The SiriusDecisions Demand Waterfall has long been the go-to model for B2B marketers trying to create, manage and optimize their lead management process. Last week, SiriusDecisions unveiled the new and improved version of their waterfall. In some ways, it's an extension of their earlier model and in another way, transformative. Here's our take on what B2B marketers need to know and do about it.
1. The Concept of Demand Unit
While the earlier waterfall was contact/lead-centric, this one introduces the concept of 'Demand Unit' which is a smarter sub-grouping of needs (by product or solutions) within an organization. The focus has to be, and rightly so, on identifying buying groups, engaging them with the right content and even nurturing them distinctly. Businesses with existing buyer personas may well revisit them to check if they include demand unit identifiers.
2. Closer to Reality
The previous model had Inquiry as the starting point, which kind of limited the visibility of TOF/awareness activities (point to note: Verticurl's proprietary demand funnel model had always included the pre-inquiry stages). Very often, marketers tend to forget or ignore the Total Addressable Markets - the Target Demand stage in the new funnel brings it back into focus.
3. Importance of Account Intelligence
In order to identify and engage demand units, sales (and marketing) will need superior account intelligence. While contact and account level profile/behavior data has been available for some time, demand unit related intelligence will need to be derived from multiple sources.
4. Closer Sales-Marketing Alignment
While modern marketing best practices have been stressing the significance of sales-marketing alignment, this model takes it to the next level with the dividing lines being completely eliminated. It remains to be seen how well this is received by both the teams.
5. Role of Technology
It would be interesting to watch how marketing/sales technology vendors respond to this change. In the meanwhile, some functionality can be delivered via customization and process workarounds.
In the long term, there may be an opportunity for AI/Machine Learning plays, especially to generate account intelligence focused on demand unit.
To summarize, this is definitely a good 'upgrade' but bringing it to life by actually implementing it is another matter. As usual, it will need a combination of data, processes, consulting and technology to make it happen.