How Multiplier Gained Complete Account Engagement Visibility with Factors.ai

Multiplier's marketing efforts were a powerhouse, generating a staggering 80% of their overall revenue.  Inbound marketing, in particular, thrived, driving a remarkable 90% within that figure. Their website, therefore, was a crucial engine for lead generation.  

An effective way for them to boost revenue was by improving conversions on the website. 

But the company had just about 6% visitor to form fill rate—which meant 94% of their website traffic was anonymous. 

To remedy this the team used a tool inside Google Analytics that provided them with a 'client ID' that could be mapped in CRM to track the user's engagement. 

Unfortunately, the release of Google Analytics 4 (GA4) disrupted this process. GA4 utilizes a "user pseudo ID," an anonymous 22-digit identifier that doesn't map to any system providing visitor identification. This left Multiplier with a significant blind spot.

This means the team now had NO rich insights into who was landing on their website. Was the traffic from ICP accounts or was it irrelevant? What were these visitors doing on the website? How did they engage with them on other channels? 

This resulted in a blind spot for the team. That resulted in challenges like:

• Loss of user insights: Basic information like location, browser, and time spent on the site remained available, but crucial details like company affiliation and engagement history were lost.
• Hampered lead nurturing: Without the ability to identify high-intent leads, effectively tracking user journeys and personalizing marketing outreach became impossible. 

To bridge this knowledge gap, Multiplier explored implementing an enterprise Account Identification platform. This held promise, offering the ability to identify and map the engagement of companies visiting their website.

But that hit a roadblock, too. 

• Firstly, the platform's hefty price tag, exceeding $60,000, significantly exceeded their budget.  
• Secondly, the feature set beyond account identification proved to be largely irrelevant to their needs.

But the challenges didn't stop there.

The team wanted to grow outbound motion to take a bigger piece of the revenue mix, but neither their existing set-up nor the enterprise account identification tool could help with the goal. 

They needed a solution that could help them identify high-engagement accounts, understand the effectiveness of campaigns, and determine if outbound was working. 

A solution like Factors.ai.