B2B SaaS Revenue Attribution with Lars Grønnegaard of Dreamdata. Blog posts, case studies, ads, and conferences are fantastic ways of attracting leads and generating revenue. But, how do you know which of your top-of-the-funnel activities led to that revenue? With a complex sales cycle, that´s not an easy task.  If this challenge sounds familiar to you, listen to this episode of SaaS Open Mic. My guest today is Lars Grønnegaard, the co-founder and CEO of Dreamdata.  Revenue Attribution in B2B SaaS When leading product at Trustpilot, Lars experienced a lot of product-led growth but he couldn’t pinpoint its impact on revenue.  We had lots of data, but it was connected from the product data directly to the revenue data, which was that was in our CRM, and in our subscription system. That problem, as we discovered, was of course about marketing. Lots of people were doing things in the go to market that were impacting revenue. But they didn’t know if it actually worked, or what worked and what didn’t work.  Lars and I speak about revenue attribution, the process of connecting business tacts, like ads or content, to business outcomes. There’s a set of multiple data silos in your company. Getting all the data out and connecting it in a meaningful way, is just such a huge problem and challenge that it remains unsolved for pretty much all SaaS businesses out there.  Site Analytics for Complex Sales Cycles Similar to any other B2B SaaS business, Dreamdata’s deals are complex. They engage with multiple people during a sales cycle. Lars shared that it takes their team around three months from the time somebody discovers Dreamdata, through a demo request, sign up, until the ultimate sale. During that time the team interacts with multiple people.

Dreamdata completely abandoned using Google Analytics for their business. Lars explains how Google Analytics didn’t allow for multi-touch journeys that a B2B business needs and how it doesn’t integrate with business results. I think that the fundamental problem about Google Analytics is that it’s not account-based. On This Episode of SaaS Open Mic The challenges of revenue attribution for B2B SaaS businesses 
The do’s and don’ts of revenue attribution
Google Analytics for complex sales cycles  
Why you can’t measure everything but you should measure what you can 
[INST] B2B SaaS Revenue Attribution with Lars Grønnegaard of Dreamdata [/INST]
 Blog posts, case studies, ads, and conferences are fantastic ways of attracting leads and generating revenue. But, how do you know which of your top-of-the-funnel activities led to that revenue? With a complex sales cycle, that´s not an easy task.  If this challenge sounds familiar to you, listen to this episode of SaaS Open Mic. My guest today is Lars Grønnegaard, the co-founder and CEO of Dreamdata.  Revenue Attribution in B2B SaaS When leading product at Trustpilot, Lars experienced a lot of product-led growth but he couldn’t pinpoint its impact on revenue.  We had lots of data, but it was connected from the product data directly to the revenue data, which was that was in our CRM, and in our subscription system. That problem, as we discovered, was of course about marketing. Lots of people were doing things in the go to market that were impacting revenue. But they didn’t know if it actually worked, or what worked and what didn’t work.  Lars and I speak about revenue attribution, the process of connecting business tacts, like ads or content, to business outcomes. There’s a set of multiple data silos in your company. Getting all the data out and connecting it in a meaningful way, is just such a huge problem and challenge that it remains unsolved for pretty much all SaaS businesses out there.  Site Analytics for Complex Sales Cycles Similar to any other B2B SaaS business, Dreamdata’s deals are complex. They engage with multiple people during a sales cycle. Lars shared that it takes their team around three months from the time somebody discovers Dreamdata, through a demo request, sign up, until the ultimate sale. During that time the team interacts with multiple people.

Dreamdata completely abandoned using Google Analytics for their business. Lars explains how Google Analytics didn’t allow for multi-touch journeys that a B2B business needs and how it doesn’t integrate with business results. I think that the fundamental problem about Google Analytics is that it’s not account-based. On This Episode of SaaS Open Mic The challenges of revenue attribution for B2B SaaS businesses 
The do’s and don’ts of revenue attribution
Google Analytics for complex sales cycles  
Why you can’t measure everything but you should measure what you can 
<sys> [INST] B2B SaaS Revenue Attribution with Lars Grønnegaard of Dreamdata [/INST] Blog posts, case studies, ads, and conferences are fantastic ways of attracting leads and generating revenue. But, how do you know which of your top-of-the-funnel activities led to that revenue? With a complex sales cycle, that´s not an easy task.  If this challenge sounds familiar to you, listen to this episode of SaaS Open Mic. My guest today is Lars Grønnegaard, the co-founder and CEO of Dreamdata.  Revenue Attribution in B2B SaaS When leading product at Trustpilot, Lars experienced a lot of product-led growth but he couldn’t pinpoint its impact on revenue.  We had lots of data, but it was connected from the product data directly to the revenue data, which was that was in our CRM, and in our subscription system. That problem, as we discovered, was of course about marketing. Lots of people were doing things in the go to market that were impacting revenue. But they didn’t know if it actually worked, or what worked and what didn’t work.  Lars and I speak about revenue attribution, the process of connecting business tacts, like ads or content, to business outcomes. There’s a set of multiple data silos in your company. Getting all the data out and connecting it in a meaningful way, is just such a huge problem and challenge that it remains unsolved for pretty much all SaaS businesses out there.  Site Analytics for Complex Sales Cycles Similar to any other B2B SaaS business, Dreamdata’s deals are complex. They engage with multiple people during a sales cycle. Lars shared that it takes their team around three months from the time somebody discovers Dreamdata, through a demo request, sign up, until the ultimate sale. During that time the team interacts with multiple people.

Dreamdata completely abandoned using Google Analytics for their business. Lars explains how Google Analytics didn’t allow for multi-touch journeys that a B2B business needs and how it doesn’t integrate with business results. I think that the fundamental problem about Google Analytics is that it’s not account-based. On This Episode of SaaS Open Mic The challenges of revenue attribution for B2B SaaS businesses 
The do’s and don’ts of revenue attribution
Google Analytics for complex sales cycles  
Why you can’t measure everything but you should measure what you can  </sys