What is Zapier?
Who uses Zapier?
Why developers like Zapier?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Zapier in their tech stack.
Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.
I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.
For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.
Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.
Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.
Future improvements / technology decisions included:
Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic
As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.
One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.
I've used more and more of New Relic Insights here in my work at Kong. New Relic Insights is a "time series event database as a service" with a super-easy API for inserting custom events, and a flexible query language for building visualization widgets and dashboards.
I'm a big fan of New Relic Insights when I have data I know I need to analyze, but perhaps I'm not exactly sure how I want to analyze it in the future. For example, at Kong we recently wanted to get some understanding of our open source community's activity on our GitHub repos. I was able to quickly configure GitHub to send webhooks to Zapier , which in turn posted the JSON to New Relic Insights.
Insights is schema-less and configuration-less - just start posting JSON key value pairs, then start querying your data.
Within minutes, data was flowing from GitHub to Insights, and I was building widgets on my Insights dashboard to help my colleagues visualize the activity of our open source community.
#GitHubAnalytics #OpenSourceCommunityAnalytics #CommunityAnalytics #RepoAnalytics
When starting a new company and building a new product w/ limited engineering we chose to optimize for expertise and rapid development, landing on Rails API, w/ AngularJS on the front.
The reality is that we're building a CRUD app, so we considered going w/ vanilla Rails MVC to optimize velocity early on (it may not be sexy, but it gets the job done). Instead, we opted to split the codebase to allow for a richer front-end experience, focus on skill specificity when hiring, and give us the flexibility to be consumed by multiple clients in the future.
We also considered .NET core or Node.js for the API layer, and React on the front-end, but our experiences dealing with mature Node APIs and the rapid-fire changes that comes with state management in React-land put us off, given our level of experience with those tools.
We're using GitHub and Trello to track issues and projects, and a plethora of other tools to help the operational team, like Zapier, MailChimp, Google Drive with some basic Vue.js & HTML5 apps for smaller internal-facing web projects.
The decision to go with KISSmetrics for our main live user input analytics tool was based on the integrations available with Slack and Shopify . Alterting the right people based on user actions without the noise that most of the tools will push as notification made the difference between KISSmetrics and the rest in this segment. Then the fact that Zapier can connect KISSmetrics with other apps like Salesforce Sales Cloud and G Suite makes the process very smooth.
Also the fact that we can automate some of the campaigns is saving a lot of time
Achieving #MarketingAutomation using AutopilotHQ
Some of the key aspects evaluated here: - Ability to integrate with Segment or Zapier - Being multi-channel (Not just Email automation) - Dozens of integrations and capabilities: SFDC, In app messages, SMS, Push Notifications, Direct Mail, Segment Events... - Allowing teams to operate outside of engineering dependencies - Segmentation against user attributes / user traits - Static or Dynamic segments - Concept of user journeys - And more
Combined with Segment and its own sets of integrations and capabilities, AutopilotHQ ended up being a very powerful tool for Product Marketing to use at SmartZip.
Couple of years later, there certainly were some overlap with the features offered by Intercom 's engagement module , but our team kept on using this tool given the greater range of functionality / capabilities.
Although Trello has some good and easy to use triggers to push updates from Trello in different environments we use, using Zapier has made our life much easier. Creating a zap is easy and a full management of those zaps are in a full overview to review and manage.
With GitHub in the same combo with Zapier and Trello it's very easy to track issues and bugs and make them available to the responsible project manager or team directly.
- A Zap is a blueprint for a task you want to do over and over. In words, a Zap looks like this: "When I get a new thing in A, do this other thing in B." The first part is the trigger and the second part is the action. An example is "When I get a new entry from a Wufoo form, create a new lead in Salesforce."
- You can pick what fields from the trigger service should go to the action service and you can use static text and custom fields too. For instance, you might say that the phone number from your Wufoo form should be the work phone of your new Salesforce lead.
- Zapier regularly checks your trigger for new data. When the Zap triggers, Zapier automatically performs your action for you. Continuing with the Wufoo scenario, say you receive five new entries. Zapier takes each one and makes a new lead in Salesforce, customized to the way you specified in your Zap.
- Without any more effort from you, data flows from one service to the other