Dreamdata Benchmarks: Measuring G2 Intent Data impact on B2B buying journeys
In 2022, Dreamdata found that customer journeys where a user review site was the first touch were 63% shorter on average than those initiated from another source.
With an increasing number of businesses now integrating their G2 Buyer Intent signal data with Dreamdata, we’ve decided to take a closer look at how G2 signals influence B2B customer journeys.
And the findings are fascinating.
The bottom line is: G2 signals have a considerable impact on the journey of a buyer and the average customer deal size.
Notably, of the mutual customers integrating their G2 data with Dreamdata, the value of deals containing a G2 intent signal are 2x larger than the average deal value.
Our study’s findings offer valuable learnings for B2B software sellers, helping them optimize their go-to-market in the age of signal-based selling, so we hope you enjoy the report.
The Dreamdata G2 Intent Data benchmarks:
How many closed won deals are influenced by G2 signals?
Is there any difference in the size of the deals between those with a G2 signal and those without?
How many G2 intent touches are there on average, and how long does it take to close a deal with G2 signals in the journey?
Which type of G2 Buyer Intent signal has the biggest influence on closed won deals?
When do G2 Buyer Intent signals occur in the buying journey?
What are G2 Buyer Intent signals?
Before looking at the data, let’s ensure we have a clear understanding of G2 Intent data and what the signals represent.
G2 Buyer Intent captures enriched data about buyers researching your product on G2. Buyer Intent signals are triggered by various actions: interacting with your Product Profile page, comparing your product to a competitor, or viewing alternatives to a product in a shared G2 product category. Signals are account-level data, and represent meaningful buyer behaviors that reveal when a company shows an interest in purchasing a software product or service.
Types of G2 Buyer Intent Signals
Each buyer intent signal represents a unique buyer interaction on G2. Here are the different signals G2 offers:
Category: A buyer viewed a G2 category page that includes your product. G2 categorizes products based on a number of factors, including similar functionality and use cases.
Alternatives: A buyer viewed a G2 alternatives page for your product or looked for alternatives to a competitor’s product that is listed in the same category as your product. This activity can indicate that the buyer is looking at alternative products in your category as part of their buying process. It can also mean churn risk for existing customers - especially if these customers are close to their renewal process.
Product Profile: A prospective buyer viewed your G2 Product Profile. This activity indicates that the buyer is specifically researching your product.
Pricing: A buyer viewed the pricing page of your G2 Profile, it indicates they are evaluating your product in the context of their budget.
Compare: A buyer viewed a G2 comparison page that included your product. This activity indicates the buyer is directly comparing your product to a competitor’s product.
Each signal sent to Dreamdata contains the Signal URL (the type of signal), company name, company website, location, and session time.
G2 Buyer Intent Data + Dreamdata
Dreamdata allows customers to integrate their G2 Buyer Intent signal data for products listed on G2 directly into the Dreamdata platform.
This integration brings G2 data together with other B2B go-to-market data sources in the customer’s tech stack, allowing Dreamdata’s account-based, multi-touch attribution modeling to reveal which touchpoints drive pipeline and revenue (and which don’t!).
A quick word about multi-touch attribution
In B2B, decisions often involve multiple touches, by multiple stakeholders, across multiple channels. G2, as a high-intent review platform, can influence various stages of the buying process, so any reliable analysis of its impact on the customer journey needs to encompass all touches, i.e. it needs multi-touch attribution.
Here is what a standard B2B customer journey looks like.
Multi-touch attribution ensures that every interaction, from first discovery to final purchase, is accounted for.
However, single-touch models miss the complexity of buyer journeys by focusing on one interaction, while multi-touch attribution maps all touchpoints to accurately assess the impact of G2 intent signals on revenue and pipeline.
That said, single-touch models are still useful in some analyses. For instance, last-touch attribution can be useful for determining the impact a particular channel has on a conversion event.
“Single-touch models oversimplify complex buyer journeys by only capturing one interaction, while multi-touch attribution allows us to map out the entire sequence of touchpoints and properly assign value to each. This level of granularity is essential for accurately measuring the true impact of G2 intent signals on revenue and pipeline.”
Mikkel Settnes, PhD, VP Data, Dreamdata
For our benchmark analysis, we’ve applied data-driven attribution modelling to examine the impact that every G2 signal has on average B2B buying journeys. Read about the data we extracted and our methodology at the end of this report.
An Analysis of G2 Buyer Intent Signals
Our analysis reveals that G2 Buyer Intent signals have a substantial impact on the average B2B customer journey. These are the five main insights we found:
1. 12% of closed won deals are influenced by G2 signals.
12%
of all deals
influenced by G2 signals
Of the 1000s of deals analysed, the data found that 12% of closed won deals have a G2 signal appear in the organization’s buyer journey before closing date.
This suggests that G2 signals can serve as a meaningful indicator of buyer interest or readiness. With G2 signals showing up in deals of larger size (see next point), this data reinforces the importance of tracking and responding to these signals, as they can guide sales and marketing teams in prioritizing high-potential leads.
2. The value of deals with a G2 signal are 2x larger than the average deal size.
When we compared the average value of deals with G2 signals to those without, we found that deals with G2 signals were two times larger. This suggests that companies making larger investments spend more time researching and evaluating products, and rely on G2 to do this.
For sellers, this finding is especially insightful. It indicates that prospects sending G2 signals are likely more valuable, making it worthwhile to allocate extra resources to action these signals over others.
3. There are an average of 3 G2 touches in successful buying journeys.
3x G2
signals on
average B2B journey
The data revealed that deals influenced by a G2 signal typically have three G2 touches throughout the buying cycle. This underscores the importance and trust that buyers place on G2’s insights when evaluating their shortlist of solutions.
That is, buyers using G2 are faithful and recognize its trusted source of information, and therefore use it repeatedly in their decision-making process. It also underlines the need for multi-touch analysis, as discussed above.
For sellers, this indicates that multiple G2 signals are strong indicators of buying intent, suggesting that such deals should receive extra attention and resources. It also emphasizes the importance of keeping G2 profiles, pricing pages and performance in reports (categories) up to date - which includes keeping a constant stream of reviews.
4. G2 Comparison signals have 5.7x more influence than Category signals
The data showed that Comparison signals influenced almost 15% of closed deals per session, which represents over 3x more than Product (Profile) signals, and 5x more than Category signals.
This confirms that making a direct comparison between two products indicates higher buying intent than intent signals on a category page or visiting a profile page. This is a boon for sellers seeking to prioritize their sales efforts; greater attention and higher-touch efforts should be paid to prospects making a comparison between their product and a competitor’s.
5. Time from G2 Intent signal to Closed Won
Comparison signals had the shortest time from the session to the deal being closed, taking an average of 63 days. From a Product Profile view to closed-won takes 147 days, and from a Category signal, you can expect to wait 174 days before closing a deal.
Apart from re-emphasising the strength of the signal, as with the previous data insight above, this tells us when these signals might be taking place in the buying journey.
The intuitive notion combined with the type of content on each of these pages where intent shows up, tells us that companies looking for a solution will start at the category level to see what solutions are available before giving those solutions a closer look, then pitting the strongest solutions against each other.
Category signals can indicate that buyers are in-market early, which should trigger a nurture campaign to mature their awareness through the funnel, and encourage deeper product research and comparisons on G2. This might trigger campaigns on other channels, such as LinkedIn Ads, to nurture the lead towards these lower-funnel actions.
All of this can be easily set up with G2’s LinkedIn integration and Dreamdata (more below).
Customer Spotlight
Action your G2 Signals with Dreamdata
Dreamdata doesn’t just connect G2 Buyer Intent signal data to the rest of your go-to-market ecosystem. With Dreamdata’s reports and additional integrations to ad platforms, you’re able to analyze and action this data to initiate or optimize your signal-based go-to-market strategy.
Teams that integrate G2 Buyer Intent data with Dreamdata can:
Build a holistic attribution model: Dreamdata will collate the first, second, and third-party data sources you invest in so teams can have a comprehensive view of all buyer journey touchpoints in a single place.
Measure the strength of G2 intent signals through attribution: Dreamdata’s account-based data models attribute intent signals to their specific impact on your pipeline and revenue. This enables you to assess what signals lead to the most valuable outcomes, helping you optimize and prioritize your efforts.
Identify leads and opportunities early on: With Dreamdata, you can filter by your ICP criteria to identify the prospects sending signals early in their buying journey. Which is now conveniently categorized with our ‘Signal type’ filter on Reveal.
Using these early-stage signals will help teams miss fewer opportunities, streamline and improve the sales process.
Automate sales outreach and marketing retargeting: Instantly build audiences of intent accounts and automate retargeting process through Dreamdata’s Audience Hub feature. The click-and-point audience builder builds an audience of all those companies meeting your ideal customer profile that send a G2 signal, and directly sync the audience to your LinkedIn Ads campaign manager.
Optimize your prospect and customer engagements: Centralizing your data in Dreamdata offers a comprehensive map of every single B2B customer journey. This enables you to learn exactly when signals are being sent as well as easily compare against other sources and channels so you can optimize resources and budget.
Get more insights with G2 Buyer Intent signals
In conclusion, our study highlights the significant presence and impact G2 Buyer Intent signals have throughout B2B customer journeys.
The integration of G2 signals with Dreamdata provides valuable multi-touch attribution insights into how these signals influence deal types, deal sizes, and the speed of the buying process.
Our study found that:
12% of closed won deals are influenced by G2 signals
An average of three G2 signals per closed deal.
Deals influenced by G2 signals are twice as valuable as those without.
Compare signals in particular, have a markedly high impact, influencing nearly 15% of deals and shortening the journey to an average of 63 days.
These findings underscore the importance for go-to-market teams, including marketers and sellers, to pay close attention to G2 signals and optimize their go-to-market strategies accordingly.
By leveraging G2’s unique and exclusive data with Dreamdata’s robust measurement capabilities, businesses can make informed strategic decisions, capitalize on valuable opportunities early in their buying journey, and work from a centralized source of truth for go-to-market.
This approach ensures a streamlined sales process, maximized opportunities, and ultimately, a more effective signal-based strategy.
About the data
The data used to compile these insights is anonymised aggregated data* taken from all Dreamdata customers who have integrated G2 Buyer Intent Signals with Dreamdata (and who have not opted out of the Benchmarks).
To make the insights as accurate and reliable as possible, our methodology has been as follows:
Normalizing the data to allow a fair comparison among accounts with different advertising spend.
Only including accounts with a minimum spend to avoid non-representative data.
Using median and quartiles to remove the influence of outliers that might skew the metrics.
Aligning definitions for the funnel stages through a setting that everyone can set up inside our product.
* At Dreamdata we take data security and privacy very seriously. Dreamdata has processed only non-PII data for this study. The data insights are aggregated, and a minimum number of data points (accounts) has been introduced for every benchmark meaning it is not possible to identify individual companies. Only data from companies that have agreed to let us use data in benchmarks are included.
