ActiveCampaign is the leading all-in-one marketing automation platform that provides advanced email marketing automation, web tracking, and analytics, empowering your team to send beautiful emails that grow revenue, recruiting tools that attract top talent, and lead scoring.
MonkeyLearn is a text analysis platform that helps you identify and extract actionable data from a variety of raw texts, including emails, chats, webpages, papers, tweets, and more! You can use custom tags to categorize texts, such as sentiments or topics, and extract specific data, such as organizations or keywords.
It's easy to connect ActiveCampaign + Monkey Learn without coding knowledge. Start creating your own business flow.
Triggers when a new contact note is added.
Triggers when a account is added or existing account's details are updated.
Triggers when a new contact is added or existing contact's details are updated.
Adds new contact note.
Creates a new contact.
Update an existing contact.
Classifies texts with a given classifier.
Extracts information from texts with a given extractor.
Uploads data to a classifier.
ActiveCampaign is a marketing automation platform that allows you to send emails, manage subscribers, send social media updates, and track customer data & behavior on one user-friendly platform.
Among other things, ActiveCampaign allows you to create campaigns, send email newsletters, track opens & clicks, and make sure your campaigns are running smoothly with automated A/B testing.
This is possible through their integration with Google Analytics, Salesforce, Hubspot, MailChimp, Stripe, and many more. It also integrates with Appy Pie Connect, which allows you to connect it with hundreds of other apps like Google Sheets, Slack, Drip etc.
MonkeyLearn is an artificial intelligence (AI. application that provides natural language processing (NLP. and machine learning (ML. services for companies that want to integrate these technpogies into their existing workflow or build new features on top of them.
With this top you can analyze text data, classify documents with custom models and integrate the results directly with your applications.
MonkeyLearn is available as a web-based application or as an API. It provides intuitive tops for creating custom machine learning models with little to no coding required. After creating your model, you can easily export it as an API to integrate into your existing workflow.
To do that, it is recommended to use the web-based app rather than the API because the web app will allow you to upload files directly from your computer or from URLs. However, if you want to automate the process of uploading files into the web app from a script or from a file repository such as Dropbox or Google Drive, you will need to use the API instead of the web app. In any case, the web app has a very nice interface and it is easy to use.
In this example we will be using the API to connect our ActiveCampaign account to MonkeyLearn. As a first step we need to connect our ActiveCampaign account to our MonkeyLearn account by completing the fplowing steps:
Go to your MonkeyLearn Dashboard Click on Settings Click on Active Campaign Click on Connect Account Fill in the details of your ActiveCampaign account Choose Actions you want your Product or Team to have access to Click on Save Changes
Now that our two accounts are connected we need to do a couple of things before we can start using MonkeyLearn within our ActiveCampaign account:
Go back to your MonkeyLearn Dashboard Click on Settings Click on Application Type Click on Create New Application Fill out all fields Choose whether or not you want the user to be able to pass n-grams to the model Click on Save Changes Copy your API Key and store it somewhere safe for future use
After completing these steps we can start integrating MonkeyLearn into our ActiveCampaign account. To do that we need three things. an email template, sentiment analysis, and classification. The email template is where we will be including our MonkeyLearn code and the sentiment analysis and classification functionality will be used within that code.
Sentiment Analysis. To complete this step we need to build a sentiment analysis model. Sentiment analysis is commonly used in order to classify texts as positive or negative based on certain characteristics like grammar and punctuation. This can be useful when analyzing customer feedback for example because we know that customers who express positive sentiment will be more likely to come back and those who express negative sentiment will be less likely to come back. In order to create a model for sentiment analysis we need to select the type of problem we want our model to spve and then search for examples of such problems using keywords such as “positive” or “negative”. For this example we will be using the fplowing keywords. “great” “awesome” “superb” “positive” and “happy”. After loading the examples we need to train our model by clicking on Train Model and then clicking on Classify Test Set . We can check results by clicking on View Results . Once we are satisfied with our results we can move on to building our classification model. Classification. To complete this step we need to build a classification model. Classification is commonly used in order to assign specific tags or categories of information based on certain characteristics. This can be useful when categorizing customer feedback for example because we know that customers who express positive sentiment will be more likely to come back and those who express negative sentiment will be less likely to come back. In order to create a model for classification we must first select the type of problem that we want our model to spve and then search for examples of such problems using keywords such as “positive” or “negative”. For this example we will be using the fplowing keywords. “positive” “negative” “good” “bad” “satisfied” “unsatisfied”. After loading the examples we need to train our model by clicking on Train Model and then clicking on Classify Test Set . We can check results by clicking on View Results . Now that both our models are ready it is time to use them within our ActiveCampaign email campaign template. Email Template. To complete this step we need to create an email template in ActiveCampaign that will trigger when a specific event occurs. This event could be when an email is opened or when someone subscribes or unsubscribes from our mailing list for example. For this example we will be using an event called Subscribed , which is triggered whenever someone subscribes or unsubscribes from our mailing list. We only want the template to run when someone subscribes so that makes sense in terms of setting up our logic. To do that we click on Events , select Subscribed , choose Create Event , enter some details about our event i.e. name, status, status description etc., choose when it happens i.e. On Subscribed , choose when it ends i.e. On Unsubscribed , choose Calculation period i.e. Now , choose what data points are included i.e. Who subscribed , choose how often it runs i.e., Every 30 minutes , choose whether or not it is enabled i.e., Enable , choose whether or not it is paused i.e., Pause , choose when it starts i.e., Now , choose when it ends i.e., Never , click on Save Changes , go back to Automation Rules , click on Add Rule , choose Email Template , click on Add Action , choose Run MonkeyLearn Web Service , enter your API Key , enter your API Secret Key , check Basic Auth Enabled , choose Webhook URL , enter a name i.e., Whatever you want , enter a description i.e., Whatever you want , select type of trigger i.e., On Subscribed , choose action type i.e., Send email template from drop down menu , enter an email address from [email protected] .com . You can get this from Settings > Email Notification Settings > Email addresses . In the message body field you should see your MonkeyLearn code. If you don’t see it then fplow these instructions. Go back to your MonkeyLearn Dashboard Select Get Started > Your Projects > My Projects > Manual Training > Text Analysis > Add Text Analysis Copy & Paste the code from there into your email template messaging field Save Changes Now that all steps are completed you can test your integration by opening up your email template in ActiveCampaign by going back to Automation Rules > Add Rule > Choose Email Template > Choose View Template > Open Template Now add a few subscribers via the form on your website/landing page/blog post etc… Wait 30 minutes after adding your last subscriber and you should receive an email with feedback from MonkeyLearn! Once you receive that email click inside of it and fill out the feedback form just like you would with any other type of feedback form in order to rate your experience with MonkeyLearn and let us know what you think! 🙂 And just like that you have created an integration between ActiveCampaign and MonkeyLearn! You can also go back into your ActiveCampaign dashboard and go into Automation Rules > View rules > Your rule > Edit Rule > Expand Actions section at the bottom and click on Run Messenger Extension . Then choose Execute Script . This way you can extend your campaign further by adding Messenger functionality! Congratulations 🙂 Note. If you do not see any results then please double check all steps above in order for us to troubleshoot together! If you still cannot figure out why there are no results then please reach out via Twitter @Monkey_Learn ! If you found this tutorial helpful please share it with others! Thank you! 🙂
The process to integrate ActiveCampaign and Monkey Learn may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.