audience but risk of being undercut by a platform
product extension.  (The good news is
those extensions often involve acquiring a leading application.)  

Application vendors also benefit from the
platform providing data management functions that the application vendor
would otherwise have to build for themselves. 
This simplifies application development, freeing resources to improve
the primary application functions. 
Unfortunately, it also makes it easier for other companies to build
competing applications.  This lower
barrier to entry (and to continued survival) is one reason the number of
marketing applications has increased so sharply in the past decade. 

The only way for application developers to escape this “app trap” is to themselves become platforms.  Many aspire to this and some, including HubSpot, have had some success moving down that path.  But most are too small to support a robust app marketplace and certification program or to attract a critical mass of application vendors.  

And what does all this mean for marketers and other
business users?  Since the platform model
isn’t new, we can already draw on experience.  It’s a mixed bag: buyers have a greater
choice of applications for any particular task, which is mostly good but does create
a burden of having to choose.  Buyers are
tightly bound to whichever platform they select, since switching platforms
means switching the related applications as well.  This creates a quasi-monopoly situation, with
the potential for higher prices and poorer service that comes with it.  Raise your hand if you’ve seen that
already.  This will only become worse as
platforms become more common, making it harder for independent application
vendors to survive and, thus, harder for companies to assemble their own ‘best
of breed’ architecture from separate point solutions.  In other words, you may miss those silos when
they’re gone.

It doesn’t have to be this way.  The alternative to a platform architecture is
a true composable architecture, where different applications are written to
common standards that are not controlled by any particular platform.  The ecommerce world has managed this to some
extent, with ‘headless’ solutions and standards enforced by the MACH alliance.  Standard data access languages like SQL are
another example.  That the customer data
world will come up with similar standards seems doubtful, although there’s
always hope.   

It’s also possible that integration
platforms will let different systems interoperate even without shared
standards.  That’s certainly their goal
but so far results are limited by the effort to accurately capture all the nuances of one
system and present them to another without losing anything in translation. AI might well
change things by making this translation easier.  But AI might change a lot of things, so let’s
not count on any of them quite yet.

For the immediate future, then, we can expect a handful
of platform vendors to control customer data at a growing number of companies.  Those companies will be captives of the
platforms, but it will be a fairly enjoyable captivity, with many pleasing
applications to choose from and few obstacles to working as they please.  Every so often they’ll pull back a curtain and see the bars on
the windows. Some will be so unhappy that they’ll escape.  But most will accept the limits of their chosen platform and get on with their work.