Want to learn how to create successful customer analytic dashboards?
We recently presented on “5 Keys to Self-Service Analytics” with our friends at Tableau. The webinar was focused on showing how you can establish a foundation of self-service data blending, and specifically focused on real-life examples of how to use Alteryx workflows to analyze and output Tableau visualizations for:
- Customer Acquisition
- Customer Segmentation
- Customer Sentiment
- Lifetime Customer Value
- Offer responsiveness
In case you missed it (or even if you watched it once already!) you can replay the webinar. I’d suggest downloading the Marketing Starter Kit for Tableau first – it includes all the Alteryx modules and Tableau workbooks we showed during the webinar. Follow along or even try yourself with your own data!
Self-Service Analytics Q&A
At the end of the presentation we had some great audience questions, ranging from file output formats to real-time data updates to predictive analytic functionality. I’ve paraphrased the questions here:
How do Alteryx and Tableau integrate between workflows and visualizations?
The beauty of Tableau and Alteryx together is that Tableau can take the data from Alteryx and create the visualizations. Most people are pulling data together from more than 10 disparate sources, and by using Alteryx you are able to pull that data into a format that makes sense, then push into Tableau Desktop, Tableau Online or Tableau Server where you can explore your data visually. More specifically, there is the file format that Tableau reads as a dashboard and then another file format, TDE, which is what Alteryx outputs. Each time you update the TDE, Tableau draws the underlying data up into the workbook, preserving the visualization but with refreshing the data.
Are data refreshes real time or a batch process?
Alteryx is a run-time-based environment. Once the workflow is run all the new data is going to be written to the TDE file. While this isn’t a live update, many joint users schedule Alteryx to run on a regular basis, using the workflow to update the workbook behind the scenes. This keeps the data fueling the visualizations fresh.
And finally, tell us more about advanced analytics, can I really run these without coding?
We have 40+ predictive analytic tools available based on R, and our team of data scientists is constantly working on new tools. Current tools include AB controls, forest and decision tree models, linear logistic regression, market basket, and neural network tools. There are time series tools for forecasting and predictive group tools. And if you do know how to code you are able to write your own code, then share your tool as macros! And our spatial analytic tools help you geocode large volumes of data, create trade areas, and more. Again, no coding required.
If you watch the webinar and have questions of your own, join our community and get answers from Alteryx users and experts.
