Growth isn’t just about marketing; it's about the entire funnel. This means I have to know what’s happening on the website, with the open opportunities, what went wrong in the closed-lost deals, and what went right in the closed-won deals. If I see a pattern, we work on experiments to fix the problems or scale what’s already working—but there always needs to be a pattern. This daily report is very important to me as it helps me identify patterns or understand if it’s a one-off thing.
What makes a pattern? I don’t have a defined answer for this. In some cases, I can observe a pattern on a monthly or even quarterly views; for example, for opportunities, pipeline, and closed-won deals; but for some, I can observe a pattern on a daily view; for example, live demo:contact sales conversions.
In the first table, I look at the high-level daily stats: the number of daily website visitors, how many visit product pages, how many visit high-intent pages (case studies, pricing, live-demo), how many visit the contact sales form, and how many actually submit the form.
Then, among these submissions, how many have become a deal (qualified), what is the conversion rate between form submission and deals, then what’s the percentage of first calls booked. Apart from these, I look at how many of these website visits actually came from competitor and brand campaigns on Google.
Next, we have the visualization of daily visitors - we know there’s a decrease on the weekends, and that’s fine, but apart from that, if we observe anything different, then we look at possible explanations. For example, you can see there’s generally a peak on Tuesdays, and it’s because we release the weekly Labs reports on Tuesdays.
The third chart shows the form submissions vs. first meeting booked data - this is important for us because we only allow booking if the company is qualified, so this shows us if we’re bringing qualified visitors and qualified submissions. If we see a decrease or increase in this ratio for two days in a row, we begin analyzing the website traffic and sources to see if there’s anything in particular that brings us this. (Caveat: if it’s a holiday season, or a weekend, or similar, we don’t do anything.)
Next, we look at the data on the industry level. Which industries are we getting our traffic from? What do we see in terms of their product page visits, high-intent page visits, contact sales form views, and submissions? What’s their conversion rates, how many of these conversions actually booked calls, and what’s the view-to-submit rate for each industry.
The last column doesn’t exist in the first report; the reason it exists here is because we want to understand if there are any industries that don’t necessarily fall under our ICP but with high view-to-submit rates to help us with expansion.
The next one is similar to the industry board, but this time it’s for the employee sizes. The logic is similar; we are trying to see if there are any patterns among different sizes of companies. Are we seeing any company sizes that we don’t target?
The sixth board shows the contact sales journey; once they land to the website, what do our visitors do? How many of them go to the Flow, how many go to our blog; among these, how many visit product pages, then high-intent pages, form submissions, and pipeline?
We use this funnel view to understand the website journey and improve the conversion rates. For instance, if we’re seeing a lower conversion rate from high-intent pages to contact sales, then we dive deeper and see if there are any pages decreasing this average, if so, what’s the heatmap of this page, what do our visitors do here compared to other high-intent pages? Do we observe this behavior among all website visitors or in specific segments?
This is an interesting one, although we know that one page doesn’t bring all the deals; we want to understand after which page, we end up generating more deals compared to others. This helps us to understand the last part of the pre-deal journey.
But the previous report alone isn’t enough; we look at this data combined with the lift board where we actually can see the causal link between the pages and deals. This is one of our most important reports because it helps us to measure the actual impact of each of our pages.
Lastly, we have the weekly metrics report. This is the same as the first one but in the first one, we look on a daily basis; and in this one, we look on a weekly basis. For example, for website visits or high-intent pages, looking on a daily basis makes sense, but for conversion rates and deals created, it’s more helpful to look on a weekly basis.
Here is the full view of the dashboard - next up, we’ll share the monthly and quarterly versions of these dashboards where we analyze the entire funnel.
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.
Canberk Beker is Head of Growth at HockeyStack.
LinkedIn: https://www.linkedin.com/in/canberkbeker/
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