Connect Data from Mailchimp to Qlik

You can get your MailChimp data into Qlik to make more informed business decisions. This simple and quick guide gives you easy instructions on how you can extract your data from MailChimp and then analyze it in Qlik. Our MailChimp to Qlik connector allows you to access your MailChimp data so you can easily manage various media objects, view metadata, and comments, and get reliable insights and metrics, such as reach, impressions, follower-like ratio, and likes. Integrate your MailChimp with Qlik to turn your MailChimp data into actionable insights.

Mailchimp

MailChimp provides reliable marketing automation as well as email marketing services for e-commerce businesses. It is an effective cloud-based email marketing solution, which allows you to design and send marketing emails to your customers.

Note that MailChimp's integrations and unique features allow users to send marketing emails, automated messages, and other targeted campaigns. These important features enable MailChimp's users to deploy unique and flexible designs for brands of different sizes, automation for most online sellers, and sophisticated analytics to scale.

Qlik

Qlik is a business intelligence platform that provides simple end-to-end data management as well as real-time artificial intelligence analytics. Qlik is great as it has a number of powerful tools for Facebook Ads data, such as Qlik Sense and Qlik View.

Qlick’s features also include embedded data analytics and developer and high-quality data integration platforms. You can use Qlick to combine all your Facebook Ads data, create custom applications, and share your business insights easily with your different teams on any device.

Extracting data

Before loading your data into Qlik, you will have to prep it first. If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them.

MailChimp's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes. Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. In these cases you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

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Preparing data

Note that MailChimp offers a RESTful API to easily sync campaign information and other stats. To quickly get all your MailChimp data into the data warehouse of your choice, you may extract the data from MailChimp's servers with the MailChimp API.

Depending on your specific needs, you might want to use webhooks in order to receive streaming updates of MailChimp events (when someone opens and reads an email, an event is generated) as they happen. If that is the case, you will have to build code on your end in order to receive this streaming data.

Loading data

You can easily add data by clicking on Add data within the Data manager. You have the option to select data from various connections, such as a database, or a folder containing your data files.

Note that when you are adding data from any new data source using Connect my data, then a connection to your data source is swiftly created in Connections, which makes it easier and quicker to add more.

You have to take the following steps:

  • Click on Add data
  • Click on Connections
  • Select the connection you want to use.
  • Now select the specific data source that you would like to add data from. For example, for file-based data sources, you can select a data file.
  • Then choose the tables and fields that you want to load.
  • Click on load data and finish in order to load your added data into the app.

If you are using QlikView note that it uses a load script in order to connect to as well as retrieve your data from numerous data sources. When you execute the script, QlikView will identify common fields from the tables to associate your data. You can see the resulting data structure of your data in the document within the table viewer.

You can execute the script simply by clicking on the Reload button. When you execute the script, the Select fields dialog will open. From here you can easily choose the fields that you want to display in list boxes in QlikView. Once your data is loaded into QlikView, it’s stored in the document.

Keeping data up to date

If you've made it this far, congrats! You probably have a written a program or script to extract your data and move it into Qlik.

Now it's time to think about how you will keep this data up-to-date by loading updated or new data. Of course, you can just replicate all your data every time you have updated your records, but that would be extremely manual and time-consuming.

Luckily there is a better way. The key is building your script so that it can sense incremental updates made to the data.

Thankfully, MailChimp’s API results include fields so that you can identify those records which are new since the last update you made (or since the most recent record you have copied). Once you have taken new data into consideration, you can easily set your script either as a continuous loop or cron job to pull down new data as soon as it appears.

And keep in mind that, as with most codes, once you write it, you will need to maintain it. In case MailChimp changes its API, or if the API sends a field containing a data type that your code does not recognize, you might have to change the script.

The Easiest And Fastest Way To Do It

If all this sounds a bit overwhelming, don't worry -- there is an easier way to get this done!

Thankfully, products like Improvado were developed to move data from MailChimp to Qlik automatically. Using Improvado, you can easily combine the most crucial and relevant data from your ad campaign into a dashboard. You can then connect this data to Qlik.