Lead Scoring for a Silicon Valley SaaS Company
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Lead Scoring for a Silicon Valley SaaS Company

Lead Scoring of over 50,000 prospective customer accounts for a software company. Silicon Valley SaaS/Software company with over 1,000 enterprise customers in the manufacturing vertical.

Overview

Prospecting an Existing Database with Accurate, Timely Lead Scoring

A successful Silicon Valley SaaS company with a manufacturing industry focus had its own CRM populated with plentiful data. The client had collected information on more than 50,000 target customers including contacts details, email, and physical address. In an effort to grow its business even more, they looked to mine their existing data for extra opportunities.

The client had a clear sense of its most successful target markets and the shared characteristics for their customers. Rather than randomly unleashing its sales and marketing efforts on all 50,000 potential accounts in a manner that lacked process and method, they decided to implement a lead scoring methodology. Lead scoring allowed the client to segment their prospect base into several tiers based on relevant characteristics such as manufacturing operations, manufacturing methodologies, product types, technology stack, and distribution.

After scoring only 100 of the prospective customers in their CRM, the client realized they were facing a substantial resource challenge. Processing and scoring 100 records took an excessive amount of time for internal sales and support staff, but they needed to get the data as quickly as possible without taking away from other priority tasks.

Challenge

Prospecting an Existing Database with Accurate, Timely Lead Scoring

A successful Silicon Valley SaaS company with a manufacturing industry focus had its own CRM populated with plentiful data. The client had collected information on more than 50,000 target customers including contacts details, email, and physical address. In an effort to grow its business even more, they looked to mine their existing data for extra opportunities.

The client had a clear sense of its most successful target markets and the shared characteristics for their customers. Rather than randomly unleashing its sales and marketing efforts on all 50,000 potential accounts in a manner that lacked process and method, they decided to implement a lead scoring methodology. Lead scoring allowed the client to segment their prospect base into several tiers based on relevant characteristics such as manufacturing operations, manufacturing methodologies, product types, technology stack, and distribution.

After scoring only 100 of the prospective customers in their CRM, the client realized they were facing a substantial resource challenge. Processing and scoring 100 records took an excessive amount of time for internal sales and support staff, but they needed to get the data as quickly as possible without taking away from other priority tasks.

Solution

Defined Buyer Personas and Data Points for Assivo Team Scoring

The client approached Assivo with the desire to scale their lead scoring process, complete the backlog of updating and scoring the existing 50,000 records, and form an ongoing relationship where all incoming leads would be scored. Assivo worked with the client to develop a deep understanding of the data points required for accurate scoring and how the client defined prospective buyers.

Armed with this information, Assivo staffed a team of 15 full-time associates to tackle the lead scoring backlog over the course of 2 months. Every single lead was reviewed, updated in the client’s CRM accurately and effectively, and scored based on the client’s criteria.

Result

Effective, Targeted Marketing Based on Reliable Lead Data

Assivo staff completed the backlog data append project to give the client a solid foundation for prospecting their own CRM system. To support ongoing data accuracy, Assivo dedicated 2 full-time associates to the client’s account to continuously monitor, cleanse, and enrich the CRM with lead scoring data and up-to-date contact information and related research. The client’s sales and marketing efforts became more targeted, personal, and effective once they were able to find relevant data on their prospective customers. The client was also able to save marketing and sales expenses by mining existing leads in their system and dedicating internal resources to more complex tasks tied to content generation and building relationships.

Overview
Challenge
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