What is Help Scout and what are its top alternatives?
Top Alternatives to Help Scout
- Zendesk
Zendesk provides an integrated on-demand helpdesk - customer support portal solution based on the latest Web 2.0 technologies and design philosophies. ...
- Intercom
Intercom is a customer communication platform with a suite of integrated products for every team—including sales, marketing, product, and support. Have targeted communication with customers on your website, inside apps, and by email. ...
- Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning. ...
- Reamaze
Reamaze can handle your support@ email box just as well as it can handle your in-app support and live chat. Or Facebook Page. Or Twitter handle. ...
- Jira Service Desk
It lets you receive, track, manage and resolve requests from your team's customers. It is built for IT, support, and internal business teams, it empowers teams to track, prioritize, and resolve service requests, all in one place. ...
- FreshDesk
Freshdesk is an on demand customer support software that works across multiple support channels. ...
- Front
Front allows you to collaborate with your team, stay productive, and use email and social together. Currently available on Mac, Windows, Web, and Mobile. ...
- JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...
Help Scout alternatives & related posts
- Centralizes our customer support135
- Many integrations72
- Easy to setup59
- Simple26
- Cheap26
- Clean12
- Customization7
- $1 Starter Pricing Plan4
- Woopra integration4
- Proactive Customer Support3
- Charitable contribution to SF hospital for $20 plan1
- Full of features1
- Remote and SSO authentication with CMSs like WordPress1
- Integrations0
related Zendesk posts
Zapier is one of our favorite tools in our stack. We automate the entire company with Zapier. When a lead fills out the form on our website, it creates an opportunity on Zendesk. We have an entire pipeline of automation that goes from our website, to Zendesk, it then creates a contract in Pandadoc and creates an invoice in Xero.
I will like to know, which chatbot can be compared with Zendesk/Zopim if there's a need to migrate?
- Know who your users are168
- Auto-messaging115
- In-app messaging as well as email107
- Customer support88
- Usage tracking68
- Great Blog18
- Organized engagement, great ui & service11
- Direct chat with customers on your site9
- Very helpful4
- Onboarding new users3
- Tirman2
- No Mac app2
- Free tier2
- Filter and segment users2
- Github integration2
- Very Useful2
- Changes pricing model all the time7
related Intercom posts
As a small startup we are very conscious about picking up the tools we use to run the project. After suffering with a mess of using at the same time Trello , Slack , Telegram and what not, we arrived at a small set of tools that cover all our current needs. For product management, file sharing, team communication etc we chose Basecamp and couldn't be more happy about it. For Customer Support and Sales Intercom works amazingly well. We are using MailChimp for email marketing since over 4 years and it still covers all our needs. Then on payment side combination of Stripe and Octobat helps us to process all the payments and generate compliant invoices. On techie side we use Rollbar and GitLab (for both code and CI). For corporate email we picked G Suite. That all costs us in total around 300$ a month, which is quite okay.
Vue.js Intercom JavaScript Node.js vuex Vue Router
My SaaS recently switched to Intercom for all customer support and communication. To get the most out of Intercom, you need to integrate it with your app. This means instrumenting some code and tweaking some bits of your app's navigation. Checkly is a 100% Vue.js app, so in this post we'll look at the following:
- Identifying a user with some handy attributes
- Getting page views right with Vue Router
- Sending events with Vuex
- Some nice things you can now do in Intercom
After finishing this integration, you can actively segment your customers into trial, lapsed, active etc. etc.
- Open-source61
- Fast and Flexible48
- One platform for every big data problem8
- Great for distributed SQL like applications8
- Easy to install and to use6
- Works well for most Datascience usecases3
- Interactive Query2
- Machine learning libratimery, Streaming in real2
- In memory Computation2
- Speed4
related Apache Spark posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.
Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).
At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.
For more info:
- Our Algorithms Tour: https://algorithms-tour.stitchfix.com/
- Our blog: https://multithreaded.stitchfix.com/blog/
- Careers: https://multithreaded.stitchfix.com/careers/
#DataScience #DataStack #Data
related Reamaze posts
- Integration with Jira and Confluence1
related Jira Service Desk posts
FreshDesk
- Omnichannel capabilities3
- Centralizes our customer support2
- Great Value for Money2
- Cheap1
related FreshDesk posts
Front
- It's the most professional email application I've seen7
- Great agenda organization with time tracking and snooze1
related Front posts
I use Front instead of Zendesk because even in very early beta it had gotten many of the little details of what we wanted in a customer support product right. E.g. emails look like they come from me, instead of looking like they come from a ticketing system. And they do a good job at basic workflows like assigning tickets, and having side conversations about tickets. Other features I like are their keyboard shortcuts, and canned responses (though I expect other products have those as well).
For context, the Zulip support team is roughly 1-3 people, depending on who you count.
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast896
- Light weight745
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness236
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Setup is easy12
- Its everywhere12
- JavaScript is the New PHP11
- Because I love functions11
- Like it or not, JS is part of the web standard10
- Can be used in backend, frontend and DB9
- Expansive community9
- Future Language of The Web9
- Easy9
- No need to use PHP8
- For the good parts8
- Can be used both as frontend and backend as well8
- Everyone use it8
- Most Popular Language in the World8
- Easy to hire developers8
- Love-hate relationship7
- Powerful7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- Popularized Class-Less Architecture & Lambdas7
- Agile, packages simple to use7
- Supports lambdas and closures7
- 1.6K Can be used on frontend/backend6
- It's fun6
- Hard not to use6
- Nice6
- Client side JS uses the visitors CPU to save Server Res6
- Versitile6
- It let's me use Babel & Typescript6
- Easy to make something6
- Its fun and fast6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- Function expressions are useful for callbacks5
- What to add5
- Client processing5
- Everywhere5
- Scope manipulation5
- Stockholm Syndrome5
- Promise relationship5
- Clojurescript5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Hard to learn1
- Test1
- Test21
- Easy to understand1
- Not the best1
- Easy to learn1
- Subskill #41
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
related JavaScript posts
Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark