Product analytics or process monitoring: funnels vs deadlines

What product analytics does

Product analytics tools such as PostHog, Mixpanel and Amplitude collect events from your app or website and turn them into charts. Funnels are their core view of a process. In PostHog a funnel shows where users drop off, within a conversion window you set, and can count steps in sequential, strict or any order. Mixpanel funnels measure conversion through a series of steps within a time window and are available on all plans. Amplitude's funnel analysis shows how users move through a defined path and where they drop off.

These tools can alert too. PostHog alerts work on trends, funnels and SQL insights, with thresholds or anomaly detection, and notify by Slack, Discord, Microsoft Teams or webhook; its documentation even suggests an alert on missing critical events. Mixpanel alerts are on paid plans, with five per project on Growth, by email, Slack or webhook, and include anomaly detection.

What process monitoring does

Process monitoring looks at the single case instead of the aggregate. tiqline links events to one case by an ID, such as an order number, moves the case through the steps you describe and checks each step against its time limit.

When a step passes its deadline, that case is marked as stuck. All stuck cases of one step share one incident, and one alert goes to Slack or email with links to exactly those cases. Someone can open the case, see its timeline and act.

The key differences

• Unit: analytics counts users or sessions. Process monitoring tracks each case on its own.
• Question: a funnel shows the share that converted. tiqline shows the list of cases that are late now.
• Time: a conversion window ends a funnel step for analysis. A time limit in tiqline triggers an alert for that one case.
• Alert: analytics alerts fire when a metric crosses a threshold. tiqline alerts when a deadline passes for a case.
• Typical data: clicks, page views and sign-ups. Orders, fulfillments, refunds and warehouse steps.

Side by side

When product analytics fits

Use product analytics when you want to improve a flow for many users. Why do 40% of visitors leave at checkout? Did the new onboarding raise activation? Which campaign brings users who stay? These are aggregate questions, and funnels, trends and experiments answer them well.

When process monitoring fits

Use process monitoring when every single case matters and someone has to act on it. An order that was paid and not shipped, a refund waiting longer than promised, a ticket that missed its first response: in each case a person should get a message with the case, not a chart that shows conversion dropped by two points.

Using both together

Many teams send the same events to both. The analytics tool shows the long-term picture, for example how long a typical order takes from payment to shipping and how that changes over months. tiqline checks each open order against its time limit today and alerts when one is late.

With the track API you can send the events your backend already produces, such as picked or refunded, with the order number as the case ID. The two tools then look at the same steps from two angles.

Example: conversion is fine, one customer is not

All numbers in this example are made up for illustration. A shop's analytics dashboard shows that 96% of paid orders are fulfilled within two days, a normal week. Inside that 4% are 11 orders with a gift note that were sent to a separate packing table and forgotten.

In tiqline the process has a branch on a property of the paid event: gift orders go to a packing step with a time limit of 12 hours, all others to the normal pick step. On Wednesday the 11 gift orders pass their limit. One Slack message names the step and says 11 cases are waiting, and the email lists them. The funnel never changed enough to trigger an alert.

Setting it up in tiqline

• Send the business events your backend already produces through the track API, or connect Shopify.
• Choose the ID field that links events to a case, for example the order number.
• Describe the steps in the process editor and set a time limit for each step after the first. Add a branch where cases split, for example shipped or cancelled.
• Preview the draft on your real cases before you publish it, so you see which cases would be stuck today.
• Choose the alert channels: a Slack channel through an incoming webhook, up to 20 email addresses, or both.
• Publish. A time limit you change later applies at once, also to cases that are already running, and the change is recorded in the audit log.

Limits of tiqline

tiqline is not an analytics tool. It has no funnels by segment, no retention charts, no experiments and no anomaly detection. It does not explain why a case is stuck. It works with the events it receives from Shopify or the track API and needs an ID to link them to a case. For questions about user behaviour, keep your analytics tool.