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Tido Carriero
Tido Carriero
Koala Content Reports: The Deep-Dive

Koala Content Reports: The Deep-Dive

We've learned that many of the best B2B companies - especially those with a PLG motion - have woefully inefficient sales conversion of enterprise accounts because they fail to recognize and act on enterprise buying signals.

Somewhat unintuitively, the strongest indicator of an enterprise sales-qualified opportunity isn't product usage data but when someone in your enterprise ICP researches your website, help centre, and technical docs.

Most enterprise buyers aren't early adopters sending production data without an Enterprise MSA, so you typically won't find them using the product but rather researching your enterprise offering.

Koala Content Reports differ from what you'll see in any other marketing attribution tool, so we wanted to dive deep into the origin story, show an example content report, and teach you how to apply learnings to drive more pipeline and top-level company strategy.

The Origin Story

In our early days, during our quest to find product-market fit, we interviewed as many fast-growing B2B PLG companies as possible to talk to us. We were trying to learn how these companies leveraged product usage data to drive upsell, cross-sell, and expansion. But what we found surprised us.

Surprisingly, the most advanced PLG companies were not building models based on product data. Yes, somewhere in the company, there was some BI dashboard that reported on all of the over-quota users, and these companies had set up an inside sales team focused on getting those accounts right-sized, but that wasn't where they were generating the majority of their pipeline.

So what were the most advanced companies doing? They were working with their data science teams to build sophisticated MQL definitions. Specifically, they were trying to understand every single action that a prospect could take across the entire buying journey — including content consumption, form fills, product lifecycle events — and they were trying to understand which of these actions was most correlated with a sales qualified opp being created.

What several of these companies had found is that high product usage wasn't actually the biggest predictor of true enterprise sales qualified opps. Enterprises buy software very differently from the initial "PLG" cohort of early adopters. Enterprises are much more risk-averse — for instance, a true enterprise probably isn't going to send real data into the system without a legal agreement in place. What they found is that enterprises were actively engaged and "in" the store, but instead of driving product usage, they were consuming a lot of very specific marketing content. They were trying to understand how the enterprise offering worked — checking out the security posture, whether or not existing enterprise systems could integrate with the product, how various advanced features worked, etc.

If you zoom out slightly, this makes perfect sense: (most) people don't read technical docs for fun — people read this content because they have a problem they are trying to solve and they are a bit stuck, so they need help. And it turns out: if you try to start a conversation with someone who is stuck right at the moment they need help, they are about 50-100x more likely to start a sales conversation than they would be on the average Tuesday morning.

An example Content Report

Koala Content Reports replicate the same process that these advanced data teams were doing in-house. Before we get into the nitty gritty of the data science, here's a screenshot of a Koala customer's actual Content Report (we've anonymized the URLs to use Koala pages, but the data is from a real customer and representative of most Content Reports):

Content Reports Example

Conversion event. In the report you see, the conversion event we chose was a Stage 1 -> Stage 2 transition. Like many companies, this customer is very focused on using demand gen to drive Stage 2 opps, which is when the Sales team formally accepts the opportunity and begins to work it.

Conversion window. In the report you see, the conversion window is 28 days. Because content consumption often happens for a week leading up to a demo being booked and then another 1-2 weeks can go by before the opp is qualified and formally accepted by Sales, this customer felt like a 28 day conversion window was most relevant.

As you might expect, the best-converting action for this company is when a demo form fill happens. 13% of the time this demo form-fill turns into a Stage 2 Opp within 28 days. However, there's a lot of other actions that customers can take that are almost as predictive of a Stage 2 Opp within 28 days. What's even more surprising about this is that the demo form fill is a highly systemized process — this particular company has an SLA to get a meeting booked within 30 minutes. But these other actions weren't systematized at all when we first built the content report you're seeing, and yet they convert almost as well.

How to use Content Reports

Triggering sales plays. The most obvious thing that you'd want to do with a Content Report is to use your highest-converting content as a trigger to start a sales play — chances are you have content that converts as well as an inbound demo request! For anything you'd like the Sales team to act on, you can send an Intent Signal through Koala or even set up an automation (PS - Koala can do that too!).

Understanding different parts of the journey. One of our customers wanted to understand the different parts of their buying journey, so they made three different content reports to understand what actions led to self-service trials being started, what actions led to SQOs being created, and what actions led to deals going to Closed Won. Interestingly, they found pretty different patterns — their help center articles and guides were very influential in driving self-service trials, their enterprise feature docs were influential in driving net new opps, and their legal documents played a surprisingly important role in driving forward late-stage pipeline.

Informing pricing & packaging. A few of our customers have been surprised at the topics that were leading to SQOs. For instance, one customer realized that some of the features they had made available on the self-service plan were shooting off the charts as features that predicted a sales conversation. After layering in some qualitative research, they realized that despite the feature being available on self-service, it was often too complicated to actually use without support, so it was leading to Sales conversations. They are now shipping an update to pricing and packaging that removes this feature from the self-service plan (and instead are adding some other features that weren't actually leading driving sales conversations).

Understanding which content is performing best. You can slice and dice your Content Reports in lots of ways — for instance, if you want to see which blog post or case study converts the best, you can easily filter. We've seen customers use this to figure out which content is working so they can make more content like that, but also so that they can leverage their best content in sales plays.

Further reading

We obsessed over hundreds of Content Reports for leading hypergrowth SaaS companies to understand what type of content leads to a higher win rate... we compiled it into our own report. Check it out:

We're looking forward to hearing your feedback as we prepare for our biggest announcement yet, coming soon!

Interested in speaking with sales? Contact [email protected]

Feedback, questions, comments, or want to chat? Reach out to [email protected]

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