I initially planned to write a dedicated report on Bing Ads, prompted by our findings from the 2023, Q1 2024, and Q2 2024 recap reports. If you missed those, here’s a brief summary: our dataset revealed that Bing has maintained the most consistent MQL:SQL conversion rate since 2023. Over the last six quarters, from Q1-2023 to Q2-2024, Bing’s conversion rate fluctuated by less than 5%, regardless of budget changes. This consistency is particularly notable when compared to other platforms, where conversion rates varied significantly—Linkedin saw a 20% change, Google 35%, and Facebook over 180%. Despite Bing’s average budget allocation decreasing by 2.5x in Q1, and then increasing by 2.7x in Q2, these budget shifts did not impact its performance.
On the close-won side, the trends have been similarly impressive. In Q1-2024, Bing was just behind Google; and by Q2-24, it surpassed Google, securing the second-highest close-won rate after Linkedin. This clearly shows that Bing is performing better and better, even though it still receives a minimal portion of the overall budget—around 3-4%, compared to Google’s 10x larger share.
A key observation from Q1 was the significant drop in PPC budget allocation, which then normalized in Q2, with Google and Bing together accounting for approximately 49% of the total paid marketing budget. While it’s premature to draw conclusions about Q3-2024, early indicators suggest we might see further budget fluctuations. Given these dynamics and the volatility in the numbers, I’ve decided to pivot this report towards a comparative analysis of Google and Bing, aiming to gain a clearer understanding of how each platform is performing.
MQL: High-intent demo, pricing page, contact us submissions. Basically, every hand-raiser on the website. Ebook form submissions, lead-gen stuff, webinar registrations were not counted as MQLs.
SQL: Pipeline created; SQO, Opportunity, etc. Every company has different definitions, but we unified this on the backend and used the SQO definition for when the pipeline is actually created.
Pipeline: Total deal value of SQLs
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.
Revenue: Total value of CWs
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. Especially since this report was focused on Google Ads and Bing Ads, our main goal was to uncover the data that’s not the last touch.
Sample Description: 68 B2B SaaS companies
-From $15M ARR to $720M ARR; average ACV from $11K to $125K
-At least 1% budget allocation for Bing, at least 20% budget allocation for Google
-70% NAM, 30% UK
-From July 1st, 2023 to June 30, 2024 (four full quarters)
According to our 2023 Recap, as well as the 2024-Q1 and 2024-Q2 Recap reports, budget allocations for Google and Bing have shown significant volatility. In 2023, Google’s average budget allocation was 47.72%, while Bing’s was just 1.6%. By the last quarter of 2023, Google’s share slightly increased to 48.28%, while Bing saw a substantial jump, ending the year at 3.05%. However, in Q1 of 2024, another major shift occurred—Google’s budget allocation decreased by about 15%, and Bing’s allocation dropped by over 50%. This trend reversed in Q2, with Google’s budget returning to normal levels and Bing’s budget rebounding to its 2023 average. While fluctuating budget allocations across quarters is not uncommon, this pattern aligns with a shift between create-first and capture-first mindsets. In Q1, there was a clear lean towards create-first mindset, while Q2 marked a return to capture-first mindset.
This volatility is also reflected in in-platform metrics. Throughout 2023, Bing led with the highest CTR at 3.1%, followed by Google at 2.2% - while paid social channels lagged, with an average CTR of less than 1%, which is understandable given the differing intents between awareness-driven platforms and those focused on intent. However, we should highlight the fact that Bing’s CTR was nearly 40% higher than Google’s.
My hypothesis is that, given Bing’s modest budget allocation—just above 1.5%—companies may be using Bing for flagship campaigns, such as brand or high-intent keyword campaigns, which likely explains the higher CTR. Over the past quarters, Bing’s CTR has been stable, with less than a 10% variation throughout 2023. In Q1-2024, it dipped slightly to 3.07%, a negligible decrease, before rising to 3.11% in Q2. In contrast, Google’s CTR was more volatile, fluctuating between 1.8% and 2.5% in 2023. It improved to 2.74% in both Q1 and Q2 of 2024.
The Google Ads Benchmarks report highlighted that CPM on Google became nearly 75% more expensive in 2023, only to see a significant drop in Q1-2024. CPC trends were more consistent; over the last 27 months, the average CPC was $5.9. From Q1-2022 to Q4-2023, CPC jumped by 134%, followed by a 30% increase in Q1-2024. Bing’s average CPC was $4.3, making it about 35% cheaper than Google’s. However, Bing’s CPC has been more volatile than Google’s. In 2022, Bing’s CPC averaged $1.89, spiking to $6.51 in the first half of 2023, likely due to the launch of Bing AI as the first AI-integrated browser, which drove increased investment and costs. By the second half of 2023, Bing’s CPC returned to $4.1, and in the first half of 2024, it stabilized at $4.15. Despite its volatility, Bing has consistently maintained lower CPCs than Google.
In summary, Bing has outperformed Google in terms of both CTR and CPC, making it a strong contender in the current digital advertising landscape.
In 2023, Google had the lowest MQL:SQL conversion rate amongst other major paid channels - which was 21.7%, followed closely by Bing at 22.3%. So although CTRs were higher, as explained earlier because of the search intent, this didn’t mean that those clicks were that qualified. In Q1 2024, however, Google saw its conversion rate jump nearly 20% to 25.79%, even as its budget allocation decreased by 15%.
For me, it was a clear indication that companies in our dataset shifted their focus to high-intent keywords during this period, likely pausing campaigns targeting low to mid-intent keywords. This strategic adjustment led to fewer overall clicks but a higher conversion rate. By Q2 2024, though, the conversion rate for Google dropped back to 21.25%, coinciding with an increase in budget allocation. In a way, it feels like companies wanted to get back to the 2023 levels as perhaps they were not enough MQLs - although the conversion rate was higher.
Bing, on the other hand, demonstrated remarkable stability in its conversion rates, mirroring its CTR performance. Despite budget cuts, Bing maintained a consistent conversion rate, averaging 22.3% in 2023, 22.01% in Q1 2024, and holding steady at 22.1% in Q2 2024, even as its budget allocation increased.
Over the last six quarters, Bing’s conversion rate has remained within a narrow band, never deviating from the 22% mark. This stability contrasts with Google’s more volatile performance, though, in the long run, Google’s average MQL:SQL conversion rate of 22.64% slightly outperformed Bing’s 22.07%. While Bing provided a more consistent conversion rate, Google’s overall performance was stronger.
Given Google’s improved conversion rate, the next logical question is whether this translates to better deal sizes. Historically, I would have expected Bing to show more stability in deal sizes as well, but the data tells a different story.
Bing’s average deal size was $15.1K in the first half of 2023, surging to $47.2K in the second half—a statistically significant increase that I verified twice due to its unexpected nature. However, by the first half of 2024, Bing’s average deal size dropped to $30.8K. This represents a quarterly fluctuation of over 150%, with an average deal size of $31.4K over the last six quarters.
In contrast, Google has shown more stability in deal sizes, despite some fluctuations. In the first half of 2023, Google’s average deal size was $30.1K, which then decreased to $20.5K in the second half of 2023, before rebounding to $26.8K in the first half of 2024. Although these shifts are notable, they’re far less extreme than Bing’s. Over the last six quarters, Google’s average deal size was $26.1K, roughly 15% lower than Bing’s.
I always had this hypothesis that enterprise companies would be using Bing more because they predominantly use Microsoft computers at work, and stick with the default Microsoft Edge browser, and don’t switch their search engines to Google. This could explain why we’re seeing higher deal sizes with Bing.
When it comes to costs, I’ll start with understanding the cost per MQLs, SQLs, and closed won deals. However, I won’t be discussing the cost per MQL but rather the changes in cost per MQLs.
What’s the difference? If I were to discuss the former, I’d need to mention an average cost; however, the latter involves analyzing the changes in cost per MQL on a company level in percentages, calculating the weighted average, and merging the data.
For instance, if Company A had 2K MQLs and their cost per MQL increased by 20%, and Company B had 1K MQLs and their cost per MQL increased by 10%, then the average increase would be 17.5%. In simpler terms, I've ensured the data displays what we need to see.
Cost per MQLs decreasing for Google, but not for Bing.
From the beginning of 2023 to the end of the year, the cost per MQL from Google Ads increased by 16% on average.
However, in the first quarter of 2024, the average cost per MQL for Google Ads decreased by 18%, and then increased by 15% in the second quarter of 2024. This fluctuation resulted in a 3% cheaper average cost per MQL in the first half of 2024 compared to the 2023 average.
On the other hand, Bing experienced a 4.6% increase in the cost per MQL during the first half of 2024; while almost no fluctuation happened between quarters. Although this 4.6% increase in the average cost per MQL might seem modest for Bing, it should be considered important since we’re observing that Google’s costs decreased during the same period.
On the Google side, the cost per SQL ended up being 12% more expensive in 2023 compared to 2022.
With the decrease in cost per MQLs and the increase in conversion rates in the first quarter of 2024, we monitored that the average cost per SQL was 31% lower than the 2023 average. But in the second quarter of 2024, there was another decrease in the MQL:SQL conversion rates in Google; this meant that cost per SQL got higher; and the first half of 2024 had just 6% lower cost per SQL than the 2023 average. It’s really fascinating to see how much these metrics fluctuate quarter by quarter.
Similar to the Google side, we’re seeing an increase in the cost per SQL side on Bing—although the MQL:SQL conversion rate stayed relatively similar, the small increase in CPCs sort of impacted Bing, and the cost per SQL increased by 1.21%.
Now, let’s look at the average pipeline ROI on these platforms - so how much pipeline is being generated for every $1 spent on Google and Bing.
In 2023, the average pipeline ROI of Google was 8.34; and it increased to 8.44 in the first half of 2024.
Bing, on the other hand, had an average of 7.26 pipeline ROI in 2023; however, in the second half of 2023, it jumped to 8.4, and throughout 2024, this ROI increased every further was 9.33—meaning that B2B SaaS companies are generating 10.5% more pipeline through Bing than they generate through Google.
What does the change in revenue ROI look like? In other words, what is the actual dollar added for each dollar spent on Google and Bing?
The average revenue ROI of Google was 1.13 in 2022, it increased to 1.36 in 2023, and further to 1.4 in the first half of 2024. (However, this revenue ROI isn’t significant enough to justify the budget allocated to Google Ads.)
When it comes to Bing, the numbers show some volatility, similar to what we observed with deal sizes - but not necessarily in a bad way. The ROI for Bing was 1.22 in the first half of 2023, which then increased to 2.14 in the second half of the year.
The average revenue ROI for the entire year of 2023 was 1.73. By the first half of 2024, Bing's ROI had risen further to 2.53. This means that Bing generated 80% more revenue per dollar spent compared to Google—a truly amazing number.
While Bing has demonstrated strong performance across various metrics, including CTR, deal sizes, and pipeline ROI, it’s crucial to remember that search platforms are ultimately limited by search volume. The consistency in Bing’s metrics, despite fluctuations in budget allocation, highlights its potential as a valuable channel, especially for high-intent campaigns. However, the key takeaway here is not to drastically shift your budget from Google to Bing. The success of any search campaign hinges on the user base, and Google’s dominance in search volume is unmatched, underscored by their substantial investment to remain the default search engine on major platforms; hence even if you decide to allocate your entire budget to Bing, it might not work.
Nevertheless, Bing’s lower costs and stable performance suggest that it’s worth exploring if you haven’t already, but this should be done strategically. Allocating a small portion of your budget—around 1.5-2% as seen with many companies in this dataset can provide a foothold on Bing without requiring significant time commitment. Another thing is that you can easily sync your existing Google Ads campaigns to Bing; therefore you don’t need to have a huge time commitment; this makes it considerably a low-risk, potentially high-reward option. This report should serve as a guide to consider Bing as a complementary channel rather than a replacement, leveraging its strengths while acknowledging its limitations in reach compared to Google.
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