Your customers interact and engage with your brand in a wide variety of ways, which means marketing professionals have access to more sources of insight about their customers than ever before. But for many, marketing activities are a rear-view mirror activity. What if you could put your customer data to work to capitalize on opportunities when they are still in front of you – and predict outcomes instead of just reporting information?
Alteryx allows you to unify customer data from all channels and systems in a single analytic workflow, where you can easily enrich it with integrated demographic, firmographic, segmentation, and geo-spatial data to discover the preferences of your top customers. Plus, Alteryx allows line-of-business analysts to create sophisticated analytic applications and publish them to a public or private cloud platform, giving senior executives and field personnel the insight to make critical business decisions and measure improvements in sales, retention, and customer loyalty.
Powerful data mining and predictive analytics tools allow you to:
- Understand the demographic and psychographic attributes of existing customers so you can target them more effectively
- Create hyper-local marketing strategies and messages that target prospects with similar attributes as existing customers
- Measure the effectiveness of social media, loyalty cards, community, and local marketing investments based on how they are delivering sales
Related Info
- Learn how Alteryx analytic applications for Customer Analytics can:
- Exchange and enrich data with Salesforce.com
- Predict the likelihood of high-value customers to churn
- Download the white paper: A Buyer’s Guide to Customer Analytics
- Download the solution brief: What is the True Value of a Facebook “Like"?
- Read our case studies to see how Alteryx provides customer insight:
On-Demand Webinars
- Finding Value from Marketing Analytics, featuring Forrester Research
- Hear Customers Speak through their Data, presented by Direct Marketing News
- Alteryx Analytics Educational Series: Predicting Customer Behavior
