Connect Data from Mailchimp to Tableau
You can get your MailChimp data into Tableau 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 Tableau. Our MailChimp to Tableau 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 Tableau to turn your MailChimp data into actionable insights.
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.
Tableau is a business intelligence platform and visualization tool that helps anyone see and better understand their data. People love using Tableau because it allows you to take raw data and turn it into charts, graphs, dashboards and reports that share insights and tell a story.
Before loading your data into Tableau, 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.
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.
If you would like to analyze data in Tableau, you will have to convert it into a format that Tableau can read. You can import data from excel files or text files and PDFs, but the most suitable practice is to create a data warehouse that has all the data, and then to connect your data warehouse to Tableau.
To import your data from an MS Excel file, click on "Microsoft Excel" present under the connect tab. This will open a new dialog box so that you can easily navigate to your Excel file in the machine from which you would like to import your data. Now, click on the file and then click ‘Open.’
In case there is more than one sheet in your MS Excel workbook, all of these workbooks will be automatically imported, and they would be listed as sheets on the left-hand side panel of Tableau. Once you have loaded your data, Tableau offers an option to locally cache your data to expedite queries.
There are almost no restrictions on how you import any type of data into Tableau. Tableau has many options to represent data in various views, applying filters, formatting, drill-downs, creating sets, performing forecasting, and generating trend lines.
If you have used Pivot Tables in MS Excel, then the Tableau report building process will feel quite familiar. You will have to select the columns and rows desired in the resulting data set, and the aggregate functions used in order to populate the data cells.
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 Tableau.
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 Tableau 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 Tableau.