How Cacheflow Improved LinkedIn Ads Attribution by 30% with Factors.ai
Cacheflow, a Palo Alto startup, offers a deal-closing platform that unifies CPQ, renewal management, and billing, and integrates CRM and ERP reporting. Cacheflow simplifies the entire deal lifecycle, from quoting to ARR reporting, decreasing admin workload for RevOps, sales, and finance teams.
Read on to learn how Cacheflow managed to improve ROI from LinkedIn advertisement and kickstart warm outbound using first-party signals provided by Factors.ai.
Everstage’s Challenges
Converting traffic into sales is like piecing a jigsaw puzzle. Manually tracking accounts and monitoring campaign data felt like chasing shadows. Incomplete data and bot traffic muddied the water, making it hard to see our true impact. Tools were supposed to help, but with their low account match rates, we were often left in the dark. We needed something better.
Limited visibility into LinkedIn Ads performance
Cacheflow lean GTM team relied heavily on LinkedIn Ads for inbound leads. While leads came in, the lack of detailed attribution data made it difficult to understand which specific aspects of their LinkedIn ad strategy were driving results. This limited data made increasing the advertising budget a gamble.
Transition to Google Analytics 4 (GA4) Worsens the Problem
The transition to GA4 from Universal Analytics further compounded the issue. GA4's user interface lacked the intuitiveness of its predecessor, making it difficult for the team to navigate and extract the insights they needed. Additionally, GA4's depth of information fell short compared to Universal Analytics, particularly in terms of tracking conversion rates effectively.
Cacheflow’s Attempts to Improve Lead Source Attribution
To tackle these challenges, the team implemented a multi-pronged approach. They used UTM parameters and custom cookies to track user activities on their website more effectively. Additionally, they employed offline conversion tracking within their ad platforms to capture conversions that happened outside of their website.
However, despite these efforts, a significant blind spot remained – 30-40% of their lead sources still couldn't be identified. This lack of clarity forced Riley to manually review all deals every quarter, a time-consuming and often inconclusive process that yielded minimal actionable insights.
These persistent challenges highlighted the urgent need for a solution like Factors.
Why Everstage chose Factors.ai
With Factors.ai, we're no longer in the dark. The data consolidation is like magic, no more juggling multiple platforms. Our ABM campaigns and, thus, our outreach got a big big boost in performance. In short, it's our single source of truth.
Cacheflow's journey with Factors began with a chance encounter between the chief executive officers of both companies at an industry event in the US. This sparked their interest in a solution to Cacheflow's marketing challenges, and competitive pricing made the decision to adopt Factors an easy one.
Understanding LinkedIn Ad Performance and Audience
From the outset, Factors provided valuable insights into Cacheflow's LinkedIn ad performance. By integrating view-through data from LinkedIn with account engagement data across Cacheflow's other channels (both first-party and third-party), Factors helped them understand how LinkedIn ads influenced accounts to explore their product and at which stage of the buying journey.
Factors provided demographic data on over half the companies engaging through LinkedIn, helping Cacheflow fine-tune their campaigns. With more precise job title targeting and the ability to remove irrelevant companies, Cacheflow felt more confident in their ad targeting. This enabled them to boost ad spend and improve conversion rates.
Enhanced Outbound Campaign
Factors' benefits extended beyond LinkedIn. Their capabilities enhanced Cacheflow's new outbound campaign with better account identification and engagement tracking.
Improved Conversion Rate Optimization
The solution further aided conversion rate optimization (CRO) by tracking account visits to new website pages. It also seamlessly integrated with HubSpot to monitor progress in the sales funnel. This enabled measurement of conversion rates at a company level, a significant improvement over their previous setup.
Tracking Content Efforts on Website
Cacheflow released a series of data-driven articles titled “The SaaS Proposal Study” and wanted to identify if these content pieces resonated with their readers. They used Factors to measure the impact of their blog posts and how many readers came across these pieces and signed up for a demo.
Revive closed lost deals
With Factors you can also track how many closed lost accounts suddenly show intent on the website. Cacheflow used this feature to set up Slack alerts when closed lost accounts showed intent and returned to their website. Now their BDR could see which account was showing interest in a particular feature at a particular time and strategically send personalized emails. This helped them gain 5-7 new reconverted deals worth $20K ACV every month.
Generating First-Party Intent Signals
One innovative use of Factors was in generating first-party intent signals. By bidding on competitors' terms, the Cacheflow team could identify interested companies that didn't initially convert but showed interest in similar products. This data was automatically sent to HubSpot, providing them with valuable intent signals traditionally purchased at high costs from third-party sources.
Exceptional Support
Cacheflow's experience with Factors' support has been exceptional. Regular sessions with their dedicated CSM, provided not only customized reports but also empowered them to build their own. This fostered self-sufficiency in their marketing efforts.
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The Results
With Factors.ai, we've seen real results. It simplified our data, made our campaigns smarter, and boosted engagement. Simply put, it made our work more efficient and effective.
With Factors.ai, we've seen real results. It simplified our data, made our campaigns smarter, and boosted engagement. Simply put, it made our work more efficient and effective.
Future
Converting traffic into sales is like piecing a jigsaw puzzle. Manually tracking accounts and monitoring campaign data felt like chasing shadows. Incomplete data and bot traffic muddied the water, making it hard to see our true impact. Tools were supposed to help, but with their low account match rates, we were often left in the dark. We needed something better.
Cacheflow now also aims to bolster brand presence through content marketing and thought leadership. This includes brand ads, data-driven industry benchmarks, and insights showcasing their differentiation. Tracking long-term ROI with Factors on this brand awareness content allows for a more balanced marketing strategy, driving both immediate pipeline and long-term brand value.
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