Segment Reviews

My main use case for Segment is to share a practical experience about how we used Segment at XP Investimentos bank to transform behavioral data into business intelligence and high-impact marketing campaigns, where we worked in the MarTech arm with a very clear goal: to turn Segment into our CDP, making it the main source of truth about our customers while understanding how they interacted with the XP app to personalize the end-to-end experience.

Before giving a specific example of how I used Segment to personalize customers' experience in the XP app, I will talk about the challenge and the technological solution, where my role as a software engineer was directly tied to implementing, maintaining, and optimizing this pipeline. I knew the tool very well inside and we created and configured sources, structured the receipt of events via HTTP calls or webhooks, and developed specific scripts to trigger two fundamental types of events: track, focused on capturing behavioral events within the app, and identify, responsible for capturing customers' registration data, ensuring we continuously used and updated customers' registration data for a solid, enriched, and always up-to-date base. The architecture of the solution and the data flow was the way to make this work at bank scale, managing millions of daily events through a robust architecture where events generated in the app passed through an intermediary application responsible for collecting these actions through messaging services like Kafka and RabbitMQ, allowing us to format the events with custom fields for proper identification, processing, and standardized sending to Segment, which let us segment and create highly qualified audiences crossing in-app browsing behavior and product acquisition with the client's investor profile, opening a huge range of operational and marketing opportunities like abandoned cart campaigns and personalized banners displaying real-time customized offers.

The process to create those qualified audiences involves a multidisciplinary approach seeking a successful final impact, where building this ecosystem is not a one-person job and requires deep integration between multiple technology and business fronts, as we worked side by side with the Mobile, interface, hub, advisors, BFF, backend, and database teams to ensure that front-end collection was performant and did not impact the app experience, while serving the Revenue team directly as it used Segment as its main work tool and source of truth, enabling them to create dynamic audiences, trigger targeted campaigns, and extract precise reports for strategic decision-making in a summarized implementation of Segment at the XP bank, transforming our communication approach into a fully personalized strategy focused on the investor's journey, an enriching technical project where I applied software engineering to leverage MarTech results generating real business value.

I believe that the offer banners were successful cases from my experience with Segment, as we tracked the entire flow from click, view, and conversion of marketing campaigns, which brought in significant revenue reaching about 650 million in monthly revenue.

In my opinion, the best feature that Segment offers is the creation of audiences focused on the investor's profile, which was the biggest differentiator enabling us to cross a large number of behavioral and customer profile data points, generating increased engagement in marketing campaigns.

Regarding audience creation, I consider Segment CDP interface itself the most valuable feature, as it allows the marketing team to work with a business-focused profile without needing deep programming knowledge, greatly facilitating the creation of marketing campaigns while integrating with tech solutions.

Segment allowed for the organization of the entire source of all audiences, making it a very robust tool where the cost pays for itself through return on investment, highlighting the tool's cost-benefit ratio as a major differentiator.

Segment has a very significant positive impact on my organization as it provides robust data to understand our consumer's profile and needs, focusing on the customer's needs in various life stages, ultimately maximizing our efforts on the customer, which is where the main gain with Segment lies.

I have not used Segment for more than a year, so I am not aware of its current evolution, but I know there was a migration from Segment to Adobe as a strategic decision by XP bank, which pointed out unified databases as an improvement area compared to Segment, where they effectively utilized AI for creative marketing campaign generation.

The necessary improvements in Segment based on my experience focus on providing more tools for the marketing team, particularly using AI to create campaigns through images and short videos, enhancing communication with end customers via offer banners in a more automated and effective manner.

I used Segment from December 2022 until around the end of 2025.

Segment is very stable with no major issues encountered, aside from avoiding Friday deployments to prevent losing any event capture, ensuring stability throughout our operations.

Segment's scalability is very good given the large processing capacity handling millions of events from around 10 million customers daily, where every in-app navigation and various accesses were tracked and sent to Segment CDP without encountering issues.

Customer support for Segment was satisfactory, as communication happened through tickets and scheduled meetings with support staff who sometimes spoke Portuguese, with a need to adapt to the tool's capabilities rather than having fully customized solutions. I would rate customer support around seven or eight due to what I perceive as limited availability for immediate assistance compared to the overall value derived from the tool's capabilities.

I did not use a different solution before joining XP as we directly employed Segment CDP, which was later replaced by Adobe.

My experience with pricing, setup costs, and licensing was smooth, though I did not know the total expense, estimated around 1 to 2 million per month, with licensing restrictions on access to Segment CDP tool, experiencing a negative aspect when triggering numerous tests that exceeded our monthly limit resulting in a 5 million fine.

I have already shared measurable results demonstrating this positive impact of Segment at XP Investimentos, highlighting our ability to increase engagement and conversion in marketing campaigns by 30-40% depending on the campaign, generating monthly revenue of up to 650 million through triggers sent via email, WhatsApp, and push notifications in the XP app itself.

I have previously detailed the return on investment from our relevant increase in revenue attributed to Segment, where for every 1 to 3 million invested, we generated 650 million, with no staff reduction but an increase of advisors from 17,000 with goals now surpassing 20,000, while we also aim for a target of 2 trillion in investments under custody, highlighting our solid knowledge base for relevant marketing campaigns.

My experience with pricing, setup costs, and licensing was smooth, though I did not know the total expense, estimated around 1 to 2 million per month, with licensing restrictions on access to Segment CDP tool, experiencing a negative aspect when triggering numerous tests that exceeded our monthly limit resulting in a 5 million fine.

I do not recall which other options were evaluated prior to Segment, but I recognize that Adobe was in the same tier, and the challenge was that multiple applications had already integrated with Segment, leading to a migration project lasting about six months.

My advice for those considering using Segment is to thoroughly research the market and understand the tool's benefits as it is a strategic investment that necessitates discussions with other businesses to benchmark their experience and success post-implementation. My final comment on Segment is that it was a very enriching experience that taught me about event-oriented applications and how behavioral events and registration data are stored in Segment, allowing me to appreciate the potential for creating marketing campaigns based on a deep knowledge of our customer profiles. I would rate this product an 8 out of 10.

Segment connects with our data streams to send WhatsApp campaigns and email campaigns to our international audience, including Argentina, Nigeria, South Africa, and other South American markets.

One of our problem statements was to send WhatsApp campaigns to the Nigerian audience to understand how they would respond to our campaigns, so as to have incremental revenue based on the voucher or discount codes that we give to them, and also to measure the performance of the campaigns once we send them. The bottleneck situation was that we didn't have any campaign measurement capability. That's why we reached out to Segment team from Ireland. The idea was to get the data infrastructure ready, which is required for Segment to get the data streams. Once the data was set up, we were able to set up journeys based on our needs and pre-select the data identifiers, and we sent the campaigns using WhatsApp setup from Segment.

For the campaigns, we touched base with the architect from Segment team. They were very helpful in setting up a data infrastructure via regular sessions with our data architecture team and product team. We identified approximately 25 data fields which would be useful to select the primary and secondary characteristics for the campaigns. This engagement lasted almost two to three months. Once the data was set up and signed off by the high authorities, we tested the setup. Once we were confident in the setup, we then collaboratively worked with the marketing team to set up the campaigns and set up WhatsApp campaigns to start with. The performance showed that there was a 2% conversion rate on the campaigns that we sent, and we were happy with the prototype setup using campaign analytics of Segment.

In the initial rollout of the campaigns, we definitely saw a 2% conversion rate. The end-to-end return on average ad spend showed an improvement of 14%. That was good, especially because we were using Segment for the first time. This was near the industry standards.

The best features that Segment offers is the ability to connect with data of any type because we had a very complex data set which could be integrated into Segment systems. That was helpful. Another valuable feature was that Segment is part of Twilio and Twilio has its own suite of communication features such as WhatsApp, CRM, and others. We can integrate the communications of WhatsApp and email communications from Twilio to Segment. That was helpful again. Another feature of Segment was the scalability of Segment. We could replicate the same setup for other countries because initially, our main target was to send campaigns for international countries such as Argentina, Nigeria, and South Africa. The next country that we wanted to target was the United States. It was easy to replicate the setup for other countries.

Segment enhanced our capability to use third-party tools for enhancing our analytical capabilities because segmentation as well as the campaign measurement using Segment helped us also identify the AI component of measurement as well as sending campaigns. In a way it actually changed our mindset on how we absorb the data set keeping the long-term view objective in mind. It also helped us be more data-driven when it comes to campaign measurement.

One thing that was surprising and inconvenient at the same time was the risk of becoming too rigid with the data. The pre-selecting data identifiers was useful for the initial use cases, but as we got more mature with our use cases, it could become more restrictive because the business might later decide to introduce more data attributes or feeds. That means more dynamic segmentation requirement. Segment didn't have that good capability to be more dynamic with the inclusion or exclusion of data feeds.

Segment can be improved by centralizing the features that it has. I understand that it has gone through acquisitions, such as Twilio and Segment still operates as a separate system. If they can integrate the Twilio aspect of communication with Segment system itself, it will save our time when it comes to the infrastructure setup because we had to reach out to DevOps to have the right setup connected to our Twilio communications. It actually would save time for the clients of Twilio Segment to make sure that the systems are well integrated. It would also be good to have a good understanding of the inherent constraints because we remember that WhatsApp communications were not applicable for certain countries. That could be a part of the knowledge transfer in the onboarding discussions itself, so as to avoid any surprises in the downstream conversations. More support from WhatsApp conversations could be helpful. It could be possible that some countries don't allow multiple numbers. If we can have multiple numbers for the communications, that would be helpful to reach out to our target client base.

For the technical challenge, we can have more flexibility on the data feeds that Segment can incorporate from the client database because the data needs can change for any corporate, whether it be small, medium business, or large enterprise. If we can retrofit the data irrespective of some data fields being empty, that would be really helpful. It would also be good to have two or more data feeds input because it's difficult to get the data infrastructure done on the client side. It's better to have a customization of the data irrespective of the sources it came from. That would be really helpful for the data manipulation activities inherent to the segmentation.

The advice that I will give to anyone who is looking at Segment as a potential partner is to make sure that you have your problem statement ready. Ask the difficult questions to Segment about how the data will be used from a storage perspective and from a processing perspective. Are there any challenges inherent in their data which might not be understood by Segment system? Have the questions ready about the data infrastructure because the data is key to getting the right processing and the accurate processing of the data from Segment.

I have used Segment for almost 18 months in my previous company.

Segment is stable.

Segment scalability is good when it comes to geographic enablement but it is not scalable in terms of data. As I mentioned before, when different streams of data change, it might not incorporate once the data is set up. It should be flexible and robust enough when it comes to handling different streams of data once the product is set up.

Customer support is good. I won't say excellent, but they do respond and they have a dedicated customer support team.

This was the first time we used a third-party tool for AI segmentation as well as campaign measurement.

We worked with Segment team in 2023 and 2024.

Segment pricing depends upon the number of interactions and the number of campaigns sent. Irrespective of the great service and onboarding support, it is a little pricey. For example, we were still not ready with the data setup and we realized that the onboarding support hours were getting over and that was keeping our project at a standstill. We had to request the onboarding team for extra hours. After multiple requests, the request was granted for the free hours, but I think that should not be the case since the beginning of the project because the complexity of the project and all should be discussed beforehand and that should come from Segment because Segment is aware of the complexity inherent by working with different clients. Pricing could be a bit cheaper and more flexible and transparent in nature to avoid any confusion because the switching cost of any technology is very expensive for any organization and that can add to the frustration. Segment can do more competitive analysis when it comes to pricing its products.

I don't have specific numbers to share, but we did see improvement in the campaign's performance and ability of our organization to send campaigns without building the technology up front. We definitely saved money by not building the technology on our own. However, Segment is not that cheap. There's an investment of almost north of $1 million for more than three years contract. If Segment integration is very successful for any organization and the contract is long enough, then the ROI would be good. If not, then ROI might be a debatable issue.

We did evaluate other options and most of them were concentrated in US markets. We wanted to work for WhatsApp campaigns which could be worked in Argentina and South Africa. We zeroed down to Segment. I don't remember the names of other competitors we evaluated.

I have discussed all the challenges inherent in Segment that I have witnessed. The review rating for this assessment is 7.

I have been using Segment for the last two and a half years as part of my role as a Product Analyst. During this period, I have worked extensively with the platform for customer data collection, event tracking, analytics integration, and user behavior analysis across multiple digital touchpoints. My experience with Segment has involved implementing and managing tracking plans, integrating with third-party analytics and marketing tools, monitoring the customer journey, and ensuring data consistency between different platforms. Over time, I have also collaborated with the product marketing and engineering teams to streamline the data workflow and improve decision-making through centralized customer data.

My main use case for Segment is to centralize customer data management and product analytics. As a Product Analyst, I mainly use the platform to collect, standardize, and distribute customer event data across multiple analytics, marketing, and reporting tools for a single integration point. Segment plays a critical role in tracking user behavior across web and mobile applications. I also use it to monitor the customer journey, analyze feature adoption, and measure engagement metrics. This helps me understand how users interact with different parts of the product. Overall, this enables my product and business team to make data-driven decisions regarding feature improvements, customer experience optimization, and retention strategies.

Our team uses Segment as a central data orchestration layer across multiple business functions. What makes our implementation somewhat unique is the close collaboration between the products, marketing, analytics, and engineering teams through a shared tracking framework. We have also established a standardized event taxonomy and governance process with Segment, which helps to ensure consistency in how customer interactions are tracked across all digital platforms.

One of the best features Segment offers is its ability to act as a centralized customer data hub. The platform simplifies data collection by allowing teams to implement tracking once and send data to multiple downstream tools simultaneously. This significantly reduces engineering overhead and improves consistency across analytics and marketing systems.

Another standout feature for me is the extensive integration ecosystem. Segment supports integration with a large number of analytics platforms, CRMs, and data warehouses. This flexibility makes it easier for organizations to scale their data infrastructure without constantly rebuilding integrations. The audience segmentation and user profile unification are also critical and highly beneficial features. The platform helps consolidate customer interactions from multiple touchpoints into a more unified customer view, which enables more targeted marketing campaigns and deeper product usage analysis.

Segment provides strong capabilities overall, but there are still areas of improvement. One area that comes to mind is the pricing and scalability cost. As data volumes, event tracking, and integrations increase, the platform can become expensive for growing organizations. More flexibility in pricing models or clear scaling options would make it easier for mid-sized companies to expand usage without significant budget concerns.

Another improvement is that there is a learning curve for advanced configuration or governance features. Basic implementation is relatively straightforward, but some advanced capabilities, such as protocol management, identity resolution, custom transformation, and complex audience segmentation, can require deeper technical knowledge. More guided workflows, building recommendations, and simplified administrative controls would surely improve the usability for non-technical teams.

I have been working in my current field for the last five and a half years.

In my experience after using Segment, I believe that it is quite stable. For the majority of our day-to-day operations, such as event collection, routing, and integration, it performs consistently without any major disruption, which is extremely important because many downstream analytics and customer engagement workflows depend on that flow. I have not experienced any critical outages directly impacting our business operations. Segment maintains strong uptime and handles large volumes of traffic efficiently.

Segment is quite scalable. Whenever there is high demand for this solution and high traffic, Segment is able to handle that traffic. As our user base, event volumes, and number of integrations increased over time, Segment was able to handle the additional load without requiring any major architectural changes from our side. The platform's centralized infrastructure makes it much easier to scale analytics operations because I did not need to continuously rebuild or redesign data pipelines for every new tool or workflow.

The customer support is really helpful and knowledgeable. They are always happy to help. I am not much in touch with customer support currently. At our initial phase, whenever I required any help related to the setup, I contacted them and they provided me with the solution in very little time. However, due to regional timing differences, I received some replies with a delay. My personal experience with them is quite good.

One of the most measurable benefits has been the time savings for engineering and analytics teams. By centralizing event tracking and integration, I reduced the amount of custom development and maintenance work required for analytics and marketing tools. Based on internal estimates, engineering effort related to data integration and tracking maintenance decreased by roughly 40 to 50%. From an analytics operational standpoint, data validation and troubleshooting efforts decreased significantly because tracking became more standardized and product and business teams spent less time reconciling inconsistent reports, which improved productivity across departments.

Another area where I have personally seen ROI was through improved customer insights and conversion optimization. Better visibility into user behavior helped me identify friction points in onboarding and adoption flows, and optimization initiatives informed by Segment data contributed to measurable improvements in engagement and conversion metrics, including onboarding completion improvement in the range of 15 to 20%.

As an experienced user of Segment, I have a few pieces of advice to provide. My main advice for organizations considering Segment is to invest time upfront to build a strong data strategy and event tracking framework before starting implementation. Segment is extremely powerful, but its long-term success depends heavily on how well the data structure and governance processes are designed from the beginning. I would also recommend involving cross-functional teams early in the implementation process. Product engineering, analytics, marketing, and customer success teams often rely on the same customer data in different ways. Aligning these stakeholders around common KPIs and tracking standards helps to maximize the platform value across the organization. I would rate my overall experience with Segment an 8 out of 10.

I used Segment's audience prediction tool to identify look-alikes and connect them through Meta Ads, Google Ads, and email marketing. In addition to that, I was able to create other types of audiences such as exclusion audiences that allowed me to save money on campaigns and not contact customers who had already purchased.

One of the latest features Segment has released and which I find the most useful is that with artificial intelligence, I can now create flows in an almost automated way.

The automated flows and the whole A/B testing part I also find very interesting.

Segment has saved marketing costs, which has allowed me to use that investment elsewhere. It has allowed me to do much more personalization than I could do manually.

I understand that this same layer of artificial intelligence could be used to integrate external tools. That would make it easier for people who are not purely technical to do integrations and not need such a large team to be able to manage it.

Segment needs better integration with, or a much simpler integration with, external tools.

When I saw the number of users who had been excluded from advertising, that already allowed me to identify how much money I was saving. If, for example, I made about 5,000 people who had already purchased not be targeted by advertising, I was saving a considerable amount of money that could be around €10,000 to €15,000.

When my tickets are high and I handle a considerable amount of data, it is very profitable.

I have seen time savings and automation, although I have not yet managed to quantify it.

Segment is currently the main customer data source of truth and the CDP we use. Our CDP has become more important over the last few years and is basically the center of all of our customer data from both B2C and part of our business.

In my day-to-day work, I collaborate with marketing in order to set up audiences and make sure that they're feeding into the correct sources so that they can activate.

Regarding our main use case, we're also checking profiles and making sure that the data that's flowing into Segment is what we're getting into our CRM, which is called Iterable.

Segment has impacted our organization positively. First of all, we have meetings with them where they give a lot of good ideas on how to use the tool and best practices. They give us really some good inspiration.

In the first year of having the tool, we weren't using even half of the features that it has available, but as time went on and we were able to clean up our data and fix a lot of issues that were going on behind the scenes, we've been able to do some of the cool things Segment offers, especially around the Engage product line.

The best features Segment offers are the audience building features. We've also launched predictive audiences, which is so far really promising for us and marketing has a lot of ideas for activating these types of audiences. We're going from using historical data to using current data to get more predictive with how we're activating.

In my experience, the audience building tools compared to other solutions I've seen or used are really sophisticated. I've used other CRMs in the past for this, and I would say the type of data you're not getting as much of is what you do when you're activating or creating the audiences within the CDP. I think predictive audiences require a 360 view of the customer in order to create these types of AI audiences because they use a lot of different data points.

How it's helping the team is by giving us more ways to reach our customers and being more proactive in the type of campaigns that marketing can launch. They have a lot of good ideas and some good things in the pipeline.

There's a lot of documentation that is really helpful. I think a bit more video tutorials for those that are really new to a CDP could be really helpful.

I chose a rating of eight out of ten because these video tutorials would really illustrate how to use the tool to its full potential, and perhaps some more hands-on support from the Segment team would push it to a ten.

I was an end user of Segment for about a year, and then I've been managing audiences as well as the data flow from the CDP to CRM for about two years, so three years total.

Segment is stable.

Segment's scalability is amazing. It's fully capable of handling all of the different use cases that we have in our company and we have a very complicated company.

Segment has impacted our organization positively. First of all, we have meetings with them where they give a lot of good ideas on how to use the tool and best practices. They give us really some good inspiration.

Segment's customer support is amazing. I just mentioned that it would be nice to have more hands-on support, but that's about it.

Positive

Before Segment, we used a legacy customer data management tool, which is a legacy technology that we've had for a while. We're actually in the process of deprecating that this month and fully relying on Segment as our main customer data platform.

I wasn't involved in the negotiation about pricing, setup cost, and licensing, but in the new negotiation that we have coming up, I know that we're very happy with the pricing so far.

We launched a user abandoned basket flow using Segment, and I would say it probably saved us weeks worth of time had we gone with the solution directly within the CRM. I think we got a much better solution in that way. It's hard to quantify exactly the hours spent, but from that abandoned basket flow, it was something around seven million DKK that has been made since we launched it.

The main metric that I have is for the abandoned basket flow that we have running through Segment, and I would say it's to the tune of seven million DKK.

I wasn't involved in the negotiation about pricing, setup cost, and licensing, but in the new negotiation that we have coming up, I know that we're very happy with the pricing so far.

Before choosing Segment, we evaluated other options such as BlueConic, which is the main one that I know we've considered.

The advice I would give to others looking into using Segment is to make sure your data is in order and that you have cleaned it to the best of your ability.

I used Segment as a partner and a go-to-market partner for a customer data activation practice, and we were partnered together for two years very closely. Subsequent to that, I was still partnered with them, but we did less work together, and today Segment is a CDP that we would use, but my relationship with them is not as strong.

My main use case for Segment is for customer data activation.

I capture customer data, understand the patterns and trends going on, and test against those understandings in an omnichannel manner. The primary use case is for omnichannel orchestration and how we could personalize and make a better experience for an individual based on our understanding of who they were. Thus, the primary use case would have been personalization.

Segment is similar to most other CDPs in terms of its offerings, and where they differ.

At the time, one of the differentiators for Segment was the fact that they were part of Twilio and there were multiple technologies that would integrate, such as Auth and SendGrid, which created a whole omnichannel experience.

I really enjoyed working with Segment's partnerships team, as I did not implement Segment for myself but was a consultant that implemented it for others. Their partnerships group, when I was working closely with them, was very strong and very good. Plus there were strong market development funds to tap into, and we could jointly show up at conferences together and be thought leaders together, so I thought the program was good.

When we were at various conferences, we were able to show the specific use cases for customer data activation in retail and retail use cases and demonstrate how Segment connected to all the various Twilio components. This helped people see how it could come to life, how a call center could act on customer data, and how an individual could be authenticated so easily. Thus, us being able to demonstrate that and show the business value jointly worked really well.

Integration was hard. The integration of any CDP is hard, and the go-to-market messaging is that it is easy for any CDP, and it isn't. It would maybe be easy if a customer's data was in perfect order, but that is generally not the case.

The professional services were a little too simplistic. They had great people, but implementing a CDP is quite challenging, and I don't think that Segment teams thought of the whole architecture and the ecosystem and how Segment was one part of it. They became a little monomaniacal on what is the one use case and didn't recognize that data could live anywhere and needed to be harvested and transformed, leading to a hard time seeing the big picture. When we worked with customers who were using the professional services, they weren't always happy with the implementation because it was a little too simplistic and didn't live up to what the sales team said it could deliver.

I have been working in the marketing field for over 15 years.

I would rate customer service as 4 out of 10.

We deploy Segment for customers, so it is not specific to us. Therefore, it would be multiple different implementations.

I would say it is important to have a phased activation plan, think about your use cases, think about your data governance, and consider the environment that you are bringing Segment into. Having the technology is not a magic bullet, as there are many other factors that will make it successful. Really think about the customer experience you are trying to drive towards and work back from that. I would rate this review overall as a 7 out of 10.

Segment serves as my primary tool for event routing and Profile Unify Sync. I utilize event routing because multiple tools exist in our stack, including a website, mobile application, and server. All these sources need to be connected to Google Ads, Facebook Ads, TikTok Ads, Snapchat Ads, our data storage bucket, a data warehouse, and various third-party tools.

I implement numerous transformations between these connections and route different functions while sending data to HubSpot CRM, which significantly simplifies the process. This relates directly to events implementation. For product exploration, I connect different sources using the profile sync features. Back-end sources, Android sources, and iOS sources are enabled, which creates a complete unified profile of users with different metadata and marketing sources.

Segment makes my work easier through the many native integrations it provides, and since action fields have been implemented for every legacy integration, my instrumentation team and enablement team can obtain a more organized marketing profile to retarget users for advertising and selling our product. The main use case is to create a lookalike audience and retarget the current set of users.

Segment offers thorough documentation and native functions that I can use to filter events and transform event properties. I can test events from live sources whenever needed and construct events to ensure they work correctly at the end destination. The testing of live events and the log of the recent ten events in the event debugger prove to be very helpful features.

Segment has positively impacted my organization by reducing implementation time to one-third of what it previously took. Previously, we manually sent data to each destination, but Segment created a unified, single-source implementation across all different sources. Whenever an event is added, it goes to various different sources.

Segment could be improved by allowing community-based integrations, particularly for integrations available only via webhook that are not natively available, such as those from attribution platforms. Some edge case handling is needed that we currently perform on an external server. A standardized SOP would help us create our own integrations to newly created destinations.

I have been using Segment for the last five years.

The user interface is good, pricing is decent, and the support is also great. I received my reply from Segment support team within 24 hours.

I would say that we have reduced the implementation time from twelve weeks to six weeks, which represents significant time savings. This also helped us save around 40,000 US dollars across all different personnel in cost per project. We handle multiple projects, so this represents a client saving of 40,000 dollars in implementation.

I advise others looking into using Segment to define your use case first and then start with a few sets of events, perhaps five sets of events that are your key events, and then build on top of that foundation. Do not start with too many events initially. I would rate this product a 9 out of 10.

My main use case for Segment involves taking information from a ticketing database and trying to reconcile it with customers that were coming from the website that were known to see if we could retarget and re-communicate with them over email.

I set up a reverse replication from their Redshift database and pulled all the customers and their primary key IDs into Segment with known email addresses. Any signals we got from the website where customers authenticated, we would send that email address as well so we could identify that customers from the ticketing database matched with website traffic. We put them into a segment inside of Segment, which we would push to the email platform Marketo to send customers emails based on their interaction on the website and the ticketing database.

We also enabled the feature of Segment called Engage where the marketing team could go in and create any other type of customer audience segments they wanted without needing IT help. Those segments would be pushed into their email marketing platform, Marketo, for them to further send any other types of emails they want, providing the marketing team with their own self-service.

The best features Segment offers are ease of use and lightweightness. You do not need overly complex technology capabilities to be able to program within Segment, unlike some other CDPs that are quite complicated. Segment is very simple.

A particular feature in Segment that stands out as especially user-friendly is that it was easy to set up the back-end data feeds and pull out these audiences without the need to create special data models, making it quite turnkey. I could pretty much set up a Segment platform within a week or two versus some other CDPs that take a lot longer.

Segment has positively impacted my organization by enabling my client to improve their marketing and understanding of their customers through the use of Segment without needing IT as a bottleneck.

Segment could enhance its identity resolution and identity management by providing more options to resolve IDs and possibly improving how it handles anonymous ID resolution since most cases are anonymous.

I chose a seven for Segment because while its lightweightness made it easy to implement, it also lacks a lot of other features. However, it is probably acceptable that it did not have more features, as Segment is fine for what it is capable of doing. They need to improve some features, particularly adding more AI enablement and AI discovery that were not in the product when I was working with it.

Regarding Segment's AI capabilities, I think its accuracy and reliability of output were lacking. It did not have any AI capabilities when I was working with it, and I do not know if Segment has added any more AI capabilities since then.

I have been using Segment on one client for the last nine months.

Segment is stable in my experience.

I did not see any issues with Segment's scalability.

The customer support for Segment was very important to us, as we had dedicated support that helped us troubleshoot at the beginning. Their professional services team worked hand-in-hand with us in setting everything up and digging into the use cases, which was important.

I would rate the customer support a nine.

I did not previously use a different solution.

I can pretty much set up a Segment platform within a week or two versus some other CDPs that take a lot longer.

Their professional services team worked hand-in-hand with us in setting everything up and digging into the use cases, which was important.

I have not seen a return on investment and cannot share metrics such as time saved, money saved, or fewer employees needed.

Based on my experience, I think Segment's pricing, setup cost, and licensing are fair. It is relatively cheap and very useful at that price point.

Before choosing Segment, I evaluated other options such as Hightouch and Adobe CDP.

My advice to others looking into using Segment is that if people want a lightweight CDP platform to collect information, validate through email in terms of identity resolution, and provide their marketing team with a lightweight tool to create audience segments, they should definitely look at Segment as a great tool to use. I would rate Segment a seven overall.

My main use case for Segment is as a CDP to create a centralized view of the customer and help integrate the activation of audiences to downstream services.

A specific example of how I use Segment for this purpose is that we collect data from different data sources, and we then leverage the activation layer within Segment to populate data within Braze as the customer engagement platform. In practical terms, this could be somebody browsing our website or interacting with our loyalty system, and based on those user behaviors, we share those events and the data with those events with Braze, which is then used for personalized communications such as email, SMS, and push notifications.

That is the primary use case, and we have also implemented custom functions and transformation layers within Segment.

The best features Segment offers include the ease with which we can set up new data sources, the protocol structure they have for validating that the data is coming in the correct format, and the connection with back-end databases, mainly with Databricks where we both receive data via Databricks as well as push data to Databricks. The audience activation layer is also significant for our use case, and the ability to connect directly with the back-end database is very useful.

Segment's Databricks integration has helped our team significantly. In many cases from an audience standpoint, when building audiences, it often relates to customers as well as other data structures. With the database connection, I can create audiences, nested audiences, and other structures that connect customer data with many other types of data structures relating to loyalty, product, and purchases, and that has been a very powerful feature for us.

Segment has positively impacted my organization by making working with customer data a lot easier for us, as well as improving the speed at which we can ingest from new data sources and push to different activation layers. I have seen improvements with our time to market with Segment, which has improved dramatically due to the ease of use, allowing us to handle many use cases that were sidelined for years and now can be completed in days to weeks instead of months to years.

I think Segment can improve in terms of identity management, possibly in some of the protocols by adding more flexibility. I also see the need for more free-form searches such as regex or conditions that are not case-sensitive, which would be tremendously helpful.

I have been using Segment for about two years.

Segment has been stable in my experience.

The scalability of Segment for my organization's needs is very good.

Segment's scalability can be measured in terms of transaction volume, which it handled very well for us in terms of millions of records, and in terms of new use cases and functionality, we managed to find workarounds across various use cases by leveraging their functions and different activation layers, showing that from a scalable perspective, it performs quite well.

I have had experiences with customer support from Segment, particularly when we were learning the product and expanding our use cases. Their support team was extremely helpful in resolving issues, mainly when we struggled with the Databricks connectivity.

I did come from a previous system before Segment, but I am currently unable to recall what the system was, and it just was not adhering to all the needs we had.

The integration process with Segment was generally straightforward, although we faced a couple of challenges with Databricks, which I believe were due to corporate policies implemented within our Databricks environment that created the complexities.

I have seen a return on investment with Segment, primarily around time saved, and it also means we have had many more business-related users able to leverage it rather than needing development.

Before choosing Segment, we evaluated other options, including Azure Data, which was the next major competitor we considered, as well as Adobe Experience Platform.

For the basic functionality, the learning curve for new users getting started with Segment is very easy.

I find Segment relatively flexible within the defined functionality, and the ability to add custom functions helps extend that considerably.

Segment's documentation and resources provided are helpful.

Segment integrates very well with all our other tools.

I appreciate the simplicity in terms of getting into and leveraging Segment. Compared to some other CDPs, those options felt much more complex to reach the same stage, which is why I valued the simplicity of Segment.

I advise others looking into using Segment to understand who their intended users of the data are, what processing they want to conduct on that data, and how clean their input versus output will be. I would rate this product an eight out of ten.

A specific example of how I use Segment for tracking user behavior or funnel interactions involves using a SQL database, particularly a Postgres database, where I ingest user tracking behavior that appears on the platform, such as what pages the user visited, what pages they dropped from, how far they dug into the website, and the items they clicked, as well as where they lacked interactions. This helps me understand how to reach users to make them complete the user journey, ultimately trying to encourage them to purchase our product. I collect all the data in our database to provide holistic insights to stakeholders and higher management about user behavior drops, guiding further analysis or actions to bring users back to complete their experience.

Regarding my main use case with Segment, we utilize GTM and HTML tagging to track users from multiple different channels and platforms, allowing us to identify the first point of interaction or touch channel details. This helps us know which platform or channel attributed to bringing the user to our site. We also create unique user IDs to analyze if one user comes from multiple different channels, allowing us to use either the last or first interaction according to our business needs. We then analyze this data through SQL or visualize it with tools such as Power BI or Tableau, which are powerful for gaining multiple different insights, demonstrating the overall BI use case of Segment.

Of the features related to integrating with different channels, flexibility in sending data to various databases, and supporting analytics and BI, I find that the overall combination is what makes Segment most valuable for my team. If I were to focus on one specific aspect of Segment, it may be comparable to other third-party tools available in the market, but what differentiates Segment is its integration of analytics and business intelligence into one platform, enabling us to derive different insights and understand what went wrong or right in our processes.

Segment has positively impacted my organization because we are getting the data correctly, and the license fee is also very much comparable with other tools, resulting in an overall win-win situation.

To share more about the positive impact, since integrating the BI part with Segment, it is really helpful for understanding the user journey and making useful decisions based on that journey. We can now focus on generating more revenue by identifying the top five or ten regions, channels, or platforms, allowing further bifurcation of user demographics through different analyses via SQL. Segment serves as our source of truth in our database.

To elaborate on the needed improvements, data accuracy needs attention because there are use cases where the data is duplicated and requires deduplication. Additionally, the attributions or conversions from Segment also need to be accurate.

On the topic of AI accuracy and reliability of output, I have not extensively used AI since it was not integrated much when I left my old organization, but I hope AI can significantly enhance the platform's capabilities compared to those without AI.

My advice for others considering Segment is that if you want a unified solution for analytics and BI, Segment should be your go-to choice.

I rate this product seven out of ten.