With HockeyStack, not only can you measure and analyze your marketing and sales programs, but you can also measure the effectiveness of your (often expensive) martech tools, like Qualified.
Qualified is a conversational marketing platform that features chatbots, meeting schedulers, website personalization, and AI-powered video chat. And this report will help you figure out if the juice is worth the squeeze.
More specifically, this report analyzes how well the Qualified chatbot influences leads, pipeline, and sales velocity by measuring:
Website personalization, meeting schedulers, and chatbots promise to fill your pipeline faster. But do they work? Or are they just taking credit for sales that would have occurred anyways?
You need to know.
So we built this report so you can measure the effectiveness of Qualified’s chatbot using data.
Let’s jump in.
First up, chatbot-sourced revenue metrics at a glance.
“Chatbot sourced” refers to all leads that entered through the Qualified chatbot on the website as opposed to the form.
Revenue metrics include:
This section of the report doesn’t tell us whether or not the chatbot had real influence over pipeline.
But it gives us a snapshot of the volume entering through the chatbot.
For example, deals and pipeline generated through the chatbot have steadily increased over the last 13 months with the exception of a slow December and January. And 45% of all MQLs come through the chatbot as opposed to other sources. So far so good.
But if we want to identify marketing influence, we need to compare chatbot deals to website form deals and measure the difference in opportunities and pipeline generated by the two.
So let’s jump to the next section.
“Marketing influence” has become a highly contentious topic in B2B 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 “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 analyze incremental lift: the lift in conversions (positive or negative) that are attributable to a specific marketing activity and that wouldn’t have occurred without it.
To do that, you need a control group who doesn’t experience an activity and a treatment group who does. The difference between the two groups is the incremental lift, or, in this case, the “influence.”
In HockeyStack, you can do this in two ways:
First, you can use lift analysis to estimate the increased likelihood of someone converting based on the marketing activity they engaged with. For example, how much more likely are newsletter subscribers to book a demo than non-subscribers? Lift analysis will tell you.
Second, you can compare conversion rates between people who took an action and those who 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 chatbot influence by comparing the following:
So, then, does the Qualified chatbot actually influence deals compared to standard web forms? Or does it just take credit for pipeline that would have materialized anyways?
This report uses dummy data. Actual results vary between our customers.
But in this example, the answer is yes- it works!
The Qualified chatbot converts visitors to demos more than twice as much as the web form. The leads that book those demos turn into sales qualified opportunities (SQOs) 8% more than those that come through web forms, and they spend nearly $10,0000 more a year. Last, account executives win chatbot-sourced SQOs 22% more, resulting in fatter pipelines and more revenue.
Bottom line: if this data were real, it proves that Qualified’s chatbot makes sales more efficient by sourcing better leads who spend more and convert faster than those that convert through the website form.
In short, it accelerates sales velocity- the rate at which a prospect moves through your pipeline and earns you revenue.
Last, lift analysis.
Like we mentioned above, lift analysis is another way to estimate incrementality.
Since HockeyStack tracks customer touchpoints, it knows who engaged the chatbot and who didn’t and what downstream outcomes came from it.
People who engage the chatbot are 2.3 times more likely to turn into an opportunity than those that don’t. And of those opportunities, they’re 4.5 times more likely to convert into a paying customer (closed/won) than if they didn’t engage the chatbot.
In this example, lift analysis gives us a data-backed case that justifies the high retainer cost associated with Qualified.
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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