Customer Centric Analytics

Zeenk leverages Customer Centric Analytics to help brands align the development and delivery of products and services with the most valuable customers.

The Process:

  • Gather your data
  • Identify the most valuable customers
    and sources with Zeenk data science team
  • Refine your products and marketing to optimize profit
Visual of customer centric analytics showing profitable and non-profitable customers.

Gather Data

Visual of Zeenk's customer lifetime value chart. Illustrates our customer level CLV analysis and prediction 3, 6 and 12 months out

Customer Centric Analytics

We have deep data science experience in attribution, incrementality, and customer modeling for measurement and prediction. We use proprietary data models to forecast CLV, contribution profit, and churn probability for customers, products, and channels in various business models, including product purchase, subscriptions, mixed subscriptions and purchases, and lead businesses. All modeling begins with First Party Tracking.

First Party Tracking – App and Web

First party data is crucial for modeling attribution, customer cost, customer value, and other individual customer metrics. Zeenk offers a web pixel for web application tracking, including both server-side and single-page applications. The Zeenk pixel also has an API for mobile device activation and tracking. This tracking allows for identifying the most valuable customers through advertising and cost analysis.

Visual showing how customer centric analytics are presented on Zeenk dashboard and charts
Zeenk Platform Visual


Attribution of revenue to marketing events is challenging especially for companies that have long decision periods or where revenue comes far past a lead. Zeenk offers a range of standard attribution models that can be configured to match your business.

Identify Best Customers


Which customers are on track to make you money, and which ones will lose you money? Leveraging the proprietary calculation of the cost to acquire every one of your customers (CAC), our report shows the distribution of your customers’ ratio of CLV:CAC so you can identify who is profitable, who is not, and who is at “breakeven.” Roll up to the channel level or drill down to the customer-level and get key insights that you can leverage in your marketing campaigns to drive profitability. Learn how to Optimize Against Customer Value Instead of CPA.

Visual of CLV to CAC ratio
Example of chart measuring customer lifetime value by channel

Manage to Lifetime Value

Companies with a delay between registration and checkout can have a wide variation in customer lifetime value. Use Zeenk to get estimates of customer lifetime value (CLV) post registration but before conversion. Use this knowledge to differentiate outreach, or to create segments with different creative strategies to drive more valuable registrations.

Segmentation on Customer Attributes

What characteristics do your highest value customers possess? Our CLV reports give a comprehensive breakdown of the attributes of each of your customers, including their first and last purchased product, advertising channel, location, etc. Utilize this information to refine your audience targeting and attract high-value customers while avoiding those who are less profitable.

Visual of customer data

Refine and Optimize

Improve Retention

Use our customer churn estimates to improve segmentation and targeting for your email and SMS retention strategies. Identify your loyal customers so you can engage them to help build your brand. Offer the customer who may be about to churn offers to get them to repurchase.

Zeenk's Churn probability chart that predict the likelihood a user will remain a customer during specific time periods
Visual of customer shopping online with delivered boxes

Advertising Halo

E-commerce experts already know that impressions designed to drive traffic to their DTC storefront affect sales at the brand level. This halo effect leads to brands seeing increases in purchases on Amazon when they increase their direct to consumer advertising. Zeenk’s platform supports media mix modeling to quantify this halo effect – which is important to take into account when optimizing spend across advertising channels. Read Zeenk’s Halo Study Results on Amazon.

Better Business Decisions with Causal Modeling

Developed in-house over the last decade, Zeenk pairs its Timeline Query Language (TQL) with Zeenk’s open source library, Causmos™, allowing for rapid development, and exploration, of causal models with just a quick change in parameters.

Visual of Zeenk Timeline Language Query process