What do users say about Dreamdata?

Dreamdata allows us to have a complete overview of the entire customer journey. Such a thorough attribution model enables us to allocate our budget properly and create prediction models based on the number of touchpoints and time to revenue for different customer segments. Additionally, we can prove the ROI of all those support activities that enable conversion but rarely occur as last touch points. The free version is very generous allowing you to already discover what companies visited your site and monitor behavior and engagement. The paid version is the perfect cockpit for attribution, ROAS optimization, and ABM. Use it daily as the main marketing and sales dashboard! Review collected by and hosted on G2.com.

There's obviously some initial setup to go through. And the more accurately you go through this phase the more reliable your results are. It's not a problem explicitly connected to the platform. It's just that to get started you need to centralize all your information, data sources, channels, forms, social media forms, and utms. Dreamdata guides you along the way with direct integrations and step-by-step documentation for all other connections. Review collected by and hosted on G2.com.

I have been using Dreamdata for four years now. During that time, we’ve gone through different marketing systems, added new supporting systems, made changes to our paid engine, and even changed our ICP. At every step, we’ve still been able to map everything into Dreamdata and continue to see the full customer journey.

Over a longer period, we also tried moving all the data into our PowerBI setup, but we were never able to replicate anything truly useful there. What I like most about Dreamdata is the ability to consistently connect marketing and sales touches directly to revenue.

In recent months, I’ve used it to really drill down into our marketing channels, and then go even deeper into our paid campaigns and channels, to show the real story from MQL to revenue. Especially after the new AI analytics—which I was lucky to test—we can clearly see our black spots. That has made it much easier for me to go to leadership, show where the gaps are, and push for changes.

I’ve always been data-driven, but Dreamdata makes it much simpler to get to the insights and tell the story. Review collected by and hosted on G2.com.

It can still be difficult when I have so many different angles I can view the same thing from, and I can’t always remember where I saw what. That said, the AI Analytics has helped with that. Review collected by and hosted on G2.com.

I like Dreamdata because it creates a clearer line between marketing activity, the customer journey, pipeline and revenue, giving the team better evidence for where to invest marketing dollars. Review collected by and hosted on G2.com.

I really enjoy using Dreamdata. That said, the reporting can sometimes be confusing because it’s real-time, and there isn’t a way to lock in or “stamp” a specific dataset at a given point in time. Review collected by and hosted on G2.com.

Dreamdata helps me to justify where marketing budget is placed as it is directly tied back to my CRM across MQLs, SQLs, Opps, and Closed Won. The content reports are received well by Product Marketing, the Analytics Hub is phenomenal for consolidated dashboards, and the Reveal section helps me to identify new ICP accounts. Review collected by and hosted on G2.com.

The interface can be tricky, especially when I’m trying to show revenue impact to non-digital marketers. It would help to have clearer explanations of what makes a visitor show up as an Anonymous Visitor in Customer Journeys—for example, whether it’s due to using an incognito tab, being on a new device, or not accepting cookies. Review collected by and hosted on G2.com.

Multi-Touch Attribution: The data-driven, capability to view data on Linear and First touch, Last touch attribution models gives us confidence in understanding which campaigns and channels truly drive the conversions and also gives us better understanding of the performance of our Paid Ad campaign performances. Review collected by and hosted on G2.com.

The pre-built reports lack flexibility meaning it will be good if we have the ability to drill down the layers of the dimensions from the dashboard.

eg. campaigns --> ad group --> keyword / Ads in the same table or dashboard. Review collected by and hosted on G2.com.

I find Dreamdata one of the most comprehensive attribution platforms out there. It brings together our paid-channel, website, CRM, field marketing, and event data in one interface, so I can see what’s performing and make decisions. I really like that Dreamdata has leaned into AI and offers an MCP. Once the data stream is set up, I can use the clean, trusted data in our warehouse to run reports and get information through Claude, the LLM we already use, without having to maintain the setup or pull reports in Dreamdata. It makes things really easy. Dreamdata also makes it simple to connect our data, run the attribution model, and get insights. The initial setup was super simple: I connected the systems through a connector, authenticated, and didn’t need to do any coding. Review collected by and hosted on G2.com.

I don’t have a lot that could be improved. Continuing to add partners and integrations would be valuable. Product-data tools like Amplitude or User Hub could be interesting for people who use them for product analytics Review collected by and hosted on G2.com.

In addition to company journey view that we continue to use especially as part of our QBRs with the CEO, transferring audiences to LinkedIn and Google through the Audience Hub, I also appreciate the recent improvements to the reports. The Dreamdata team continue to be highly engaged with our account, very responsive and willing to run trainings for us and even with the agencies we partner with. Review collected by and hosted on G2.com.

Due to Linkedin’s recent change to how it categorizes campaigns (no more campaign groups), Dreamdata is now showing our LinkedIn Ads data in some reports in a way that is not helpful to us. Rather than seeing our campaign names, we see what Linkedin used to call “campaign groups”, which for us is very ineffective. Especially since this cannot be changed for the company journey view, our most used feature in Dreamdata. Upon feeding back with this information, our account team did add the info we were missing in some reports, but confirmed there is nothing at this point that can be done for the company journey view. I hope this can be looked at again at some point. Review collected by and hosted on G2.com.

we’ve started using Dreamdata more as part of our overall revenue marketing strategy. We still use it for attribution and understanding the buyer journey, but we’re now looking more closely at how marketing activity connects to pipeline and revenue.

It’s especially helpful for seeing how different touchpoints contribute to an opportunity. B2B journeys aren’t usually straightforward, so having a clearer picture of what happens between the first interaction and a closed deal helps us make better decisions for our clients.

We’ve also found more value in using the data for paid media and identifying accounts that are showing stronger buying intent. Overall, we’ve gotten more use out of Dreamdata as our approach has moved beyond just lead generation and more toward revenue. Review collected by and hosted on G2.com.

Segmentation customization for enterprise departments and product lines. Review collected by and hosted on G2.com.

I find that Dreamdata makes attribution simpler and straightforward. Outside of first or last touch, I've found that building a multi touch attribution system comes with some challenges. Dreamdata easily gives us visibility into how different channels, campaigns, and activities influence pipeline using an out of the box multi touch attribution approach. As an example, we can better attribute credit to LinkedIn ads influencing pipeline generation when previously, its influence was understated if we only used a last touch approach. This gives us a more complete picture of marketing's impact and helps inform where we allocate our budget. Review collected by and hosted on G2.com.

Some of the preset dashboards I liked using in the previous version are no longer available. That said, they can be recreated in the Analytics Hub view. Review collected by and hosted on G2.com.

The ease of use. I've used a number of other similar platforms over my career and it's much easier to just jump into DreamData and start building a report. The integrations appear to be robust and the support from the team during onboarding has been excellent. Review collected by and hosted on G2.com.

There are a few slightly odd niggles in the report building flow. For instance, the only way to have multiple graphs on a dashboard is to add them from the report building view and manipulate them subseqeuntly. Review collected by and hosted on G2.com.