Google Cloud Dataflow vs. Fin by Intercom

It is best in cases where you have batch as well as streaming data. Also in some cases where you have batch data right now and in future you will get streaming data. In those cases Dataflow is very good. Also in cases where most of your infra is on GCP. It might not be good when you already are on AWS or Azure. And also you want in-depth control over security and management. Then you can directly use Apache beam over Dataflow.

Incentivized

FIN is great if you need someone to direct the customers based on their problems. You also have the option to use multiple languages if you have a worldwide customer base, so that's great. If you provide enough documentation to feed it, FIN can also solve tickets on its own, which enables your team to focus on other tasks. You can also have him handle conversations in other applications, such as Discord or Slack, and have them create ticket issues in JIRA if your team uses it.

Incentivized

• Streaming, Real time work load
• Batch processing
• Auto scaling
• flexible pricing

• It is very easy to train
• It does a great job of recommending answers when little context is given.
• I love the ability to create a snippet to address issues in the moment or in the long term, based on FAQs.

Incentivized

• More templates for Bigquery and App Engine. There is only limited options for templates so the things we use can limit.
• I would like native connectors for Excel (XLSX) to reduce the need for custom wrappers in financial pipelines.
• Debugging Google Cloud Dataflow using only logs in Cloud Logging can be overwhelming sometimes, and it’s not always obvious which specific element in the flow caused a failure. IT uses a lot of time.

Incentivized

• It seems some users really struggle to figure out how to escalate to a human (especially through email).
• Not excited about how "soft" resolutions still count as resolutions and are paid for. Though some abandoned cases appear to be able to be concluded as "the user got the answer they needed", there are others where they clearly didn't, because they just open up another chat (or even more), trying to get more info. This pads the resolution stats and makes it seem more effective than it actually is.
• Cost -- Fin is quite expensive. It helps us with scaling coverage, but we're not really saving money.

We have been and will be continuing our journey with Intercom and nothing too concerning has happened that I have experienced or heard of that has us on the edge yet. If it ever happens it will be something along the lines of "Outgrowing" the use of need of the platform.

Incentivized

It really saved a lot of time and it's flexibility really can give you infra which is future-proof for most of the use cases may it be streaming or batch data. And with this you can avoid use of resource-heavy big data offerings.

Incentivized

The core experience is solid but the key friction across our team is that there are so many new features for improving Fin are being launched. Content improvements, guidance settings, recommendations, trends, and monitors are each useful in isolation, but they sit across separate areas of the platform with no clear starting point. The recurring feedback from my team is that it is hard to know where to focus. A consolidated "Improve Fin" section could really improve the experience, the ideal option would be a training page where our team could improve Fin in one place, ideally by answering questions and Fin would then be able to add those details in the right place, where it's creating new guidance or building procedures. I feel that would make uptake a lot quicker.

Incentivized

always there

Incentivized

works perfect

Incentivized

Intercom is the premier customer support/engagement model and it definitely has one of the top tier customer support teams as well. I don't think I have ever waited more than 5 minutes to get the information I need or get help with an issue. They are incredible and I aim to model our customer service department after them.

Incentivized

Easy to know the learning path

Incentivized

The implementation was surprisingly easy but we are having to adapt from our old process to work well with Intercom.

Incentivized

Google Cloud Dataproc Cloud Datafusion

Although we have not utilised a specific chat box like Fin before in other websites, we have used ChatGPT and Claude within our general work. Our Product and Engineering team make use of Devin within Azure Dev Ops to support with their work. However, Fin is the most suitable for what our Support Team requires as this can be integrated into our chat with customers.

Incentivized

• cost saving from managing our own data center for ETL servers
• consumption based pricing
• with auto scaling feature, we were able to expand components to support work load

• New role opportunities — Using the “Fin-first” approach has reduced the workload for our Tier 1 team, giving them more time to focus on their own career growth. It’s also opened the door to a dedicated, AI-focused role, where a team member regularly reviews Fin’s answers and makes updates to help it perform even better.
• Enabling Fin has also reduced our response time and allowed us to meet SLA's.

Incentivized