During my pre-HockeyStack life, one of the things that challenged me the most was interpreting changes in quarterly metrics. Let’s say, we didn’t make a massive structural change in targeting or in the sales process. Throughout the quarter, there was no problem with the number of opportunities, but the deal size remained low, and you ended up missing the pipeline target. What you hear from the sales team is that they had to lower the deal amount; otherwise, it wouldn’t have converted, even though those deals appeared exactly identical to those from the previous quarter. What happens if this repeats next quarter? Can you guarantee that it won’t happen? Could it be just seasonal or something macroeconomic? I know that many revenue leaders try to avoid using these excuses as it sounds like taking the easy way out, but what if there were data to prove this? This is exactly how Labs was born.
The 2023 report was our first comprehensive benchmark report, followed by Q1, and now Q2—our 20th report in 2024. As I was analyzing the data, I realized that there are indeed some patterns between quarters and years, and that some changes can actually be explained by seasonality. As we gathered more data points since January 2023, it became easier to justify what’s happening. In this report, we’ve kept the sample companies and sample size almost the same as in Q1 to ensure that we’re comparing apples to apples. Similar to the Q1 report, I tried to maintain the same structure, starting with ad spend and budget allocation data, then moving to conversion rate and channel performance data, followed by MQL data, pipeline numbers, and the state of revenue.
MQL: Direct form submissions such as demo, pricing page, and contact us. This doesn’t include any ebook downloads, webinar registrations or anything like that. Currently there’s an inflation of terms in B2B marketing, some say ‘hand raisers’, some say ‘high intent conversions’. I’m calling this MQL simply because I like the sound of it.
SQL: Pipeline created. Every company has different definitions, but we unified this on the backend and used the SQL definition for when the pipeline is actually created.
Sales Cycle: Starts from the date of deal created, not from MQL created. The reason for this is that since we included both inbound and outbound, and outbound doesn’t start from the MQL level, it would have skewed the average.
Deal Size: Total new deal amount added divided by the number of qualified deals (also known as Deal Value)
ACV: Total new business revenue added divided by the number of closed-won deals (also known as Average Contract Value, Selling Price)
CW: Closed won deals, net new business, new revenue.
Sample Size: 94 B2B SaaS companies. (the sample companies are 97.9% the same)
Attribution Model: Position-based because it offers a balanced view on the importance of each touchpoint in a customer's journey towards a conversion. This method assigns more credit to the first and last interactions and distributes the remaining 20% among the middle interactions.
Sample Description:
- Using HockeyStack at least since December 1st, 2023.
- At least $25k monthly paid spend per company
- From $10M ARR to $2B ARR; average ACV from $8.2K to $150K.
- 72% NAM, 20% UK, 8% Europe
What we analyzed:
- More than $132M ad spend for Q2-24, and more than $130M ad spend in Q1-24.
- More than $650M pipeline and $100M revenue in two quarters.
Caveat: This doesn't mean that the ad spend in these two quarters resulted in a 2.5x pipeline ROI and negative revenue ROI. It's important to consider the length of sales cycles. The ad spend in Q1 not only impacts the pipeline for Q1-24 but also impacts the pipeline in Q2-24. Similarly, the ad spend in Q2-24 will not only influence the pipeline in Q2-24 but it will also influence the pipeline and revenue in Q3-24.
I think one of the most interesting aspects is the total ad spend, which almost didn’t change in Q2-24. The Q2 data shows that companies in our dataset spent just 0.69% more than what they spent in the first quarter.
According to the 2023 Recap Report, Google had the largest budget share with 47.72% among the B2B SaaS companies. Linkedin was close behind with 45.84%, followed by Facebook at 4.8% and Bing at 1.6%.
That was the yearly average in 2023; but things were slightly different in the last quarter of 2023 where Google had a total of 48% of the budget. As discussed in the previous reports, this wasn’t surprising as companies likely focused on short-term wins before the year’s end. Furthermore, in 2023, Capterra, Display Network, Reddit, and Youtube each got less than 1% of the budget.
In the first quarter of 2024, there was a strategic shift—Linkedin, for the first time, became the leading channel with an average of 42.74% of the budget allocation. More notably, Google had a significant decrease, dropping from 47% to 39% of the budget. Interestingly, much of that budget was redirected to Facebook. In fact, Facebook’s budget was more than tripled compared to the 2023 average. Similar to Google, Bing also saw a substantial decrease, where the budget allocation dropped from 3% to less than 1%.
So in a nutshell, search channels experienced significant budget cuts in the first quarter of 2024 while most of the budgets were allocated to paid social. One reason for this could be that 2024 started with positive intentions for marketing teams, perhaps planning to invest more in branding— did this continue in Q2?
Unsurprisingly, Google and Linkedin got the most budget in the second quarter of 2024 - but the surprising thing was the narrow margin between these two channels. Google and Linkedin were nearly even in budget allocation, with just a 0.64% difference. With this outcome, Google once again became the channel with the largest share of the budget, receiving 45.72%, while Linkedin followed closely with 45.08%.
Another notable point is that Facebook got back to its 2023 levels—actually, even lower; the average budget allocation for Facebook dropped from 16% to just 3.04% (the 2023 average was 4.84%). It feels like marketing teams had a fresh start in 2024 with good intentions and gave Facebook another chance, only to return to previous levels after realizing that it wasn’t as effective.
It appears that much of Facebook’s budget was redirected back to paid search. In addition to Google, there has been a significant increase in Bing’s budget. In the Q1 Recap report, I claimed that Bing had its chance in the search engine war with Copilot last year and they lost it. However, in this second quarter, we are seeing that the budget allocation for Bing surged from 0.6% to 3.85%. We are also seeing an increase in general Bing search data - I was wrong.
In total, Linkedin and Google accounted for 90.80% of the paid media budget allocation, followed by Bing at 3.85% and Facebook at 3.04%. This means that only 2.31% of the budget was allocated to other channels. This time, the Display Network received the most budget within these smaller allocations at 0.8%, followed by YouTube, Reddit, and Capterra.
In 2023, Linkedin had the highest average MQL:SQL conversion rate with an average of 36.2%, which slightly decreased in the first quarter of 2024 to 35.82%. Although Linkedin still has the best conversion rate by far, we continue to see a decline in the second quarter of 2024, where conversion rate dropped to 33.33%. The number 33.33 looks aesthetically pleasing, at least.
When it comes to Google, there was a considerable increase in its conversion rate in the first quarter, where the average in 2023 was 21% and it jumped to 25.8% in Q1 2024. My hypothesis was that, with companies allocating less budget to Google, they had to be more laser-focused on campaigns and shift focus away from broad/low-intent campaigns to more effective ones. Now, things get interesting because, in the second quarter, we’re seeing the conversion rate return from 25.8% to 21.25%. So, the budget allocation for Google has returned to the 2023 level, and similarly, the conversion rate has decreased back to the same level. Is it just me, or does it seem like old habits are resurfacing? We’ll explore this further in the pipeline section, but could it be related to companies focusing on generating more MQLs from Google? If so, these companies indeed manage to do so, but do these MQLs actually convert? Is this Google or paid search in general?
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If this were the case, we might expect to see a similar impact on Bing. Bing’s average conversion rate was 22.03% in 2023, nearly identical at 22.01% in Q1, and still consistent at 22.1% in Q2. Despite increased budget allocation for Bing, this did not lead to a decrease in conversion rates as it did with Google.
In the first quarter, we observed that Facebook’s conversion rate decreased from 23% to 14%, likely influenced by an increase in budget and number of different campaigns. Then as briefly noted earlier, Facebook underwent a significant budget cut in Q2—I would have expected this cut to shift the focus back to using Facebook as a remarketing channel, potentially increasing conversion rates. However, the opposite happened; the conversion rate dropped further from 13.93% to 12.81%, even lower than the display network’s conversion rate of 12.96%.
We hadn’t included G2 and Capterra in previous reports, and I wasn’t planning to do so in this report either; however, the data I analyzed was too compelling not to mention. Although only about 0.5% of the budget was allocated to Capterra and it generated just a few thousand MQLs; its conversion rate of these MQLs was only 3.89%—the lowest among all channels by a significant margin. On the other hand, if we consider G2 as a channel, the MQLs generated directly from G2 had a conversion rate of 27%, the highest after Linkedin.
When it comes to other channels, Youtube maintained an average conversion rate of 6.13% (slightly down from 6.2% in the first quarter), and Reddit’s conversion rate was 3.97% (down from 4.5% in the first quarter).
Looking at SQL:closed won rates by channels, we’re seeing a consistent trend. Linkedin leads with a 29.61% close rate, although it’s worth noting this was higher at 30.41% in the first quarter. Google’s close rate has increased from 16.5% to 19.5% - so we’re seeing a different picture here than the MQL:SQL side, however 1/3 of the Google closed won deals in Q2 were created in Q1.
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On the other hand, Facebook continues to disappoint, with a decrease from 14.6% to 13.5%.
Lastly, Bing has had a strong quarter on every front; we’re seeing another improvement here, with the close rate increasing from 14.6% to 21.3%. I’m retracting my previous judgment—Bing isn’t dead.
According to our 2023 benchmarks, Q1-23 was the weakest quarter for MQLs, generating only 17.5% of the total. On the monthly view, January was the weakest month, contributing just 4% of the MQLs. Conversely, Q2 was the strongest quarter, generating 31% of the total MQLs—nearly double that of Q1-2023. On the monthly view, May was the best month for generating MQLs.
Note: These changes in MQL were not related to changes in spend - the spend remained relatively stable during those months in 2023. For example, the total ad spend difference between Q1 and Q2 of 2023 was less than 15%.(In 2024, it’s just 0.69%)
Then we released the Q1-2024 Recap report, the report showed very promising MQL figures. One crucial aspect to consider was whether Q1 would continue as the weakest quarter for MQLs when comparing the data from Q4-23 and Q2-24. Initial observations in Q1 suggested otherwise. Compared to Q4-23, B2B companies spent 6% less in the first quarter of 2024; however, the number of MQLs generated increased by 24.7%.
The reason for this increase in MQLs wasn’t due to ad channels getting cheaper, as CPCs and CPRs remained nearly the same. Instead, it was the websites themselves that converted better; the website conversion rates saw a significant increase in Q1-24 compared to Q4-23. My hypothesis was that this might be linked to the changes in budget allocation. Companies are investing more in Linkedin, where their targeting is more effective than on any other platform, resulting in more qualified website visitors. While the number of visitors doesn’t necessarily increase, the conversion rates do.
As mentioned, the total spend increased by just 0.69% in Q2; although spend didn’t really change, the total number of MQLs decreased by 8.64%.
We’re seeing similar numbers of website visitors across the two quarters; this suggests that the website conversion rates have decreased. Considering this situation alongside the changes in budget allocation, one could argue that allocating more budget to search didn’t yield the expected results. However, to come to this conclusion, we need to look at the pipeline and revenue metrics, which we’ll do in the next part.
In Q1-24, most of the MQLs were generated in the last month of the quarter, March - accounting for 44% of the total MQLs in that quarter. This was very similar to what we observed in Q1-23.
When we look at the second quarter metrics in 2023, the report shows that most MQLs were generated in May, followed by June and April. We’re seeing the exact same trend in 2024, with most MQLs in Q2-2024 generated in May, followed by June and April.
On the month-on-month basis,
- April: 29.34%
- May: 41.72%
- June: 35.57%
On a yearly basis, it seems that March was the best month for MQLs so far in 2024:
- January: 13.62%
- February: 15.63%
- March: 23%
- April: 14.01%
- May: 19.92%
- June: 16.98%
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Although the monthly performance within each quarter aligns closely with last year’s data, there has been a shift in the distribution of MQLs in 2024 compared to 2023. This year, we’re seeing 8.65% more MQLs generated in Q1 compared to Q2, whereas last year, there were 80% more MQLs generated in Q2 compared to Q1.
Although the second quarter wasn’t the best quarter in terms of the number of MQLs, the picture is slightly different when it comes to the number of SQLs. Despite an 8.65% decrease in the number of MQLs generated, the number of SQLs actually increased by 5.12% - indicating an approximate 8% increase in the MQL:SQL conversion rate.
When we analyzed the MQL:SQL conversion rates between Q4-23 and Q1-24, I mentioned that there was a 16% decrease in the first quarter of 2024 compared to the last quarter of 2023. I hypothesized two reasons for this decline: firstly, deal qualification criteria could have been relaxed at the end of the year in 2023 to maximize deal numbers and boost sales; secondly, it might have been related to deal sizes, as we observed that the average deal size in January surged by 91% compared to December, likely because closing deals right away wasn’t the top priority in the first quarter.
The average deal size in 2023 was $20.8K, peaking at $39K in January 2023, then steadily declining month by month throughout the year, reaching $12K in November 2023. It appeared that companies began the year with the highest ACVs and strictest qualification criteria, feeling less pressure to meet quotas. We observed a similar pattern in the first quarter of this year, where the average deal size in Q1-24 was $29.7K compared to $15.6K in Q4-23. A similar month-on-month trend also existed: January had an average deal size of $36K, which decreased to $28.5K in February and $24.5K in March.
Looking at the second quarter of 2024, the average deal size rose from $24.5K in March to $27.4K in April, then dropped to $26.9K in April, and further to $23.1K in May. This also meant that the average deal size in Q2 was 13% lower than in Q1.
This decrease in average deal size meant that although there was an increase in the MQL:SQL conversion rate and in the number of SQLs, it did not significantly impact the pipeline; in fact, the total pipeline generated in the second quarter was 3.22% lower than in the first quarter.
The first quarter of 2023 was the best for pipeline generation, with 30% of the total annual pipeline generated. In terms of monthly distribution, March had the highest pipeline, followed closely by January and February. This year, we observed a comparable pattern in the first quarter; however, the difference between March, and January and February this year was more pronounced, while January and February had almost identical pipeline amounts.
24% of the annual pipeline was generated in the second quarter of 2023, which was notably lower than the first quarter. In terms of months, May 2023 was the peak month for pipeline generation in the second quarter, followed by April and June.
Now, looking at 2024, we’re seeing a similar trend—actually, the situation looks a bit better. Although the second quarter had less pipeline than the first, the difference in total pipeline is just 3.22% compared to 6% in 2023.
In terms of month-on-month pipeline, we’re seeing the same trend as in 2023. May was the best month in the second quarter, followed by April and June.
Pipeline split by months in 2024:
- January: 12.84%
- February: 17.50%
- March: 20.46%
- April: 17.55%
- May: 17.76%
- June: 13.87%
Although the percentages are not completely identical, this split is the same as we had in the first six months of 2023.
In terms of total closed-won deals, the second quarter of 2023 had 8.1% more deals compared to the first quarter. On the monthly level, December was the top month in 2023, and on the quarterly level, Q4 was the top quarter with 30% of the annual deals closed. Comparing the second quarter of 2024 to the first quarter, our dataset indicates a similar pattern: Q2-24 has already seen 4.74% more closed-won deals than Q1-24.
I’m writing this report as of July 8th with the data up until July 6th, 2024; it’s important to note that we might see additional closed-won deals coming for the second quarter in the upcoming weeks as the quarter has just ended, but the data available already shows more deals closed in the second quarter than in the first.
I believe this phenomenon can be explained by the decrease in deal sizes. As discussed previously, the deal size decreased by 13% in the second quarter of 2024, mirroring the trend from 2023. This decrease in deal size has most likely helped closing more deals.
We can verify this assumption by looking at close rates. For instance, the Q1-24 Recap report shows that the SQL:CW close rate decreased by 43% in the first quarter of 2024 compared to the last quarter of 2023, while the deal size increased by 1.9x. In the second quarter of 2024, we’re seeing that the SQL:CW close rate got 14.9% better, while the average deal size got 13% lower compared to Q1-24.
When we focus only on the contract value of closed-won deals—I use ‘deal size’ for all qualified deals, and ‘contract value’ only for closed-won deals—we see that the average contract value in the second quarter of 2024 was 15.4% lower than in the first quarter. Meaning that, despite seeing 8.1% more closed-won deals in the second quarter, the total added revenue is almost 26% lower due to the decrease in the average contract value.
In 2023, 29% of the total revenue was generated in the first quarter, compared to 25.5% in the second quarter—meaning that the first quarter had 14% higher revenue than the second quarter. This year, we see that the added revenue difference between the first quarter and the second quarter is 26%—almost twice as much as last year. However, as previously mentioned, there may be new closed deals in the coming weeks, which will likely narrow this gap. We’re already seeing a smaller pipeline difference between the two quarters compared to last year, and the increase in the close rate suggests that these deals are likely to be closed—this could close the gap and bring the difference to a similar level as we had in 2023.
The second quarter of 2024 showed a shift back to the 2023 budget allocation, with Google regaining its lead over LinkedIn. The increase in the MQL:SQL conversion rate helped generate more SQLs compared to the first quarter, even though the number of MQLs decreased. However, this conversion rate increase and the improved number of SQLs didn't significantly impact the pipeline, as the total pipeline generated actually lagged behind the last quarter.
One interesting observation is the patterns we are seeing in monthly and quarterly performances across 2023 and 2024. In both years, similar trends in MQLs and pipeline have emerged. The decrease in deal sizes in Q2-24 mirrored the trend from 2023, likely leading to more deals being closed. The average contract value in Q2-24 was 15.4% lower than in Q1-24, resulting in higher discount rates. Despite seeing 8.1% more closed-won deals in Q2-24, the total added revenue was almost 26% lower due to the decrease in the average contract value.
In 2023, 29% of the total revenue was generated in Q1 compared to 25.5% in Q2, meaning that Q1 had 14% higher revenue than Q2. In 2024, the added revenue difference between Q1 and Q2 was 26%, nearly twice as much as last year. However, this gap may narrow as new closed deals come in, given the lower pipeline difference between the two quarters compared to last year and the increase in the close rate.
I really enjoyed writing this report - hope it’s beneficial for all of you as well!
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