use cases Posts

The Six Dimensions for Expanding Customer Engagement and TCV

The Six Dimensions for Expanding Customer Engagement and TCV

When corporate customers see compelling value in a given SaaS offering they are capable of increasing their adoption rapidly throughout their organization. In recent times this has happened with Box, Netsuite, Salesforce, ServiceNow, Slack, Splunk, Workday, and other vendors’ software. What I don’t see happening often enough is tech executives or sales teams adopting an intentional strategy to help their major customers to expand and deepen their utilization of the product or service in question.

Land & Expand is a Business Strategy – Not a Sales Tactic

Land & Expand is a Business Strategy – Not a Sales Tactic

In selling to business customers virtually every SaaS/XaaS company claims to be pursuing a land and expand strategy, to make their subscription and/or consumption business model generate the growth and profits that their investors and executives are expecting. Some companies are already demonstrating emerging best practices in this area though most startups and fast-growing companies still struggle to make their “strategy” pay off. Why is it such a struggle, and what can they do to crack the code?

How Splunk is Playing for Power in Big Data

How Splunk is Playing for Power in Big Data

Since 2009, big data has progressed from being an awkwardly named though highly touted super-category to being an awkwardly named and over-hyped bandwagon category. During this time Splunk has quietly gone about building a leadership position in a few gritty but mission-critical sub-categories such as log search, security information and event management (SIEM), and operational analytics. Splunk’s machine-based indexing, search, and analytics engine also qualifies it to play in another emerging super-category – the internet of things (IOT). With around $420m in revenues and growing at 50% or so every year, Splunk has got everyone’s attention despite being much smaller than many much larger big-data pretenders such as IBM. How has the company achieved this, what new challenges does it face going forward, and what every other player in big data learn from Splunk’s progress thus far?