openfoodfoundation / analytics Goto Github PK

We want to understand conversion rates around Split-checkout. There are many ways to achieve this, two have been identified:

1. using page visits

• set a goal of type "page view" -> section Goal is triggered -> when visitors -> visit a given URL; take note of the ID
• set up a trigger, of type All Elements Click and Only Trigger When -> Click Class -> contains -> button primary (this is can be viewed when using the browser page inspector of the /checkout/summary page)
• set up a tag, to: i) trigger the goal with ID (noted above); ii) select the trigger set above

2. using events

• Similar as above, but the Goal should be of type "send an event" -> section Goal is triggered -> when visitors -> send an event

ATM, not sure how to make option 2) work correctly, so, proceeding with 1).

What is the question we want to answer?

Does anyone uses the "Mailing list" report in the customer section? The Addresses report contains similar information.

What type of data do we need to answer this question (and how to get it, if known)?

Page views from the respective URLs?

Potential solutions that will solve the problem? [[brainstorming on how to access the data, using Matomo, Metabase, other]

Matomo: comparing the following:

Goal (page view) with

• a funnel Reports page / Mailing list report

And a second goal

• a funnel Reports page / Addresses report

Additional context

https://openfoodnetwork.slack.com/archives/C012LE8LLDS/p1680705866453549

What is the question we want to answer?

What are the actions that are performed the most, as admin?
Which admin pages are compromising usability on mobile?

What type of data do we need to answer this question (and how to get it, if known)?

Matomo data:
Which events are triggered more often?
Which pages do admins spend most time on?

Potential solutions that will solve the problem? [[brainstorming on how to access the data, using Matomo, Metabase, other]

To be agreed upon, needs discussion.

Additional context

This came up here.

What is the question we want to answer?

We want to know how often do users experience an item finishing stock, before the order actually is completed.

What type of data do we need to answer this question (and how to get it, if known)?

One approach could be measure how often do users see the out of stock banner.

Potential solutions that will solve the problem? [[brainstorming on how to access the data, using Matomo, Metabase, other]

Proposed solution: Set up an event on Matomo, to observe when the out of stock banner is triggered.

How does an order look like, when an item is of stock, in the DB? Maybe there are some features which allow setting up queries on Metabase?

Additional context

https://openfoodnetwork.slack.com/archives/CG7NJ966B/p1691400145549199?thread_ts=1691374390.628649&cid=CG7NJ966B

We need to compare user interaction between the soon to be released split-checkout and the legacy checkout.

What is the question we want to answer?

1. Ensuring the https://about.openfoodnetwork.org.au/ Matomo dashboard is working. Currently the general tracking code has been removed - how do I fix this? On both ends - Wordpress and Matomo.
2. Connecting Wordpress landing pages (e.g. https://about.openfoodnetwork.org.au/open-food-ecosystem/) to Matomo reporting so page views, etc. can be seen - how can I embed code tag to these pages then connect it back to a Matomo dashboard?

Additional context

OFN France seem to have their Wordpress set up and might be a good reference

There is a drop in the tracked visits within the Matomo-AU website:

This is an artifact caused by the replacement of the general tracking by the tag manager code.

In Progress

Description / Problem

Currently we only started measuring business metrics. But making OFNs impact measurable is equally important, both to support decisions and for fundraising purposes.

Objective

Come up with a first set of KPIs (that are rather simple to measure with Metabase)

KPIs / Queries to be created

Objective 1: Sales Concentration:
Hypothesis: OFN empowers many small food hubs and producers to sell (vs. having a small number of big food hubs and producers)

• KPI 1: Sales Concentration (in €): What´s the share of Top 10(tbd)% food enterprises of overall sales generated per instance, by revenue?
• KPI 2: Sales Concentration (in €): What´s the share of Top 10(tbd)% food enterprises of overall sales generated per instance, by revenue?

Objective 2: Market Access / Connecting Food Enterprises
Empowering small scale producers by connecting them with different points to sell

• KPI 3: AVG # of different Hubs a producers is selling through

Objective 3: Prioritizing sustainable and regenerative agriculture

• KPI 4: Number of sustainable / regenerative agriculture producers
  Proportion of enterprises that use some form of ecological property that to describe their enterprise (would need to gather the tag across different enterprises) [mapping of properties used across different instances]

Problem / Description

As an instance manager / product manager I would like to insights about the selling and purchasing behaviour of our enterprise users and shoppers, i.e. segment food enterprises by their sales frequency and shoppers by their buying frequency.

Buying Frequency
The busing frequency relates to how often a customer buys in a given unit of a lifetime.
This can be tracked in cohorts: Cohorts are groups of buyers or sellers who joined the platform in a specific period, usually a given month. In any cohort you’ll find both buyers and sellers who

- transact once
- some who transact occasionally
- super users who transact consistently

These KPIs will also help to calculate the Customer Lifetime Value (LTV) in the next steps:
What is the is the total value (in €/$|GBP) an average user(shopper) of the platform generates for OFN, over their active life on the platform?

KPIs / Queries to be created

• Buying Frequency: Buyer Segmentation, what % of users buying once, buying occasionally (tbd) and super users who are buying regularly (per given cohort, e.g. among all users that joined in January 2020)

• Sales Frequency: Seller segmentation, what % of shops selling once, selling occasionally (tbd) and super users who are selling regularly

What is the question we want to answer?

We'd like to have estimates on the number visitors for OFN-US website.

What type of data do we need to answer this question (and how to get it, if known)?

Page view numbers can serve as a first approach to access this.

Potential solutions that will solve the problem? [[brainstorming on how to access the data, using Matomo, Metabase, other]

We can set basic tracking using Matomo, by following these steps.

Additional context

The steps above are required since we've removed the general tracking code and installed the tag manager code. After doing so, we need to set up the correct trigger / tag / goal combination to re-enable page views / basic tracking.

We've discussed this here recently and via huddle with @wuchristina

What is the question we want to answer?

Are the buttons "first" and "last" used?

What type of data do we need to answer this question (and how to get it, if known)?

When these buttons are clicked: what is the URL of the current page.

Potential solutions that will solve the problem? [[brainstorming on how to access the data, using Matomo, Metabase, other]

Goals and/or Events, not sure

Additional context

Focus should be on the /products page

This thread.