Mixpanel

What do you like best about the product?

I use Mixpanel to track how users use our products and which parts of our web and mobile applications are used most. I can track many details and different kinds of user-initiated events, and use conversion rates and user categorization analysis to see the steps specific users follow. It helps us focus on real-life use cases that are relevant to users instead of getting lost in scenarios and features that are not used often and do not bring value to customers. Our experience with Mixpanel has been great.

What do you dislike about the product?

I found the initial setup slightly complicated, so our PM and QA teams needed support from developers. The reports and insights are very detailed and can sometimes make us consider details that aren’t relevant, though I don’t think it’s something to complain about.

What problems is the product solving and how is that benefiting you?

I use Mixpanel to track real-life use cases that are relevant to users instead of getting lost in unnecessary scenarios and features that aren’t used often or bring value to customers.

What do you like best about the product?

Their Analytic dashboard for the events. Pushing the events and metrics is easy and scalable. It's easy to see the analytics about our product usage. Their UI stands out and their API integrations are easy.

What do you dislike about the product?

Nothing as of now. Works for us without any issue.

What problems is the product solving and how is that benefiting you?

Our product usage and metrics completely rely on Mixpanel. Using Mixpanel, we track the feature usage and based on that we make decisions on product features. It is really helpful to understand our product usage. Their performance with huge data is also fast. Their dashboard's UI looks good.

What do you like best about the product?

I use Mixpanel for product event tracking across our web and mobile apps. The SDKs are lightweight and easy to integrate, and the tracking API is simple: one call with an event name and properties. Funnels, retention, and cohort reports are quick to build without SQL, so PMs and developers can answer questions themselves and spend less time on ad hoc queries. Live View and the event debugger let me check event names and properties from a local build in seconds during development or QA. That shortens our feedback loop, keeps tracking data clean, and helps make the funnels and reports PMs rely on accurate. I also get quick post-release visibility, can isolate drop-offs by properties like app version or platform, and can validate A/B experiments. The data export and raw API let us pull data into our own pipelines when needed. Setup was fairly easy: installing the SDK and sending the first events took under a day, and the docs and quickstart guides are clear. Once we had identity management set up, it was stable. Mixpanel is a strong, developer-friendly product analytics tool with easy SDKs and fast self-serve reporting.

What do you dislike about the product?

I find event governance gets messy at scale: duplicate or inconsistently named events pile up, and Lexicon cleanup is manual. Pricing climbs quickly as event volume grows. Complex analysis beyond standard reports still needs a data warehouse export. When I pull large date ranges through the export or query APIs, I have to add my own batching and retry logic to stay within rate limits. Some advanced endpoint docs lack full request and response examples for edge cases. Planning a clean tracking plan took effort, and getting ID merge right took some testing.

What problems is the product solving and how is that benefiting you?

Before Mixpanel, I had to write SQL against raw logs and wait on the data team for product questions. Now PMs and devs self-serve funnels and retention, so we spend less time on ad hoc queries, and we catch broken tracking or conversion drops within hours instead of weeks.

What do you like best about the product?

I have been using Mixpanel for the past 4 years. The best thing is the experiment testing feature; it's very easy to create custom cohorts and analyse data for long periods of time.

What do you dislike about the product?

When it comes to viewing tabular data and the line items are slightly higher, it's not very helpful. Plain visualisation is very good, but tabular format data can be improved.

What problems is the product solving and how is that benefiting you?

A lot of our marketing decisions are driven by Mixpanel. Looking at the campaign's impact at different levels is very insightful. Our company spends millions on digital marketing, and our decision-making has been very refined now. Apart from this we also do a lot of user funnel optimization looking at leakages

What do you like best about the product?

Easy to share and view metrics. I like that it's very customizable.

What do you dislike about the product?

It's hard to find what I'm looking for without asking a data partner.

What problems is the product solving and how is that benefiting you?

It helps me understand how users are interacting with new designs.

What do you like best about the product?

The behavioral insights are the most interesting part. I like being able to examine individual actions and understand more about how customers interact with a digital shopping experience.

What do you dislike about the product?

It takes some effort to organize the tracking properly. Initially, deciding which events deserve attention can be a little confusing, particularly when there are several things you want to measure.

What problems is the product solving and how is that benefiting you?

It addresses the challenge of understanding what visitors actually do after arriving at an online store. This can help identify customer behavior patterns and potential obstacles in the purchasing journey.

What do you like best about the product?

The most helpful feature was the new Mixpanel AI agent, which allows me to quickly gain valuable insights simply by using prompts. The user experience is very intuitive, and the ability to connect with other analytics platforms makes it even more powerful. The performance is impressively fast. The pricing is also reasonable, offering great value and plenty of benefits. Additionally, the onboarding process was seamless, and the UI is visually appealing.

What do you dislike about the product?

When the Mixpanel agent generates answers, the webpage sometimes crashes when it’s working with larger datasets. I then have to reload the page, and it becomes very slow afterward. The processing could be optimized to improve stability and performance.

What problems is the product solving and how is that benefiting you?

I’m a designer, and this tool helps me understand the metrics while keeping the UI simple and easy to follow. I can quickly see what’s happening with events and trends, and the graphs present everything clearly.

What do you like best about the product?

What I like best about Mixpanel is how it lets us dig into our lead and policyholder behavior without leaning on our outside dev contractor every single time. I’m Hans Isip, Operations & Business Systems Coordinator at Mountain Peak Insurance Advisors out in Denver. We’re an independent insurance agency with 11–50 people, and I spend most days testing tools, building workflows, locking down permissions, troubleshooting integrations, and walking our agents, service staff, and accounting team through new systems. We use Mixpanel mainly to track how people move through our website, our self-service quote flow, and the supplemental insurance storefront we run for add-on policies. Before Mixpanel, all we really had was basic Google Analytics data. It could tell us how many people landed on our quote page, but it couldn’t tell us where they dropped off inside that multi-step quoting process, or whether someone who started a quote later picked up a policy renewal email from our marketing sequence.

The cohort analysis is the standout feature for our agency work. A couple months ago, our sales team noticed a lot of people starting auto insurance quotes but never finishing them. We had no clue which step was scaring them off. I built a cohort in Mixpanel grouped by quote start date, then tracked them through each form stage: entering vehicle info, adding driver details, reviewing coverage options, submitting for agent follow-up. It quickly showed the majority were bailing on the coverage selection screen. It turned out the page was showing way too many optional endorsements all at once, which overwhelmed shoppers new to insurance terminology. We simplified that view, trimmed down the add-on options shown by default, and added a short plain-language tooltip for the critical coverages. Within a month, our quote completion rate ticked up nicely, and our agents got fewer calls from confused prospects asking to walk them through every single optional add-on. That change came straight from what I found in Mixpanel.

I also like how flexible the event setup is. I can tag custom events for things like downloading our coverage guide, booking an agent consultation, opening a renewal reminder link, or visiting our supplemental product shop. Since we’re heavy on compliance, it helps us separate casual browsers from serious shoppers who are actively engaging with policy-related tools. The dashboards are easy enough for me to build and share. I create a simple weekly view for our sales and marketing lead so they can see which ad sources bring people all the way through to quote submission, not just those who click the ad once and leave immediately.

We rely on role permissions too. I can share read-only dashboards with our marketing lead without letting them edit or delete our tracked events. That keeps our tracking setup consistent and avoids accidental changes that would mess up our trend data, which matters because we use these insights to plan renewal outreach for hundreds of policyholders.

What do you dislike about the product?

One of the more frustrating roadblocks I deal with regularly in Mixpanel is its limited support for the custom identity logic we need as an insurance agency. I’m Hans Isip, Operations & Business Systems Coordinator at Mountain Peak Insurance Advisors in Denver. My typical workload covers tool rollouts, permission tuning, CSV imports, integration testing, and supporting our agents, client service team and back-office staff. We track prospects moving through our online quote flow, visitors browsing our supplemental insurance store, and existing policyholders engaging with renewal content. A really common scenario for us is that a prospect starts filling out a quote on their cell phone, leaves it unfinished, then returns a few days later from a desktop computer — sometimes entering a different email, or just using their phone number as the main point of contact.

Mixpanel doesn’t handle this cross-device matching cleanly. It defaults to creating separate user profiles for each session unless we have perfect consistent IDs from the start. Not long ago, I was putting together a funnel report for our home insurance quoting flow, and the conversion metrics looked off compared against our CRM records. After digging through dozens of individual profiles, I found that many finished quotes belonged to users who already had an earlier abandoned quote session under a different anonymous ID. There’s no straightforward native rule to auto-match users by phone number, which is our most reliable unique identifier for leads. Manually merging those duplicate records takes forever, and it’s easy to miss a handful of them, which skews our funnel and cohort analysis.

Bulk data uploads bring their own set of headaches too. Each month I export a list of active policyholders from our CRM to enrich Mixpanel profiles with policy details: coverage line, assigned agent, policy effective date, and renewal timeline. Date fields often get misinterpreted during CSV mapping, and multi-value custom attributes like discount eligibility or prior claims history frequently fail to import properly. This matters a lot because we use this linked behavioral data to time our renewal nurture emails. If renewal dates import incorrectly, we risk reaching out to policyholders at the wrong time, which creates confusion and compliance risk for our agency. I’m forced to run a full line-by-line validation on every upload before I can use the dataset.

What problems is the product solving and how is that benefiting you?

Before we got Mixpanel, we only had surface-level visitor stats to work with, and it really limited how we understood people exploring our agency’s online tools. I’m Hans Isip, Operations & Business Systems Coordinator at Mountain Peak Insurance Advisors in Denver. I spend my days standing up new software, managing access permissions, troubleshooting integrations, and supporting our agents, service team, accounting and marketing folks. We run our online quote portals, a smallstorefront for supplemental coverage, plus automated renewal campaigns for our policyholders. Back then, we relied mostly on basic analytics that could only tell us how many people landed on our quote page. It couldn’t show us where they dropped off, what pages they lingered on, or if a quote starter later engaged with our renewal and follow-up emails. Our sales and marketing team was just guessing which parts of our quoting experience were causing friction.

Mixpanel changed that by letting us track each step of the client journey, from first site visit all the way through quote submission and renewal engagement. The funnel and cohort tools are the biggest win for our agency. A few months back, our agents kept mentioning that home insurance prospects seemed to give up halfway through the application. We didn’t know if it was the coverage questions, document upload step, or something else entirely. I built a funnel tracking every stage of that home quote flow, and it quickly revealed that most people exited when we asked for detailed prior claim information. We adjusted that section: added simple explanatory text, reordered the fields, and split that heavy section across two shorter screens instead of cramming everything onto one page. After that tweak, abandonment at that step dropped noticeably, and our agents had more completed quotes coming their way.

It also helps us separate casual browsers from serious prospects. I set up custom events for actions like downloading our coverage guide, booking an agent consultation, viewing flood insurance add-ons, or visiting our supplemental product shop. We can then build segments to see which marketing channels bring in users that actually move toward submitting a quote, not just clicking an ad and leaving right away. That lets our marketing budget go further, instead of pouring money into ads that only drive empty clicks.

The permission controls are a nice bonus too. I can share read-only dashboards with our marketing lead, so they can review performance trends without being able to edit or delete our tracked events. That keeps our tracking setup consistent, which is important because we use this data to schedule renewal outreach for our policy book.

I’m fully aware of its downsides, though. Cross-device identity matching is shaky, CSV imports often mess up our policy date and metadata fields, and syncing those behavioral insights back into our CRM takes manual work. I still spend time cleaning duplicate profiles and exporting raw data to build custom reports. Even so, Mixpanel fills the big gap we had: it turns vague visitor counts into actionable user behavior data. It helps us refine our online quoting experience, reduce unnecessary friction for prospects, and make smarter decisions for our lead nurture and renewal workflows, all without leaning heavily on outside dev support.

What do you like best about the product?

I use Mixpanel for product metrics, funnel tracking, A/B tests, and product analytics, and it makes it quite easy to see how recently released features are performing. I like that its event-based data model fits product analytics so well. I can build a funnel from raw events in just a few minutes and break down charts by user properties, cohorts, or other properties without writing SQL. Funnel creation and tracking are simple to set up, especially compared with doing each tracking task in SQL, and Mixpanel has made my life easier. I can answer questions in about 20 minutes that might take a data analyst a day with SQL or GTM tracking, and product managers can access behavioral metrics directly without a ticketing queue. I also find the retention analysis one of the best, with multiple customizable views and on-the-fly filters. The flows report is useful for understanding what users do between defined steps and where they run into friction. Funnel analysis, feature adoption tracking, and cohort-level retention are all easier for me to do in Mixpanel.

What do you dislike about the product?

I find that query performance can degrade significantly on large data sets. Complex funnels over 90-day-plus windows can take 30 to 60 seconds or longer, which interrupts my analytic flow while I wait for results. The data governance side seems weak, with little clarity around event taxonomy or an upstream tracking plan, so duplicate events and ambiguous property names can build up and erode trust in the numbers if they aren’t handled well. It can also take 2 to 3 weeks to get a feel for the platform, and onboarding non-technical stakeholders can feel intimidating. I’d like clearer, more user-friendly onboarding and walkthroughs, possibly with AI guidance, videos, or demonstrations, and an easier way to build reports from scratch.

What problems is the product solving and how is that benefiting you?

I use Mixpanel to see if users do what we built or get confused, track funnels, adoption and cohort retention, and spot faults. Clean tracking lets me answer questions in about 20 minutes instead of a day in SQL and base sprint reviews on behavioral data, not gut feeling.

What do you like best about the product?

Its event-based analytics, funnel analysis and user segmentation features make it easier to understand how users interact with a product, identify drop-off points and uncover opportunities for improvement.

What do you dislike about the product?

Getting reliable insights depends heavily on having well-defined events and consistent tracking across the product. Setting up and maintaining event tracking can require significant engineering effort and poorly structured events can make analysis more complicated than necessary.

What problems is the product solving and how is that benefiting you?

I use product analytics to evaluate conversion funnels, identify drop-off points, analyse user behaviour, and measure the impact of product changes. These insights help me validate hypotheses, prioritise improvements, and make more informed product decisions.