The myth of the best-in-class vs. all-in-one solution debate

A foundational consideration in many marketing, advertising, and data technology evaluations is the question of whether to invest in solutions that can solve the full spectrum of possible needs or to purchase multiple solutions that may address some, but not all, needs more effectively. The advantages and disadvantages of each approach have been well covered and widely debated. Where businesses land on this issue largely depends on solving for specific issues like unique use cases, complex business models,  and the interoperability of solutions (note: even in an all-in-one world you want to look out for interoperability considerations). 

Rather than rehash these debates, I want to focus on understanding the shift in market dynamics that underpins the decision to choose either a best-in-class or all-in-one solution. I’ll also briefly discuss how I see these shifts impacting the CDP space. 

How Did We Get Here?

When marketing first went digital, email service providers and content management systems offered two key components of the digital toolkit for enterprises moving to e-commerce. As enterprise software companies sought to own all aspects of CRM workflow, these players became attractive acquisition targets. Over the past decade-plus, enterprise software juggernauts have continued to acquire businesses to expand their ownership of the workflow spectrum, packaged capabilities and branded aspects of their ecosystems as their “clouds.”

Before social media and search dominated the digital advertising space, digital migrants and digital native enterprises (many of whom built their own email service and content management systems), found themselves in need of a way to manage audiences across programmatic and direct advertising networks. Thus, the data management platform (DMP) became a hot commodity. 

Among the businesses targeted for consolidation and acquisition during this period were  customer support and sales solutions, which have been rolled into marketing and sales automation offerings. 

Most recently, the acquisition dominos began to fall in the business intelligence space, as these solutions have become an important part of the reporting, measurement and analytics ecosystem just as the shift from digital display all but killed off the attribution space. 

As the clouds have grown, they’ve also acquired data integration solutions to help patch together their various standalone solutions, allowing them to function together cohesively. 

After this long period of capability expansion, now the big cloud providers stand to offer an all-in-one buffet of marketing, advertising, and analytics as well as the services to support and the integration tools to facilitate the interoperability of these systems. In that case, two key questions remain: 

  1. Why do architecture diagrams of even the most intentional all-in-one enterprises still resemble a  plate of regurgitated spaghetti? Put simply: why do businesses still need so many different solutions? 
  2. Why do so many similar-sounding solutions still exist, purporting to do everything a business needs, when theoretically they could get most of what they need from an all-in-one solution? 

Disclaimer: Before we move on, I want to dispel the notion that this is another pile-on piece about how all-in-one solutions don’t deliver on their promise. Of course, they don’t. But they actually do deliver a ton of business value. Rather, I want to center this on the reasons the landscape has evolved and what this evolution means. 

Why is Enterprise Solutions Architecture Still a Mess in an All-in-One Context? 

Every enterprise architecture diagram I’ve ever seen for a business with an intentional preference for an all-in-one solution is littered with point solutions. Why is that?

The best way to break this question down is to understand the reason why a point solution might exist. There are a few key considerations: 

  • Client niche: a vendor has discovered a niche in the market resulting from a very  specific vertical need or business model, and due to either the unique nature of the client need or the level of effort to build, it wouldn’t be valuable for an all-in-one solution to build such capabilities
  • Depth of capabilities / complicating factors: the capability ceiling for a specific solution is so vast, and the value that these capabilities can drive is meaningful enough that a business focused solely on solving a very specific problem inherently builds a competitive moat in the process of serving its customers 
  • Interoperability challenges: some business’ core model is at odds with the ability to interoperate easily with other solutions, either because the value it delivers is predicated on owning some, but not all, of the business’ workflow or because data sharing introduces risk to the core value proposition 

However, these factors offer only a partial answer to the question. Let’s assume for the sake of argument, that a business lives in a fairly standard vertical with few or no complicating factors that would require point solutions. Let’s also assume that they have a strong preference for all-in-one technology. Why would a diagram of their architecture still look like this:  



Note: This architecture is based on a real client in the retail space with both a brick & mortar and e-commerce business.  This client has a strong preference for all-in-one solutions. We’ve obscured any identifying details for privacy but the complexity is evident. 

Would it surprise you to learn that this business has challenges coordinating across all of these different systems? 

I believe the answer to this question is that there really is no such thing as an all-in-one solution and that purported all-in-one  solutions are actually just broader workflow engines that aren’t necessarily designed to function effectively with other aspects of their own ecosystem. 

Why Do All MarTech Vendors Sound the Same? 

I always joke about how every marketing technology company now claims to do: “true omnichannel one-to-one personalization at scale.” When I take early-stage client calls, I’m almost always asked to differentiate between multiple capabilities that already couldn’t be more different, but when I look at those vendors’ websites, I can’t blame anyone for being confused. Everyone really does say they do the same thing. 

I raise this question, however, in the context of the all-in-one vs. best-in-class debate. 

There are five factors at play: 

  1. Consumer expectations and  technology have shifted exponentially but businesses have adapted incrementally 
  2. This shift has created huge gaps that businesses are increasingly trying to fill with off-the-shelf capabilities 
  3. Some of these capabilities have gotten so good (see Depth of Capabilities tools) that the clouds won’t ever catch up unless they acquire them, which is further complicated because: 
    1. They won’t acquire them until they reach sufficient maturity
    2. These businesses likely won’t reach sufficient maturity due to private market trends 
    3. Advancement of their technology in the pursuit of maturity makes their offering more complex, which makes them more vulnerable to competition
  4. Venture Capital has increased competitive pressure while extending the lifetime of businesses beyond what rational markets would allow. 
  5. Providers have used their venture money on marketing that has enabled them to stave off their inevitable mortality, creating a vicious cycle

In other words, best-in-class solutions are sometimes highly problematic.  

Bringing it All Together

All-in-one solutions aren’t really all-in-one and best-in-class solutions aren’t always best-in-class. Woof. What does this suggest about the strategy to adopt?

Ultimately, I don’t believe businesses ever find themselves entirely in an all-in-one or best-in-class scenario, and I certainly don’t believe that they ever should. Purported all-in-one solutions are actually best in class for many different things, but never meet the full needs of any enterprise. Separately, they have their own interoperability challenges, which speak to the need for better workflow, data, and process integration. 

Businesses need the flexibility to bring on different best-in-class or point solutions as the market and their needs evolve. 

In the CDP space, we’re biased toward thinking that the world is moving inexorably toward an infinite buffet menu of point solutions that will need to be managed and coordinated. In some cases, best-in-class will always make sense for the reasons described above. But ultimately, it’s a combination of all-in-one and best-in-class that will be most effective for the majority of enterprises, especially those without a strong build appetite or culture. 

That said, we are seeing an increasing number of large enterprises– the type who tend to be lead by tech frontiers-people deciding to move entirely to a best-in-class world. This category of players encompasses most of  the businesses founded between the late 1990s and early 2000s. These businesses are often digital native, but large enough now to have amassed significant complications. It also includes more traditional enterprises that have been more aggressive in their digital transformation and adoption of technology. This is a category of businesses where I believe CDPs have the best chance to drive value as an orchestration engine. When less digitally-inclined peers in the middle of the standard distribution of the adoption curve start to mirror this shift, its boom time for the CDP space.

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