Segment Reviews

My main use case for Segment is connecting databases and websites to track server-side user activity.

One specific example of how I use Segment for server-side user tracking is when a user comes to our website, clicks around, and we track those actions to see if they went to the about page or clicked on a specific product. We record those actions and send them back to our database. Once they submit, we send all information they submitted to our database, and from there, using Segment, we push it to an analytics layer and then to our database. We then use that to share out to our CRM and send out to Google or back to Facebook, wherever we need.

Our primary use case is tracking.

Our favorite feature that Segment offers is the website tracking.

What stands out to me about the website tracking is the data accuracy and ease of implementation. We were using an in-house solution to track and also used client-side tracking through pixels, and we found that Segment's solution was much more accurate and easier to implement.

Segment has positively impacted our organization by helping us with our website tracking. Segment has improved our data quality and our ease of collection, and most importantly, it has saved us time by not having to maintain a custom tool for server-side tracking.

Everything is covered in our current use case, but potentially more connectors could be a good addition. That is the main thing; everything is covered that we need.

I have been working in my current field for about five years.

My advice to others looking into using Segment is that it works even at a small scale. You can use this with a smaller website that has less than 100 users a day, and it also works at a large scale. I would rate this product a 7 out of 10.

Public Cloud

Amazon Web Services (AWS)

I have used Segment for more than a year.

I was working with Addx and Segment was used to align profiles and different user profiles. I used it for journey building, unifying different emails or profiles, and tracking profile behavior.

My primary use case was an abandoned cart journey where when users were viewing their cart, we would get an event. Whoever was going to view their cart would be added to our journey, and we had journey steps where they would receive emails that helped us in getting more money and subscriptions.

The events we implement with the help of Segment are great. I can view profile behaviors and determine what things to recommend to users and many other things. It is great to use to get to know customers.

Segment's best features in my experience include the profile unified system, which allows me to know if a profile is anonymous, but they have used their email before, so I would know that this anonymous profile belongs to which email. That is the best one.

When I use the unified profile system, it works smoothly for our team. The only challenge was the session functionality. If someone was using a different device, that was a difficult part, but otherwise, it was great.

Segment has positively impacted our organization because we could get the number of people receiving emails, and the rate of conversion was all we were getting from Segment. I did not see a change in conversion rates, but we were able to monitor it properly.

There was a race condition in the Segment journey that I highlighted to Segment, and I think they must be doing something with it. Everything else was perfect.

I think everything has improved. They are working on it, so it is fine on my side.

I have been working in my current field for four years.

Segment is stable.

Customer support is fantastic.

I would advise others looking into using Segment that it is a great product if they want to know more about their users. I rate this review an 8 out of 10.

We don't have a partnership, but we're a consulting organization. We've proposed Segment as a solution to a few of our clients, and some of them have adopted it. We've helped them with the configuration and integrations.

One example is in the InsurTech space. The client had a direct-to-consumer (D2C) channel for selling and distributing policies, along with other channels like an agent portal for sales, leads from partners and purchased databases, and ads from Google and Facebook. We had a lot of different data sources, and we wanted to consolidate all those leads into a CDP instead of just sending them straight to the CRM, which was HubSpot. 

So, we used Segment to ingest all the leads from those sources, and then integrated with a few third-party tools like Verisk to qualify the leads within the CDP. The qualified leads were then sent directly to the CRM, where they became MQLs—marketing qualified leads—and entered the sales funnel.

I like the straightforward way of connecting with various data sources and destinations. That's the most valuable feature. It has built-in integrations for a lot of them, so the overall effort required for integrations is relatively low. 

And they have SDKs in a wide range of programming languages, so it can support pretty much any language if you need to integrate it with your own products, not just off-the-shelf solutions. 

In this case, the D2C application was built using Java, and it was easy to integrate, with a few challenges.

The main challenge is that the SDKs are pretty similar across programming languages, and they're not super flexible. They might not support certain use cases. It has a set of functions that work well if they fit your needs, but if you need something custom, you can't rely on the SDKs and have to use recipes. And using those recipes extensively isn't ideal. 

For example, we were getting leads from the D2C application, sending them to Segment, and then from Segment to HubSpot. If Segment could mimic HubSpot's API, we could leverage HubSpot's SDK capabilities even through Segment. 

But Segment's API is generic, so it doesn't do anything tailored to HubSpot. As a product designer, I know that would be hard to accomplish anyway. It's not a criticism, because I would probably design it the same way. 

But as a consumer, I don't care how it's designed; I care if it fits my use case. If not, how much effort will it take to make it work? That was the challenging part.

It took a lot of time to integrate Segment and make it communicate with HubSpot in a certain way. So, the challenge is the lack of flexibility in the SDKs, given the capabilities of the destinations.

From my experience, it's mostly fine. It could benefit from more customization capabilities. The product itself is good, but it would be awesome if it allowed you to write your own extensions to augment the CDP's capabilities.

And another suggestion. It's not about a missing feature, but rather something Segment is doing that I personally don't think a CDP should do. It's like a mobile phone you use for watching videos, listening to music, and making calls. But to be a good mobile phone, you need to be the best at making and receiving calls, and texting. Everything else is a distraction. Instead of optimizing for those distractions, you should solidify the basics.

To illustrate this, Segment has many capabilities that overlap with things like CRMs, campaign management systems, tracking systems, and so on. These capabilities can give a small startup a real kick-start, but as you scale, the capabilities other than the core CDP features don't scale as well. 

For example, it does campaign management, but it's not really a full-fledged campaign management system. When you're starting out, it's fine, it's great, it fits almost all your use cases. 

But as you grow from a two-person organization to a 300-person organization, you'll have to deal with more complexity. You'll likely need to look for a dedicated campaign management system and integrate it with Segment. 

Now, if you've been using Segment's campaign management for a long time, moving that part to a different system will be a roadblock.

We have been using it for about a year and a half, maybe a bit longer.

Segment is stable. There have been some occasional challenges with time lags between data being passed from the source and reaching the destination, but it's not common.

In terms of general scalability, I think it scales very well. It's capable of handling loads of traffic. I'd rate it a nine out of ten.

I wouldn't call that scalability because it's more about the functional and auxiliary features. Not all of the features scale equally well.

I've used mParticle and Cadence from a vendor called the Data Team.

Top pros of Segment compared to those other products: 

• It's easy to set up.
• It's SaaS, so no infrastructure expertise is needed.
• It integrates easily with most common SaaS-based tools. 
• The segmentation capability is also great.

Cons of Segment:

Customization can be hard. Sometimes the Segment SDKs don't match the API contracts of the destinations, which necessitates custom coding.

Cadence had its own strengths. It was a different kind of CDP, with a primary strength in machine learning-based lead qualification. Segment doesn't have that capability. I don't remember much about mParticle; it's been a while since I used it extensively.

The initial setup is straightforward. 

1. First, you need to understand why you're using it, so establish the business objectives, particularly from sales and marketing perspectives. 

2. Second, identify what's driving you to use a CDP. Pinpoint the specific use cases, especially for smaller or newer setups. That's crucial, which dictates whether or not a CDP is necessary. 

In my opinion, a CDP should typically be used when the organization and its systems are mature, with plenty of customers, not right at the beginning. 

Consider if you're adding unnecessary complexity and cost by using a CDP too early.

So, first, establish the need. Then, identify the source and destination systems. Define the purposes. 

For example, you might use it for lead qualification or to consolidate leads in one place before sending them to a central management system. That's a major use case for any CDP. 

Once you've identified the use cases and established the need, identify the data sources and destinations. 

3. Then, move on to the implementation strategy. Start with out-of-the-box connectors, then look at any custom solutions that require custom integrations, like your D2C or agent portal. 

When planning, assess how much is readily available and how much needs custom work, as that's where we encountered challenges.

The resources required for deployment depend on the use cases, but it can start with just one developer. However, they need to be well-versed in marketing and sales concepts.

It's important because a typical developer might not have the business knowledge to gather requirements effectively. Someone who understands lead management, tracking, Google Analytics, and similar tools will be easier to code and contribute to requirements development.

The average timeframe for a full deployment of Segment is two to four weeks on average. You can even get started in a day if you don't have any custom tools.

Moreover, it does not require much maintenance. It's one of those systems you can set up and forget.

The ROI is entirely dependent on the nature of your business. If you're a new business, I don't think you'll reach ROI breakeven quickly with a CDP product. 

However, if you're an established business facing challenges with lead qualification or segmentation, for example, Segment can bring ROI very quickly.

It's not for everyone.

The pricing was on the higher side but it wasn't excessively high. It's definitely not tailored for the smallest businesses, but it's well-suited for setups that anticipate significant growth.

My one-line advice, not just for CDPs but for many other products, is this: Don't adopt them simply because they exist. 

Establish and validate your use case, and consider the ROI before configuring requirements. This is especially relevant for startups. 

Often, they have a young CTO who's enamored by loads of technology, viewing them as shiny toys to play with. This can lead to adding excessive complexity that becomes difficult to manage later, potentially resulting in a net loss. 

I'd always recommend starting with the basics, and a CDP isn't a basic need for most organizations. Start simple, evaluate your needs continuously, and when you encounter challenges worth solving, explore solutions like Segment.

Overall, I would rate the solution an eight out of ten.

Public Cloud

My main use case for Segment is to perform ETL with tracking user behavior, user funnel interactions with the website, where the user dropped, and bringing all this data into our database.

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.

The best features Segment offers include holistic interaction with different channels and platforms and the ability to bring data wherever I want, such as to any relational database. This is particularly useful because Segment supports analytics for GTM tagging and BI use cases, allowing user interaction data to reach our database.

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.

Segment can be improved in the initial phase regarding data quality checks between different channels' attribution versus Segment itself. I have observed many cases where the data is incorrect or duplicated, often due to multiple channels attributing to one single user. Bringing the data into a unified understanding requires business-specific insights that are not particularly addressed by Segment. Although data accuracy was initially lacking, we managed to clean the data after it was brought into our database, which is a downstream responsibility rather than Segment's.

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.

I have not been using Segment for many years; it has been very recent, with my experience being approximately eight months to one year.

Segment is stable.

Segment's scalability depends on the licensing, as more users or higher website traffic can be integrated into Segment with a higher licensing tier, which incurs additional costs. Nevertheless, the available upgrades and features in Segment are quite good.

I have not used customer support during my time with Segment, so I hope it is reliable. However, I am uncertain if customer support is now handled by AI or real-time human agents.

I previously used an in-house solution to bring data into our database and did not use any third-party tools. This marked my first experience with a third-party tool, Segment, which we opted for after conducting thorough research that indicated it would be our best current solution.

I have seen a return on investment after integrating Segment, with significantly increased revenue due to the introduction of BI capabilities, where we pull data from the website to our database. Revenue serves as a direct metric, while the BI part further enhances revenue outcomes. Additionally, our developers use Segment more consciously and precisely, and with the help of AI, we anticipate reducing costs further in the future.

My experience with pricing, setup cost, and licensing is primarily based on comparisons with other tools, revealing that Segment is much cheaper, particularly regarding premium licensing.

Regarding Segment's AI capabilities, I believe governance and security involve a worldwide unified approach being monitored across different tools and platforms integrated with enterprise data. AI governance and security need to be assessed properly before AI can take over various functions on our behalf.

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.

Segment is deployed in my organization as an on-premises solution.

We like the easy integration with analytics services, especially Google Analytics; easy-to-write code and integration with Node.

We've had a couple of projects where robust analytics were part of the requirements. Inserting some very simple code snippets has made this part of it a breeze for our developer so he can concentrate on the hard stuff.

The design of the website is such that you lose context when clicking around (e.g. when clicking on docs). Also, it would be nice if it were easier to add users at various levels (i.e. read only, add to groups that can see multiple projects, etc)

6 months

We used Google Analytics directly in the past.

The initial setup was somewhat in the middle, because it required installing a module for Node, then adding the code. There's a bit of suspension of disbelief involved at how easy it is.

We used our in-house expertise. As I stated earlier, it's not hard.

No, we went with the product our dev recommended and we are very happy.