Harney & Sons

Background

Harney & Sons is a family tea company founded by John Harney in 1983, now run by the second and third generations. It sells hundreds of teas through its own site and subscription program, through retail partners and through distributors around the world.

Its marketing runs on Shopify and Klaviyo, with a well-developed set of flows, a subscription program, post-purchase surveys, a helpdesk and paid media across several platforms.

The Challenge

Mature retention programs hit a different wall than young ones. The flows exist and the data is collected. What’s scarce is the time to connect it, read it and act on it.

For Harney & Sons, that meant three questions:

• Which customer signals actually predict repurchase? Survey, order and support data lived in different places.
• Which numbers should flow decisions rest on? Like most brands with several tools, different dashboards gave different answers about what drove revenue.
• How do you personalize across hundreds of products? Product-level targeting is easy for a few hero SKUs and hard for a full catalog.

What We Did

Connected the stack and delivered an audit in week one

We connected Shopify, Klaviyo, the helpdesk, subscription data and ad platforms into one model, including more than 158 million Klaviyo events. The first full audit landed in week one, covering subscription retention, payment recovery, support operations and testing priorities.

Turned survey responses into support automation

We joined post-purchase survey responses to each customer’s LTV, order and support history. That showed which kinds of feedback predicted lower repurchase.

The findings became an automation: low scores and complaint responses now open a ticket in Klaviyo Help Desk. The service team can follow up while the customer is still reachable, instead of finding out from churn data months later.

Reconciled attribution

We compared email-attributed revenue with Shopify’s own reporting and showed how to adjust for orders that would have happened anyway, such as recurring subscription shipments. Flow decisions now rest on numbers that match the store’s books.

Product-level subscription targeting across the full catalog

We wrote 12 months of per-product purchase history into Klaviyo profiles. That made it possible to find repeat buyers of a specific tea who hadn’t subscribed yet, across the whole catalog rather than only the top sellers, and target them with subscription offers.

Repeat timing, payment recovery and lifecycle flows

• Repeat-gap analysis to time replenishment emails by pack size and set win-back timing from real reorder behavior.
• Payment recovery analysis by decline type, with dunning and retry logic matched to each.
• Lifecycle flows that move customers from first to second to third purchase, plus a win-back for paused subscribers.

Ongoing analytics

A daily digest flags subscription trends, ad anomalies and attribution gaps, so issues surface within days rather than at month-end.

Results

This engagement is about turning an already sophisticated Klaviyo program into faster decisions. The outputs are analyses, automations and reconciled numbers:

Area	What changed
Data	158M+ Klaviyo events joined with order, survey, support and ad data
Customer experience	Survey feedback now opens Help Desk tickets automatically
Attribution	Email revenue reconciled with Shopify’s reporting
Personalization	Product-level subscription targeting across the full catalog
Monitoring	Daily digest surfacing subscription and ad anomalies within days

Results are specific to this client and engagement, not typical or guaranteed outcomes.