The Pace Of Marketing Automation In 2010

While many of my references come from the B2C space, I do believe that the B2B market will better inform the technological direction and focus on the marketing automation space over the next few years -- more so than the vast needs of a consumer-data-driven organization. 

The foundational trends are still the same buzzwords we've used for years:

-        ROI and Reporting

-        Integration of social media

-        Buyer-centric content

-        The need for new analytical skills

-        Renewed focus on data quality

-        Sales and Marketing Alignment

Nothing new, you might say, but there are some pretty common observations that shift how we think about this in today's world.   First, ROI has always been the driver in B2B marketing.  But more progressive digital channels and methods of reach, have put pressure on ROI to be measured at the lead quality stage, not just the conversion stage.  This puts more pressure on the systems and businesses to adjust lead scoring to adapt to a more complicated sales cycle and attribution.  Second, the combination of sales and marketing has always been the utopia of a business.  How to build in the right amount of integration between a sales agent and the web experience?  We research differently, we use many more sources, and we have much better filtering mechanisms these days, which make this synchronization of sales interactions and support/consideration a much more difficult challenge to manage and optimize the funnel.



We have so much more data than we've ever had, which creates more pressure to sustain this over time.   The problem here is data quality.  If you believe in the concept of lead recycling, then you will realize how important data quality is in taking an extended view and investment in managing leads longer, even if they aren't ranked high in your "ready to buy" scale.  

With the emergence of socially engineered experiences and connectivity, the world of data quality got a lot harder.  Our view of a lead will change from "when will they buy and how much" to "how much influence do they have over the buying decision -- and who else is involved in this decision?"  This unstructured data will present many challenges for marketing automation systems.  Can you accurately mine "intent to buy" through unstructured data sources?  How will LinkedIn and other B2B social networks influence lead scoring and value?   It's not just a reach vehicle, it's about real-time simulation of social networks to gauge influence and engagement.

Buyers are becoming increasingly sophisticated in how we research, consider, compare, try and buy. The sales cycle has become an amazingly complicated web of interactions.  If you have ever tried to develop a linear lead conversion program, you'll quickly realize there are so many permutations that you are forever modifying to support optimization.  This manual task has become much easier to manage with the tools, but the analytical competence that goes into making decisions based on known facts is where most businesses will struggle.  What makes this even more difficult is the need to create buyer-centric content that aligns the experience with need and fulfillment.

We'll face many challenges in this space, but we've seen great progress with the tools. With the emergence of SaaS solutions, they aren't as expensive as they used to be.  They are much more intuitive, too, with improved modularity. Yet most will struggle with the physical management of these tools , processes and data.  

Your marketing automation program must match the intensity and sophistication of your sales cycle.

This article was inspired by the following blog post.  Definitely worth a read:

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