This dashboard measures your blog’s influence on sales velocity:
This report investigates whether or not blog pageviews have a measurable lift on sales velocity metrics like demos, opportunities, win rate, annual contract value, and sales cycle durations.
For example, does reading one blog post increase demo conversions? Does reading 2 blog posts increase annual contract value? Or does reading 8 blog posts increase win rates? And by how much? This report will tell you.
Use this template to move beyond surface-level content consumption metrics and prove whether or not blog content makes sales more efficient.
“Marketing influence” is a highly contentious topic in marketing. Rightfully so: though marketers want to prove their contribution to revenue, not every piece of content a buyer engages with will actually influence their decision to buy. Much of it won’t.
Consequently, marketers need to support their “influence” with data. At least if they want to be taken seriously. What kind of data? The best way to prove marketing’s influence on any goal is to estimate incremental lift: the positive or negative lift in conversions attributable to a specific marketing activity.
In HockeyStack, you can do this in two ways:
First, you can use lift analysis to estimate the increased likelihood of someone converting on a goal based on the marketing activity they engaged with. For example, how much more likely are newsletter subscribers to buy than non-subscribers? Lift analysis will tell you.
Second, you can compare conversion rates between people who took an action and those that didn’t. For example, do leads from channel partners turn into opportunities at a higher rate than non-partner leads? Comparing conversion rates will tell you.
Both methods use a different approach to reach a similar outcome: a strong signal of positive or negative lift attributable to a specific marketing activity. In this report, we use the latter method to analyze blog influence.
For example:
Why did we choose demo CVR, opportunity rate, win rate, ACV, and sales cycle duration?
Sales velocity. Sales velocity is a measure of how quickly a prospect moves through your pipeline and earns you revenue. It’s also a strong indicator of whether or not marketing is improving sales efficiency.
So we compared the blog's influence on the individual parts of sales velocity to prove whether or not the blog is doing its job: making sales easier.
Based on the data above, people who viewed multiple blog posts vs. those who viewed none were far and away better customers: they booked demos more often, qualified at a higher rate, closed more often and in fewer days, and spent more money.
What do you do with this insight? Get more eyes on blog content.
In this example, for every buyer who engages with multiple blog posts on their path to purchase, you’d earn $1,900 more in annual contract value than if they hadn’t read any. With 100 new customers a year, that's an extra $190,000 in ACV. Not to mention leads who read multiple blog posts convert into qualified opportunities twice as much, meaning you'd need far fewer blog readers than non-readers to hit your pipeline target.
But what content do you need to get eyes on?
If you know that people who view multiple blog posts are better customers, then what blog posts do you need to promote more often so more potential buyers engage with more of them? The ones closed/won accounts view most.
In HockeyStack, you can build a table that features a list of the top blog posts viewed most by closed/won accounts, complete with average time on page and the percentage of accounts who engaged with them before the demo.
Use this list to promote content you know buyers spend time reading and find valuable. An watch your sales velocity go through the roof ;)
Learn more about how HockeyStack helps marketing, revenue, and sales teams surface and action insights like the ones in this template by exploring the interactive demo or booking a virtual demo.
What exactly is HockeyStack? How do we help marketers drive revenue more efficiently?
Jump in to uncover the ins and outs of Marketing Mix Modeling – from its mechanics to its ideal applications – with Drew.
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