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Optimizing Lead Funnel and Conversions with AI: A CloudCheckr Case Study
Technology Category
- Infrastructure as a Service (IaaS) - Public Cloud
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Functions
- Product Research & Development
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
- Inventory Management
Services
- Cloud Planning, Design & Implementation Services
The Challenge
CloudCheckr, a cloud management platform serving a wide range of customers, was facing challenges with their lead funnel. They had leads that were 'stuck' in the top or middle of the funnel, and their email campaign strategy was underperforming. The Sales and Marketing teams were keen on finding new ways to optimize their lead funnel and discover more opportunities within it. Despite their efforts to motivate these stuck leads through email marketing and nurture campaigns, they were not achieving the desired results. They were also wary of burdening their Sales Development team with the task of chasing potentially cold leads.
About The Customer
CloudCheckr is a cloud management platform that provides total visibility across multiple public cloud and hybrid workloads. Their customer base is diverse, ranging from government agencies to large enterprises and managed service providers. These customers use CloudCheckr's SaaS-based platform to secure, manage, and govern their most sensitive environments. The Sales and Marketing teams within CloudCheckr are always looking for innovative ways to optimize their lead funnel and find more opportunities within it.
The Solution
CloudCheckr decided to explore Conversica AI Assistants to attract and acquire new customers. Their primary goal was to accelerate conversions at each stage of the funnel, especially for leads stuck in the 'awareness' or 'interest' stages but had not yet met the MQL threshold. They adopted a two-phased approach. First, they aimed to capture intent after major milestones like booth scans at in-person events and webinar attendance or downloads. The Conversational AI solution personally touched each lead post-event to determine which leads were sales-ready and which should be nurtured over time. Second, they targeted prospects who had previously expressed interest but went dark for more than 90 days. They used their AI Assistant in tandem with Marketo to drive content consumption for these static leads. Following their initial successes, they expanded the capabilities of their Conversational Marketing and Sales solution to include additional skills.
Operational Impact
Quantitative Benefit
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