A few years ago, I was put in charge of running an event for a small business. Our small team launched a big campaign, pouring resources into ads, emails, and social media. But when the results came in, we had a problem—while conversions were up, we had no idea which channel was actually working.
Some argued it was the ads, others pointed to email nurtures, and a few insisted it was organic search. Without a proper attribution system, we were left guessing, so we began looking for the best attribution software.
After deploying these tools, we were able to allocate resources more effectively and focus on what truly drives results. I moved beyond simple tracking and gained deeper insights into how each touchpoint contributes to conversions.
If you’re struggling to connect the dots between your marketing efforts and revenue, keep reading. I’ve tested the top 10 marketing attribution tools and am sharing key takeaways from my research to help you choose the right strategy.
10 best attribution software: My picks for 2025
HubSpot Marketing Hub for its comprehensive attribution reporting across all marketing channels ($45/mo)
ActiveCampaign for advanced email marketing attribution and automation tracking ($145/mo)
CallRail for connecting offline phone call conversions to online marketing touchpoints ($45/mo)
WhatConverts for multi-channel attribution, tracking leads and conversions from various sources ($30/mo)
Triple Whale for e-commerce attribution, tracking customer journeys and ROI across digital channels ($649/mo)
Invoca for AI-driven call tracking and attribution, linking phone call data to digital marketing campaigns (available on request)
impact.com for managing and tracking affiliate, influencer, and partner-driven marketing efforts (available on request)
Dreamdata for B2B marketing attribution, integrating CRM and marketing tools for full customer journey mapping ($999/mo)
Flowcode for tracking and analyzing customer engagement from QR code interactions ($60/mo)
Demandbase One for account-based marketing (ABM) attribution, offering insights into targeted account engagements (available on request)
*These marketing attribution tools are top-rated in their category, according to G2 Grid Reports. I’ve also added their monthly pricing to make comparisons easier for you.
My top 10 best attribution software recommendations for 2025
Best marketing attribution software helps businesses track and measure the impact of marketing efforts across channels. During testing, I saw how these tools streamline data collection and offer insights into what drives conversions. Features like multi-touch attribution and real-time tracking optimize strategies and resource allocation, providing a clearer understanding of campaign performance.
How did I find and evaluate the best attribution software?
First, I explored G2 Grid Reports to discover which marketing attribution tools professionals trust the most. Then, I tested them myself to evaluate how well they tracked and measured the effectiveness of various channels. In cases where I couldn’t directly test a tool, I connected with marketing professionals who had hands-on experience and cross-referenced their feedback with verified G2 reviews.
The screenshots in this article are from a combination of my testing and vendor-provided materials on G2. To ensure a comprehensive analysis, I used AI to analyze thousands of G2 user reviews, extracting key insights and common feedback. The goal? Identify the best marketing attribution software that provides accurate, actionable insights without overwhelming teams.
What I look for in attribution software
When evaluating the best attribution software, I focus on several key features to determine its effectiveness:
Cross-channel and cross-device tracking: I need software with robust tracking mechanisms that can capture user interactions across various touchpoints, including devices like desktop, mobile, and tablet, as well as marketing channels such as paid search, organic search, email campaigns, social media platforms, and display advertising. The key technical requirement is the use of persistent identifiers—such as cookies, device IDs, or user authentication tokens—to track users across multiple devices and sessions. I also expect the software to support session stitching, which ensures a seamless view of the customer journey even when users switch devices or channels. This unified tracking provides insights into how different touchpoints and channels contribute to conversions.
Multi-touch attribution models: The software must support a variety of attribution models, including first-touch, last-touch, linear, time decay, and algorithmic attribution. I also look for the ability to define and customize models that align with specific business goals and customer behavior. The software should leverage advanced statistical techniques like regression analysis or machine learning models to calculate the weight assigned to each touchpoint and reflect its true contribution to the conversion path. These models help capture the full impact of various marketing activities across the entire customer lifecycle.
Data integration: Seamless integration with other marketing tools and platforms is essential. The software should integrate effortlessly with CRM systems, marketing automation platforms, web analytics tools, and advertising networks through standardized APIs or pre-built connectors. I require the ability to work with different data formats, such as JSON or CSV, and support for extract, transform, load (ETL) processes to ensure data is normalized and ready for analysis. Integration should also enable smooth data flow across systems, eliminating manual data handling and improving overall efficiency.
Customer journey mapping: I need the software to help visualize and map the customer journey from the first interaction to the conversion. It should allow me to build multi-stage funnels and perform path analysis to see how customers engage with different touchpoints throughout their journey. I also look for the ability to segment users based on behavioral characteristics or lifecycle stages—such as first-time visitors, repeat customers, or cart abandoners. Interactive visualizations like heatmaps, flow diagrams, and cohort analysis are crucial for identifying areas where users drop off and for optimizing the conversion path.
Data privacy and compliance features: Given the importance of data privacy regulations like GDPR and CCPA, the software must provide robust features for compliance. I need it to anonymize sensitive customer data, such as personal identifiers, to ensure regulatory adherence. The software should include consent management functionality, allowing customers to opt in or out of tracking, and provide audit logs that track consent events. These tools help maintain transparency and ensure that the company complies with privacy laws, which is critical in managing customer trust.
Advanced attribution algorithms: To improve attribution accuracy, I look for software that incorporates machine learning algorithms to analyze large datasets of customer behavior. These algorithms can identify patterns and predict which touchpoints are most likely to lead to conversions, enhancing the precision of attribution models. Additionally, predictive analytics helps forecast which channels or campaigns are expected to yield the highest returns, enabling me to optimize future marketing strategies. I also need the ability to continuously refine attribution models as new data is collected, ensuring that the software adapts to changing customer behavior and marketing trends.
Data visualization: The software should support seamless integration with data visualization and business intelligence (BI) tools like Tableau, Power BI, or Looker. This enables me to export attribution data and create more advanced visualizations, predictive models, and custom reports. I also require interactive dashboards that provide a comprehensive view of marketing performance by combining attribution insights with other business metrics, making it easier to make data-driven decisions and optimize campaigns.
The list below contains genuine user reviews from our best attribution software category page. To qualify for inclusion in the category, a product must:
Track interactions across multiple marketing and communication channels.
Use attribution models like single-touch, fractional, and algorithmic attribution.
Provide dashboards and visualizations based on historical data and KPIs.
Integrate with software used by sales, marketing, or PR departments.
This data has been pulled from G2 in 2025. Some reviews have been edited for clarity.
1. HubSpot Marketing Hub
I've used HubSpot Marketing Hubfor over two years, and it's proven to be a powerful, all-in-one marketing solution. Strategizing, creating, implementing, and analyzing content performance in one place has drastically improved our team's efficiency.
By having visual attribution to metrics, it's easy to connect the dots between the marketing activities we launch and the results they generate. This has allowed me to give real meaning to our content strategy and ensure we're always on track with our goals.
Click tracking and automatic UTM parameter creation when sending marketing emails further enhanced our marketing campaigns' measurability and accuracy. It’s great knowing that the platform takes care of these details automatically, freeing me up to focus on other parts of the campaign.
Another feature I’ve greatly appreciated is the real-time visibility into the sales pipeline. With this, I could easily see where leads stood in the funnel, which helped me prioritize efforts and make smarter decisions.
Plus, the HubSpot Academy is an excellent resource that helped me enhance my expertise. It provides valuable lessons and certifications that deepen my understanding of the platform.
While the HubSpot Marketing Hub is generally excellent, there are a few areas where I felt it could improve. For instance, when it comes to marketing attribution reporting, I found myself wishing for more customization options. I needed more flexibility with percentages and additional ways to view and analyze the data, which would allow for deeper insights into campaign performance.
Another area that could use refinement is the default contacts view. I would have preferred to see recently engaged customers at the top of the list, even if they were not new. This adjustment would have made it much easier to focus on the most relevant contacts and engage with them more effectively.
In addition, I noticed that HubSpot Marketing Hub lacked advanced AI functionalities in analytics and database cleansing. These processes are tedious, especially when dealing with a large database, and AI-based solutions would have added immense value by streamlining them and improving efficiency.
What I like about HubSpot Marketing Hub:
HubSpot Marketing Hub has greatly improved our team's efficiency by consolidating content strategy, creation, implementation, and performance analysis in one platform.
The platform’s visual attribution to metrics provides a clear insight into how marketing activities drive results. This visibility has helped me connect our content efforts directly to outcomes.
What G2 users like about HubSpot Marketing Hub:
"I've been using HubSpot Marketing Hub daily, and it's become my go-to marketing command center. What stands out is how it packs powerful features into a system that's easy to use—everything from email campaigns to landing pages works seamlessly. The best part is how quickly you can set it up, and it integrates smoothly with almost any other tool. Despite its many capabilities, I’ve never needed to contact support because it's so intuitive. For anyone looking for a strong marketing platform without technical headaches, HubSpot Marketing Hub feels like the "easy button" for digital marketing. I’ve even discovered features I didn’t realize I needed because they’re so accessible—it’s like a Swiss Army knife where every tool is actually useful and easy to find."
One area where HubSpot Marketing Hub could improve is in marketing attribution reporting, where I found the customization options lacking. More flexibility with percentages and additional ways to analyze the data would provide deeper insights.
The default contacts view could also use refinement. It does not prioritize recently engaged customers, even if they aren’t new. Having this feature would allow me to focus on the most relevant contacts.
What G2 users dislike about HubSpot Marketing Hub:
"HubSpot Marketing Hub offers robust reporting features, but customization could be improved. There are limitations when creating highly specific or tailored reports for certain metrics or key performance indicators (KPIs). Expanding the flexibility of report customization would be a valuable enhancement."
I’ve come to appreciate ActiveCampaign'srobust features that streamline email marketing and customer journeys.
From the moment I started using it, I noticed how intuitive and user-friendly the interface is. Navigating the platform was seamless, allowing me to dive into creating campaigns and automation workflows without feeling overwhelmed.
One of the standout features for me was behavioral tracking, which provided deep insights into how contacts interacted with my emails, website, and other touchpoints. This data-driven approach significantly improved my marketing effectiveness, helping me tailor campaigns to customer behavior.
Not only can youset up email campaigns effortlessly, but analyzing their performance is just as easy. The conversion attribution reports clearly showed how email clicks translated into conversions, giving me the confidence to invest more in email marketing strategy.
Another feature that impressed me was ActiveCampaign University. The wealth of educational content helped me maximize the platform’s potential, while community forums provided valuable peer-to-peer support. Additionally, the designated expert sessions were an excellent resource—I could speak directly with a specialist to get in-depth guidance and troubleshoot any issues.
However, there were some areas where I felt ActiveCampaign could improve. For example, I wished there was a way to track how many purchases or "add to cart" occurrences were directly tied to our email campaigns. It would have been helpful to see which specific customers made purchases or added items to their carts.
Additionally, while the reporting tools are generally valuable, I found them to be a bit slow and sometimes difficult to set up. It wasn’t always clear how to structure reports to get the most relevant data, and the delays in processing could be frustrating when I was eager to get quick insights.
Lastly, I would have liked to see more attribution related to organic searches and non-paid advertising. While ActiveCampaign excels with email attribution, there seems to be less focus on tracking the performance of organic traffic and non-paid campaigns. Expanding this would have allowed for a more comprehensive understanding of how all marketing channels contribute to conversions.
What I like about ActiveCampaign:
Behavioral tracking provided deep insights into how contacts interacted with my emails, website, and other touchpoints. This data-driven approach significantly improved my marketing effectiveness.
ActiveCampaign University offered a wealth of educational content that helped me maximize the platform’s potential. The expert sessions and community forums provided direct access to specialists and peers, making troubleshooting and learning much easier.
What G2 users like about ActiveCampaign:
"I love how straightforward the workflows are. I haven't yet encountered an automation that I couldn't create using ActiveCampaign. Over the past five years, I've migrated myself and four other clients to ActiveCampaign, with contact lists ranging from a few hundred to 50,000. They’ve always been personable and helpful when issues or questions arise. I’ve especially appreciated being able to reach a real person when facing technical problems, and I love the recent updates that have made tagging and segments more user-friendly. These improvements have helped my clients understand the platform better. I’ve built extensive sales, onboarding, and client CRMs using the deals feature, and my client loved it. Her entire team used it, and it was seamless to integrate into their rapidly growing coaching business."
I found the data attribution for marketing emails to be insufficient. It didn’t provide clear insights into purchases or "add to cart" actions tied to email campaigns. Being able to track specific customer actions would have offered a better understanding of how our emails contributed to actual conversions.
While the reporting tools are generally useful, I found them to be slow and difficult to set up at times. The delays in processing and the unclear structure made it frustrating when I needed quick and relevant data insights.
What G2 users dislike about ActiveCampaign:
"The reporting capabilities are limited, with a poorly designed and slow interface. Reports are often inaccurate, and the weak attribution model makes it difficult to trust the numbers, which could be a dealbreaker for companies with an established marketing function. Additionally, functionality for channels outside of email feels disjointed—SMS is hard to configure, and the transactional email feature requires signing up for a separate platform and integrating it like a third-party tool."
CallRailis a call-tracking tool. I’ve found it to be incredibly effective in tracking marketing efforts, and one of the features I appreciate most is how it allows me to identify which marketing efforts generate the most calls. Instead of relying on assumptions or incomplete customer feedback, I get concrete data showing which ads, keywords, or sources drive phone leads.
Proving return on investment can be a significant challenge for businesses that depend on phone calls to convert leads. CallRail simplifies this process by directly linking phone calls to specific campaigns, keywords, or ads. This feature allows me to see exactly how many leads are coming from each source.
Another powerful feature of CallRail is its ability to assign individual tracking numbers to different campaigns, whether they are print, radio, TV, or online ads. This allows me to track attribution and ROI across various marketing channels with precision.
What’s even better is that CallRail measures not only the quantity but also the quality of calls. This added layer of insight helps me make smarter decisions, focusing on campaigns that deliver the most valuable leads and ensuring better outcomes for clients.
However, as much as I value CallRail's capabilities, I encountered a few challenges during my testing. Setting up the system can be quite time-consuming. For someone who isn’t particularly tech-savvy, configuring tracking numbers, routing, and other features could be frustrating.
Another issue I encountered was missing data. While CallRail provides powerful insights, there were occasions when some calls weren’t recorded or logged properly. This is a concern, as any missing data can distort the conclusions drawn from analyzing marketing effectiveness. Even a small percentage of untracked calls can lead to inaccurate trends or misleading assumptions, making it difficult to get a full picture of campaign performance.
Finally, while the reporting tools in CallRail are useful, they can be somewhat limited. I noticed that some of the API connections to third-party reporting platforms didn’t always work as smoothly as I would have liked. This can be frustrating when trying to integrate data into other systems for more comprehensive analysis.
What I like about CallRail:
CallRail provides clear and concrete data on which marketing efforts generate the most calls, eliminating assumptions and incomplete customer feedback. By linking specific ads, keywords, or sources to phone leads, I can confidently assess the performance of various marketing campaigns.
The ability to assign individual tracking numbers to various campaigns, whether print, radio, TV, or online ads, helps me track attribution and ROI with precision.
What G2 users like about CallRail:
"CallRail has been extremely useful in providing channel attribution insights, making it easy to show clients which channels are driving not just more phone calls but also the highest-quality calls."
- CallRail Review, Verified User in Marketing and Advertising
What I dislike about CallRail:
Setting up CallRail can be time-consuming and challenging for those who aren’t particularly tech-savvy. Configuring tracking numbers and routing can become frustrating if you're unfamiliar with the platform's technical aspects.
I experienced issues with missing data, where some calls weren’t recorded or logged properly. This can distort the conclusions drawn from campaign analysis, as even small amounts of untracked calls can lead to inaccurate trends and misleading assumptions.
What G2 users dislike about CallRail:
"CallRail lacks the ability to track attribution for overlay chat widgets, which are becoming mainstream communication tools for websites."
Having tested WhatConverts, a lead tracking and reporting software, I quickly found it to be an excellent tool for tracking and attributing conversions across multiple channels.
The multichannel attribution allows me to track multiple customer interactions that lead to a conversion, making it easier to understand the full customer journey. Whether the lead comes from search engine optimization (SEO), Google Business Profile (GBP), or paid ads, WhatConverts does an impressive job of providing a clear picture of the contributing factors behind conversions.
Another major benefit of WhatConverts is its ability to integrate with popular ad platforms, simplifying data collection, distribution, and analysis. This feature is key for streamlining marketing operations, allowing me to identify and eliminate wasted ad spend. With its clear attribution models, I could easily see which ads were performing well and which weren’t. This allowed me to reallocate my budget to top-performing campaigns, maximizing ROI and improving overall marketing efficiency.
Keyword attribution is also a great feature, especially when optimizing accounts. It lets me see which keywords are driving conversions, which helps with fine-tuning PPC campaigns and improving overall targeting strategies. This aspect of WhatConverts has proven to be essential for identifying high-performing keywords and ensuring that marketing efforts are aligned with business goals.
However, there are a few areas where I believe WhatConverts could improve. First, I would love to see more integrations, particularly with CRMs. The data collected by WhatConverts is highly valuable, and being able to integrate it directly into various CRMs without needing to rely on external tools would streamline the process even more.
Reporting customization could be a little more flexible. While WhatConverts does provide valuable insights out of the box, users might want more options for customizing reports based on their specific needs. Exploring the platform’s available customization options is essential for getting the most out of its reporting features, but a broader range of customization would definitely enhance the user experience.
I did notice that some users might face a learning curve when first setting up the system. The initial setup process can be somewhat complex and time-consuming, which may deter new users.
What I like about WhatConverts:
WhatConverts' multichannel attribution helps me track multiple touchpoints in the customer journey, providing a clear picture of the factors behind conversions. This feature is vital in understanding how different channels contribute to improving decision-making.
The ability to integrate with popular ad platforms streamlines data collection and analysis. It allows me to easily identify wasted ad spend and optimize campaigns for better ROI and marketing efficiency.
What G2 users like about WhatConverts:
"We love the detailed tracking and insights into the user journey. It helps us better understand the user experience on our site and identify which pages have higher conversion rates. The system is simple to use and easy to navigate. The team has been very responsive, and the implementation and integration have been much easier compared to most other tracking efforts."
I would love to see more integrations, particularly with CRMs. Direct integration would eliminate the need for external tools, making data management smoother and more efficient.
Reporting customization could be more flexible. While the platform provides valuable insights, the ability to tailor reports to specific needs would enhance the user experience, giving more control over how data is presented.
What G2 users dislike about WhatConverts:
"I like most of it! It’s super helpful! However, the first-click attribution default is different from both the Ads platforms and GA4, which creates a challenge. I’ve also heard from my web company that setting up new forms is a heavy lift, though I assume support might help alleviate that. The definitions of duplicates vs. repeats, as well as setting the attribution window for “repeat,” could also be clearer. What I’ve been struggling with is building a central lead database to avoid having to go to WhatConverts and our lead management system to capture and respond to leads. I can’t figure out how to consolidate offline leads and paid calls from other call-tracking platforms into WhatConverts or elsewhere, especially with all the different attribution models in play."
Using Triple Whale has significantly improved how I manage and analyze data across marketing channels. One of the key advantages of this platform is that it aggregates all data sources in one place. This centralization has allowed me to make quicker, more informed decisions.
I also appreciated how the platform tracked expenses, cost of goods sold, and marketing spending, giving me a more comprehensive view of profitability beyond the traditional profit and loss statement.
True attribution to ad spend is another critical benefit I’ve experienced. With Triple Whale, I finally had clarity on where marketing dollars were most effective. I particularly appreciated the ability to see new customer cost per acquisition (CPA) and return on ad spend (ROAS) metrics, which are invaluable for understanding the effectiveness of my campaigns. This level of insight was crucial for our growing business, as it provided a real-time understanding of how well they are scaling and where adjustments needed to be made.
One of the things I found most valuable is how we’ve been able to compare Triple Whale’s data with what we see in Facebook and Google Analytics. These platforms each have their own attribution windows, which can lead to discrepancies in data reporting. By using Triple Whale as an additional source, I was able to cross-check and get a clearer view of my campaign performance.
Another feature that stands out is the platform’s ability to track individual consumer journeys across multiple marketing channels. I could clearly see the path each customer took to purchase a product, which helped me better understand which touchpoints were most effective in driving conversions.
However, there are a few areas where Triple Whale could still improve. Aggregating all the data can sometimes slow the system down, especially when dealing with large datasets. While the team is actively working on improving this, it’s something to keep in mind when working with complex data sets.
I also found that cohort tracking could be clearer. Currently, it’s challenging to analyze how specific groups of customers performed over time, especially when it comes to middle-funnel conversions. I couldn’t get a clear view of customers who clicked through, became a lead, and eventually made a purchase, which left a gap in understanding the full conversion journey.
Finally, Triple Whale is currently only available through Shopify, which limits its use to businesses that run on other CMS platforms like WooCommerce, Drupal, or Magento. If Triple Whale expanded to other platforms, it would be a much more versatile tool for a wider range of e-commerce businesses.
What I like about Triple Whale:
The platform provides a comprehensive view of profitability by tracking expenses, cost of goods sold, and marketing spend. This helped me gain a deeper understanding of our financial health beyond the traditional profit and loss statement.
Triple Whale’s attribution tracking gave me clarity on where marketing dollars were most effective. The ability to view metrics like customer acquisition cost (CPA) and return on ad spend (ROAS) was crucial in assessing campaign effectiveness.
What G2 users like about Triple Whale:
"The great news is that Triple Whale offers a ton of features that, in theory, would be very helpful across marketing, finance, and operations in an organization like ours (DTC eCommerce). Triple Whale provides solutions for multi-touch attribution (MTA) and media measurement, financial forecasting, creative learning and optimization, and pseudo-CRM functions like lifetime value (LTV), cohort analysis, and sales cycle insights. I have no doubt that organizations that fully commit to adopting and truly learning how to use Triple Whale will find the tool incredibly useful."
Aggregating all the data can sometimes slow the system down, especially with large datasets. Although the team is working to improve this, it can still be an issue when working with complex data.
Cohort tracking could be clearer, as it was challenging to analyze specific customer groups over time. The lack of visibility into middle-funnel conversions created a gap in understanding the full conversion journey.
What G2 users dislike about Triple Whale:
"I'm unable to view different sublevels of the campaign, ad set, and ad directly. I can only look at the campaign level, and if I want to see the ad set level, I have to click through. I'm also not a fan of the export feature. The revenue numbers are often inaccurate, especially with view-through attribution. If that issue can be fixed moving forward, it would save my team a lot of time. Additionally, the load time for higher-spending accounts could be improved."
Having tested Invoca, a robust conversion analytics software, I was impressed with its real-time data and insights, making it a powerful tool for quick decision-making.
One of the most valuable features was real-time multi-site and multi-channel call insights. This capability is invaluable for businesses running campaigns across different channels. In industries where speed is critical, like retail or customer service, this can be a game-changer for improving both conversions and customer satisfaction.
I also found Invoca’s AI-driven signals and conversational intelligence scorecards particularly useful. These tools help standardize metrics and assess sales performance, making it easier for teams to make data-backed decisions and adjust strategies with reliable insights.
Another aspect I really appreciated was Invoca’s well-structured training program. Learning new software can often be a challenge, but Invoca has streamlined the process. After a brief session, I was able to navigate the platform with ease, minimizing downtime and allowing teams to quickly take advantage of its full potential.
When it comes to reliability, Invoca excels. It has proven to be a dependable platform over time, with many users reporting consistent satisfaction even after extended use. This kind of stability is essential for businesses that rely on conversion tracking and optimization, ensuring that Invoca remains a trusted part of their analytics infrastructure.
That said, there were some drawbacks. One major limitation I encountered was the inability to link inbound calls directly to actual sales. While call tracking is valuable, without a clear connection to revenue, it’s harder to measure the full impact of calls on business outcomes.
I also found that certain data parameters weren’t supported, requiring workarounds that added unnecessary complexity and slowed down analysis.
Additionally, the time zone functionality was a bit frustrating. While Invoca reflects the user’s time zone, it doesn’t adjust for the local time zone of the calls. This created confusion, especially for businesses operating across multiple regions.
What I like about Invoca:
Invoca’s AI-driven signals and conversational intelligence scorecards helped standardize metrics and assess sales performance. This allowed teams to make data-backed decisions and adjust strategies based on reliable insights.
The well-structured training program made learning the platform seamless, reducing downtime. After a brief session, I was able to navigate Invoca easily, ensuring that my team could quickly take full advantage of its features.
What G2 users like about Invoca:
"Invoca provides actionable insights that enhance our understanding of the customer journey and experience. It equips us with the tools and data needed to make smarter decisions about functional processes and digital strategies, including paid search. The data helps drive measurable results, and our account representatives actively listen and assist in implementing signals that align with our strategy."
The inability to link inbound calls directly to actual sales made it difficult to measure the full impact of calls on business outcomes. While call tracking was valuable, the lack of clear revenue attribution limited its effectiveness in assessing ROI.
The time zone functionality was frustrating, as it didn’t adjust for the local time zone of calls. This created confusion for businesses operating across multiple regions, making it harder to accurately interpret call data.
What G2 users dislike about Invoca:
"Setting up tracking and reporting in Invoca can take time initially, especially with a large volume of numbers and locations to monitor, making it a logistical challenge. However, this setup process is a one-time effort, and once completed, the system runs smoothly."
I’ve tested impact.com’saffiliate, influencer, and referral marketing platform, and it has certainly proven to be an impressive tool for managing different types of partnerships all in one place.
One feature I particularly liked was how seamlessly it handles various types of partnerships, whether dealing with affiliates, influencers, mobile apps, or even B2B partners. This centralized approach makes it so much easier to manage and scale multiple partnership models, especially if your business is looking to expand and diversify. I was also impressed by the platform’s advanced partner attribution and commission options.
Another standout feature is theplatform's data-driven insights. The analytics are exceptional, giving me a clear view of which partnerships are driving results. They allow me to adjust my strategy in real time based on detailed metrics. The platform is perfect for companies looking to get actionable insights from their data.
Impact.com stands out as the only platform I’ve tested that allows you to create crediting rules based on customer interactions with both paid media and affiliates. This feature gave me a much more nuanced understanding of how each part of my marketing strategy contributed to conversions, and I could set up custom rules to ensure commissions were accurately attributed.
I also appreciated the detailed referral URL reports and the easy configuration of brand portals, which significantly streamlined the entire process of managing partnerships. The platform makes it easy to handle even the most complex tasks without getting bogged down in unnecessary complications.
However, there are a few areas where I believe Impact.com could improve. First, the dashboard could benefit from more customization options. It would have been helpful to tailor the dashboard to better suit my individual needs and preferences, especially when managing multiple campaigns simultaneously.
The reporting tools, while functional, could definitely be more robust. I often felt limited in terms of customizing the reports to extract the specific insights I needed. A greater level of flexibility in report customization would have made it easier to analyze data and gain deeper insights into my campaigns’ performance.
Lastly, while the implementation process is relatively straightforward for those familiar with tools like Google Tag Manager, it can be a bit challenging if you don’t have access to a tech resource. For businesses without a technical team on hand, the setup process may take longer or require additional support.
What I like about impact.com:
The platform provides exceptional data-driven insights, offering a clear view of which partnerships drive results. This allows for real-time strategy adjustments based on detailed metrics, making it perfect for companies focused on optimizing performance.
Impact.com is the only platform I’ve tested that enables crediting rules based on both paid media and affiliate interactions. This feature gave me a more nuanced understanding of how different marketing strategies contributed to conversions, ensuring commissions were accurately attributed.
What G2 users like about impact.com:
"Impact.com offers an intuitive platform for managing affiliate campaigns, making it easy to create custom links efficiently. The wide range of well-known brands provides excellent partnership opportunities, especially for content creators. Its robust analytics features help track performance and optimize campaigns effectively."
The dashboard could benefit from more customization options to better suit individual needs. Tailoring the layout and prioritizing specific metrics would make managing multiple campaigns easier.
While implementation is straightforward for those familiar with tools like Google Tag Manager, it can be challenging for businesses without technical resources. Companies without a dedicated tech team may face a steeper learning curve or require additional support to set up the platform efficiently.
What G2 users dislike about impact.com:
"The dashboard customization in Invoca is user-specific, meaning updates to pinned or built reports are not visible to other users on the account. This requires each user to manually update their dashboard, which can be inconvenient. A shared dashboard option would improve collaboration and efficiency across teams." - impact.com Review, Tori P.
8. Dreamdata
Dreamdata is an impressive tool for B2B revenue attribution and growth analytics. While testing it, I noticed several features that set it apart in terms of functionality and usability.
One of the most noteworthy features of Dreamdata is how it collects data from multiple sales and marketing channels and unifies them under a common identifier. This capability allows me to track a customer’s entire journey from the first touch to the deal's closure, which is essential for understanding the full scope of revenue-driving activities. Dreamdata excels at connecting and cleaning data from multiple sources. This made the insights we received feel reliable. I was able to trace the complete customer journey, from awareness to conversion, ensuring that attribution was both accurate and actionable.
Another powerful feature was its custom attribution models. The ability to tailor these models to suit our complex B2B sales cycle was a game changer. I was able to pinpoint exactly which campaigns, content, and channels were contributing to revenue at each stage of the customer journey.
Dreamdata also provides a clear view of channel performance, which I found particularly valuable for understanding the ROAS, content performance for conversions, and how various initiatives impacted our sales pipeline. With Dreamdata’s robust insights, I felt more confident in reallocating resources, as the platform helped me avoid relying on incomplete attribution models like first/last touch, which can lead to over or under-investment in certain channels.
That said, there are a few areas where Dreamdata could improve. The platform's data visualization was a bit complex and not as intuitive as I would have liked. The scope of the data Dreamdata handles is immense, but if the visualization capabilities were on par with other tools in the market, it could significantly enhance the user experience.
Although the dashboards are customizable, the ability to save customized views would be a time-saver. It would allow us to access key metrics without needing to go through the setup process each time.
Lastly, I found that there was a learning curve when it came to setting up advanced attribution tools. While Dreamdata offers excellent support for 99% of queries, processing all the information during setup could feel overwhelming, especially when dealing with more advanced features.
What I like about Dreamdata:
Dreamdata’s custom attribution models allowed me to tailor tracking to our complex B2B sales cycle. This made it possible to pinpoint which campaigns, content, and channels contributed to revenue at each stage, enhancing decision-making.
The platform provided a comprehensive view of channel performance, helping me analyze ROAS and content performance for conversions. With these insights, I could confidently reallocate resources and avoid reliance on incomplete attribution models like first/last touch.
What G2 users like about Dreamdata:
"The filtering and dashboard capabilities of Impact.com are robust, and after completing a couple of training sessions with the team, the tool becomes very easy to use. The implementation was smooth, as I set up about 90% of it during the trial, with only a few adjustments needed during onboarding. Now, I use the tool daily, and with continuous updates and new integrations, it continually enhances our marketing efforts."
The data visualization was complex and not as intuitive as I had hoped, making it harder to interpret key insights quickly. Given the vast amount of data Dreamdata handles, improving visualization tools could significantly enhance usability.
While the dashboards were customizable, the inability to save customized views meant reconfiguring metrics each time. This added extra steps to my workflow, making the process less efficient than it could be.
What G2 users dislike about Dreamdata:
"We find it a bit tricky to track upsell and cross-sell deals separately at the moment. It would also be helpful to see ad impressions at the account level in the customer journey (ABM) dashboard, as currently, we can only view engagements and touchpoints. Additionally, having the ability to view trend and period-on-period comparisons natively in the tool would be a major improvement. However, the Dreamdata team takes feedback seriously, so we’re optimistic that these features will be available soon."
Flowcode is a QR code platform designed for measuring conversions. One of the biggest advantages I noticed was howsimple and user-friendly it is to create custom QR codes.
The interface on Flowcode’s web platform is intuitive and easy to navigate. I could easily generate QR codes, customize them, and integrate them into various marketing materials.
The real power, however, lies in its ability to redirect QR codes to other URLs as needed, which offers great flexibility. This feature was incredibly useful, as I could easily adapt the codes over time and track the success of different campaigns.
Another major benefit was the ability to add UTM parameters to the Flowcodes. By adding UTMs, I could track clicks, data, and attribution directly in Google Analytics 4 (GA4), which was crucial for analyzing the performance of print ads, over-the-top (OTT) content, connected TV (CTV) ads, and outdoor activations.
However, there were a few aspects where Flowcode could improve. Organizing the QR codes within the platform could get a bit frustrating at times. As I added more and more codes, keeping track of them became challenging.
Another downside I encountered was with design flexibility of the QR codes. While Flowcode offers some customization options for the design, it restricts you to a certain set of colors in the builder. It would be much more ideal if I had more freedom in choosing custom colors to match branding requirements or campaign needs.
The search functionality within the platform also left room for improvement. The need to open multiple folders to find a specific QR code can be time-consuming and cumbersome. A more robust search tool that allowed for easier and faster access to specific codes would greatly enhance the user experience.
What I like about Flowcode:
The platform's ease of use allowed me to quickly create, customize, and integrate QR codes into various marketing materials. This streamlined the process and helped me save valuable time while improving campaign execution.
The ability to add UTM parameters directly to Flowcodes enabled me to track detailed campaign performance in GA4. This feature was essential for accurately measuring the success of diverse campaigns, from print ads to OTT and CTV content.
What G2 users like about Flowcode:
"It seems like you're talking about Flowcode, which offers a simple and user-friendly platform to create custom QR codes. The ability to customize the design and redirect codes to different URLs while tracking their success is very useful, especially for print marketing and digital signage. Additionally, the customer support team is responsive and helpful whenever needed, making the experience even more efficient."
As I added more QR codes, organizing them within the platform became increasingly challenging. A more efficient way to categorize or manage codes would have been beneficial, especially for larger-scale campaigns.
Flowcode’s design flexibility was limited by the color options available in the builder. Having more freedom to choose custom colors would allow for better alignment with branding and campaign requirements.
What G2 users dislike about Flowcode:
"The backend interface of Flowcode can be a bit confusing, particularly when it comes to sharing the platform among a team."
During my time testing Demandbase One, an account-based, go-to-market platform for B2B enterprises, I discovered several standout features that make it an excellent tool for enhancing marketing attribution and campaign structures.
One of the most compelling aspects is its ability to provide intent signals that indicate which accounts are actively researching your company. This feature not only alerts you to potential prospects but also helps guide your targeting strategy by providing prediction scores on which accounts to focus on for outreach.
Using the identification and scoring model, I was able to prioritize prospects and guide them more effectively down the sales funnel. This helped me design more targeted marketing strategies, which was a significant advantage.
The platform gives you full control over the building process, enabling you to shape your attribution models based on your unique requirements. This flexibility was incredibly useful for structuring campaigns and refining attribution models to better align with our objectives.
One limitation I encountered with Demandbase One is that the lead-to-account matching engine is not always intuitive, making it challenging to maintain high data quality for lead-to-account associations.
While the platform integrates with various systems, syncing data between Demandbase One and other tools can sometimes be complex and time-consuming. Ensuring data consistency across platforms requires significant effort, which may pose a challenge for teams that rely on smooth, real-time data flow.
Lastly, the user interface (UI), while comprehensive, can be overwhelming for end users. Without full training, it can be difficult to leverage all the insights that Demandbase One offers, which might hinder the platform's effectiveness for less experienced users.
What I like about Demandbase One:
Demandbase One's ability to provide intent signals allowed me to focus on the accounts most likely to convert. This data-driven approach enhanced my targeting strategy and optimized my outreach efforts for better conversion rates.
The platform’s attribution models' flexibility gave me full control over tailoring campaigns according to our business needs. This customization was key in aligning marketing strategies with our goals, allowing for more effective campaign structures.
What G2 users like about Demandbase One:
"For me, the most impactful feature is the ability to customize experiences by creating custom lists with various filters and selectors. I also appreciate the reporting aspect, which is great for our sales and marketing teams to easily measure success by tracking engagement."
The lead-to-account matching engine was not always intuitive, which made it challenging to maintain high data quality for lead-to-account associations. This inconsistency could result in inaccuracies, making it harder for me to make informed decisions based on reliable data.
Syncing data between Demandbase One and other systems was sometimes complex and time-consuming. The effort required to ensure data consistency across platforms created friction for me, especially since I rely on seamless, real-time data flow.
What G2 users dislike about Demandbase One:
"I find the dashboard difficult to navigate. While there are many great insights available, it can be hard to surface them. You often end up clicking into an account or prospect and then have to figure out how to return to the main report. It would be more helpful to have a high-level, actionable report that aligns better with my workflow."
1. What factors should I consider when choosing attribution software?
When choosing a marketing attribution tool, consider factors such as ease of integration with existing platforms (CRM, marketing automation, etc.), support for multiple attribution models, scalability, data accuracy, reporting capabilities, and cost. It’s also important to assess how the tool can handle multi-channel data and track customer journeys effectively.
2. How many marketing attribution models are there?
There are several marketing attribution models, with the main ones being first-touch, last-touch, linear, time decay, and position-based. Each model allocates credit differently across the customer journey, providing insights into which touchpoints are most influential in driving conversions.
3. What are the differences between first-touch and last-touch attribution?
In first-touch attribution, all the credit for the conversion is given to the first touchpoint a customer interacts with, whereas last-touch attribution gives all the credit to the final touchpoint before the conversion. These models help businesses understand the role of different interactions in the conversion process.
4. How does machine learning improve attribution?
Machine learning enhances marketing attribution by analyzing large datasets to identify patterns and correlations in customer behavior across multiple channels. It can dynamically adjust attribution models based on real-time data, leading to more accurate and actionable insights, optimizing marketing spend, and improving campaign effectiveness.
5. What types of businesses can benefit from attribution tools?
Marketing attribution software can benefit any business that uses multiple marketing channels and wants to understand how each touchpoint contributes to conversions. This includes B2B, B2C, eCommerce, and enterprise-level businesses looking to optimize their marketing strategy and improve ROI.
6. Which is the best B2B marketing attribution software?
For B2B marketing attribution, Dreamdata is considered one of the best options due to its full customer journey mapping and seamless CRM integration, which provides detailed insights into the buyer's journey. A more affordable alternative is HubSpot Marketing Hub, which offers marketing attribution features at a competitive price point.
Because guessing isn’t a strategy
Without the right attribution tool, marketing can quickly become overwhelming. But once I implemented the right system, everything started to fall into place. Suddenly, I could streamline my efforts, minimize wasted spending, and keep my marketing on track.
After thoroughly testing and reviewing the best attribution software, one thing became clear to me: the right platform is a game changer when it comes to truly understanding the customer journey. With so many options available, I’m confident you’ll find the solution that gives you the data needed to make smarter, more informed decisions and take your marketing strategy to the next level.
Looking to explore a trending new channel? Dive into affiliate marketing tools to enhance your strategy and expand your reach!
Devyani Mehta is a content marketing specialist at G2. She has worked with several SaaS startups in India, which has helped her gain diverse industry experience. At G2, she shares her insights on complex cybersecurity concepts like
web application firewalls,
RASP, and
SSPM. Outside work, she enjoys traveling, cafe hopping, and volunteering in the education sector. Connect with her on
LinkedIn.
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