Use Case

Customer Segmentation

 

The essence of customer segmentation is being able to identify different types of customers, then figuring out how to find more prospects with the same profile. Using analytics that combines external and internal signals, companies can develop customer segmentation models around the patterns and trends that comprise each segment.

Customer Experience

Uncover deeper understanding of your customers’ needs

Top-Line Growth

Optimize marketing and manufacturing investment through greater understanding of demand trends

Efficiency Gains

Create and operationalize segmentation models within the same workflow

 

Business Problem

How does your organization approach customer segmentation? Keeping segmentation in view is a part of everything from the messages you convey on your website to the way you allocate production resources. When you have a clear, accurate picture of who buys from you and why, it becomes easier to appeal to like-minded prospects in the same segment.

It’s easy to see which of your products and services your customer segments bought last year, but how do you extrapolate that into the future? Few marketers can successfully navigate customer preferences on intuition and instinct alone, and in an era of abundant customer interaction points, data determines the market winners.

Alteryx Solution

Every customer interaction is the result of data and every interaction generates data. Only through the combination of external and internal signals from multiple sources do patterns and trends emerge and gradually form useful customer segmentation models.

With analytic workflows that run regularly on diverse data streams, companies can take full advantage of information on customer characteristics and historic sales levels. Marketers can then turn patterns in consumption and behavior into data-driven segmentation models, which can then be used to make decisions about products, promotions, messages, and go-to-market strategies.

Alteryx Customer Segmentation Starter Kit provides an easy method for combining customer level transaction data with customer geographic and psychographic data. This data can be blended and segmented based on categories such as average spend and number of store visits. Once the analysis is complete, it can be easily exported into Tableau for visualization and analysis.

 

 

1 – Data Access

Read in transaction data and customer demographic data

2 – Automate Prep & Analytics

Automatically segment customers based on spend

3 – Data Connections

Export segment tables for analysis in Tableau

 

Additional Resources

 
 
Customer Journey Analytics
Learn More
 
 
Customer Lifetime Value
Learn More
 
 
Marketing Analytics
Learn More
 
 
Analytics Automation for Customer Intelligence
Learn More
 
 
Starter Kit for Marketing Analytics
Learn More
 
 
Starter Kit for Customer Analytics
 

Recommended Resources

 
ブログ記事
The Value of Data in Marketing
  • 分析の成熟度
  • ビジネスリーダー
  • マーケティング
今すぐ読む
 
お客様事例
BODi Supports Customer Health with Alteryx and Snowflake
BODi’s self-service analytics environment, powered by Snowflake and Alteryx, efficiently delivers meaningful insights to users across the organization.
  • アナリティクスリーダー
  • マーケティング
今すぐ読む
 
お客様事例
データ分析の高速化により、勝利を手中に収めるマクラーレン・レーシング
週末に開催される F1 レースは年間 20 戦以上にも及び、1 レースあたり 1.5TB ものデータが生成されるため、こうした膨大な量のデータの効率的な収集、処理、活用を可能にするソリューションは欠くことのできない存在です。 マクラーレン F1 チームでは、Alteryx Analytics Automation Platform を使用して、サーキット内外で戦略的な意思決定を加速させています。
  • Cloud Products
  • Fanalytics
  • アナリティクスリーダー
今すぐ読む