Jeff Hartley and the team at Terracotta faced that exact challenge, and used a very interesting approach to lead scoring in order to categorize their buyers based on where they were in their buying journey. I thoroughly enjoyed chatting with Jeff while writing Digital Body Language, and hopefully you'll enjoy this case study as much:
Terracotta: Lead Scoring A Buyer’s Journey in Open Source
As a leading open-source software company, Terracotta has a challenge that most marketers would gladly choose to manage: too many leads. However, that wealth can create problems when you only have a few direct sales professionals. Those leads were generated from interest in a very strong, full-featured, open-source
version of its software – but which were ideal prospects to target for commercial service offerings?
The Terracotta marketing team turned to lead scoring to allow them to understand the process their buyers went through in understanding and evaluating their products. First, they categorized the buyer’s journey into a path called RESITD – Recognize, Evaluate, Sample, Integrate, Test, Deploy. Lead scoring was used to categorize each buyer in this buying path. The key metrics of each phase differed, depending on the likely approach a buyer would have:
- Recognition: Awareness metrics such as the number of visits
- Evaluate: Reading of introductory documents on Terracotta benefits
- Sample: Downloading of the Terracotta open source product
- Integrate: Forum activity, application-specific integration documents, or
downloading of pre-packaged integration modules
- Test: Reading of detailed tuning guides, sample test plans
- Deploy: Reading deployment guides, reading about enterprise subscription or deployment services, and “phone-home” capabilities in the software itself
This framework allowed Terracotta to map and guide the buyer’s journey, even in an environment where direct interaction with the end purchaser was quite rare. Sales professionals at Terracotta were provided with deep insights into the buyer stage for each of their accounts, and were sent real-time notifications as buyers progressed from one stage to another.
Over 6 iterations, the Terracotta team continually refined their algorithms for understanding their audience. Insights such as a tight focus on recency and frequency as factors in evaluating any sign of interest came from this iterative refinement process. Evidence of a need for the high scale clustering software that Terracotta provides could be deemed out of date if it was more than a few months old, due to the changing nature of buyer needs. This detailed, automatically-created map of a buyer’s journey allowed their sales team to focus on the key prospects who were ready to move forward with a purchase, and allow marketing to guide the evolution of the others.
Understanding the buying process is a critical thing to focus on in B2B marketing, and Jeff and the team at Terracotta have done a great job of mapping it out and scoring prospects to understand their stage.