Using Voyado FTP to retrieve Newsletter and Automation data to follow up both revenue attribution but also combining with CTR, CTOR, OR. When integration with Voyado it will open up the possibility to also dive deeper into CLV and customer loyalty

I would love if I could set annotations in a chart. For example when you have had a discount or event. Then when you see this date in the future in the chart you will see the annotation.

Get daily/weekly emails based on reports in the app.

Track page views and sales for bundled products (bundles consist of two or multiple products), to analyze and compare bundled/non-bundled products.

I would love if we could get the weekday in the chart

We would like to be able to have all our KPIs in one place - Dema. It would be great to be able to import data points, either from a website directly (like Zendesk for tickets, CRM subscribers from Voyado etc.) or from an excel sheet that updates continuously.

Now for landing pages we only have the url, we would like to also have page type: home/category/product/whatever that we can set in the tracker page view call. would also be good to have page key field since if you run multiple languages the url is different per language, like “jackets” vs “jackets”, but the page key will be “jackets” for all langs.

Currently, segmentation data is only provided as a CSV file. Customers have to manually upload this to Voyado, which is cumbersome and prone to errors. We will allow to automatically update customers in Voyado with tags based on segments created in Dema.

Make it possible to add customs based on a threshold order value. This is applicable for several countries today.

Cater to those that have a broken financial year.

It’s not possible to add a “positive” return cost, e.g., when a customer pays a return fee

It would be great to be able to follow the customer journey on site. From the total number of users who landed on our site, how many added a product to cart, how many of them proceeded to checkout and how many of them actually fulfilled their purchase/converted. (Same type of report as google analytics purchase journey) In both numbers and percentage.

When looking at conversions and adjusted epRoas (ads) reported from ad platforms in dema we would need to take the consent rate to be able to compare epRoas between countries, same as we do with expected returns by country. To the ad platforms we only send conversions for consented users, and the amount of consented users is very different by country, only 71% in DE and in US there is no consent needed so there we have 100% It could be a fixed config table on country level as a start, and in the future we should probably track consents in the dema tracker. This only applies to metrics marked with (ads) in dema, the normal epRoas does not have this issue as it uses commercetools data, not ad platform.

Enable input of negative customs costs to account for duty drawback. Feature request (Nice to have)

For users that don't consent to tracking and we currently can't track, we are looking into possibility to allow a cookieless solution where we instead use a hash + 24h salt to encrypt customer PII to allow compliant tracking for all visitors.

Would be great to limit guests to certain regions / platforms etc. When working with agencies in specific countries we’d prefer they couldn’t access data for the entire business. When selecting dimensions/ metrics to limit guests to it would be good to have sub categories to have this option.

Being able to share an agent chat with a coworker – and potentially also being able to both add new messages to the chat (if allowed by the one who shared)

Return platform Yayloh has events that Dema could “subscribe to”. This could give more data to returns reporting in Dema, for example Return Reasons.

Description: Currently, the dashboard filtering for text-based dimensions (such as Order Tags) is limited to "is any of", "is none of", "contains", and "does not contain". While these cover basic needs, they lack the precision required for managing structured data. For instance, when using prefixes like saleschannel_, users cannot efficiently isolate groups of tags that share a common starting string without manually selecting every variation or risking "false positives" that might occur with a broad "contains" filter. Key Requirement: Expand the available filtering operators to include: Starts with: To capture tags sharing a common prefix (e.g., saleschannel_). Ends with: To capture tags with common suffixes. Is empty / Is not empty: To identify records where tags are missing or present, regardless of the text value. Matches exactly: To ensure a 1:1 match without including partial strings. Value: This increases the speed and accuracy of segmenting data. It allows users to build dynamic reports that automatically include new tags as long as they follow a defined naming convention. It eliminates manual maintenance of filters and ensures that dashboard views remain scalable as the business's tagging taxonomy grows.