Product feed for Meta Ads

#9

1. 01

   Why does it matter?

   A full picture of marketing results is key to judging what works and finding areas to strengthen.

   Without a single source of truth each platform reports its own result and real product performance stays hidden.

2. 02

   How to check if the problem exists?

   If you look at product data from your feed, GA4, Google Ads, Meta Ads and your store separately, in different dashboards, the problem exists.

   Also compare revenue and orders in GA4 with your store engine. A gap above 15% means segmentation should rely on store data.

3. 03

   How to use the feed in your ad account?

   Data Octopus joins all sources on a common key — the product or variant ID. In the product performance view you analyse impressions, clicks, cost, revenue and ROAS from several channels at once, by product, brand or category.

   Insights flow back into the feed as labels — e.g. products strong in one channel and weak in another — and steer campaigns right away.

4. 04

   How to measure results?

   The result: visible gaps between ad-platform metrics and between GA4 and your store — and budget decisions based on one consistent data source.

#1

1. 01

   Why does it matter?

   In many stores, products that sell well in Google Ads get little exposure in Meta Ads — or the other way round. The two platforms should support each other: results in one prove potential in the other.

   Without shared data, both keep skipping products with real potential.

2. 02

   How to check if the problem exists?

   Compare product sales in Google Ads or GA4 with impressions in Meta Ads. If dozens of products sell well above average in one channel but get impressions well below average in the other, the problem exists.

   Also check the reverse: high exposure in Meta Ads, low sales in Google Ads.

3. 03

   How to use the feed in your ad account?

   Data Octopus writes these products to a custom label in the feed. Create a PMAX, Shopping or catalogue campaign targeting only that label and exclude it from other campaigns so products don't compete with themselves.

   A separate campaign gives them their own budget and bid strategy — full control over exposure.

4. 04

   How to measure results?

   The key metric is a falling number of products in the label: it means they started selling in the second platform and left the segment. Check it in the Products tab of your ad account.

#3 / 4

1. 01

   Why does it matter?

   Ads should respond to market trends as fast as possible. The sooner your strategy reacts to rising sales, the more you get out of them.

   Spotting declines early lets you stop the trend and stop wasting budget on products whose performance has dropped.

2. 02

   How to check if the problem exists?

   Check how many products changed their order count by at least +30% or −30% in the last 30 days. If it's dozens of products, they're worth separating.

   For declines, also review price versus competitors, availability (including popular sizes and colours), delivery time and cost, and ended promotions or campaign changes.

3. 03

   How to use the feed in your ad account?

   Data Octopus writes rising and falling products to separate feed labels, refreshed daily. Send each label to its own campaign and exclude it from the others.

   Add budget to rising products every 1–2 days while returns are good. Give falling products their own budget and bid strategy so the platform notices them again — unless price, stock or an ended promotion is the cause.

4. 04

   How to measure results?

   Measure growth in traffic, revenue and units sold for products in the labels. Review results weekly — it gives a clearer picture than day by day.

#8

1. 01

   Why does it matter?

   Customers who buy often and spend a lot drive high ROAS and campaign revenue.

   Your ads should reach them first — to keep them in your store and away from competitors.

2. 02

   How to check if the problem exists?

   Connect Data Octopus to your store engine. Customers are split automatically into RFM segments (how recently, how often and how much they buy).

   Pick the 2–3 most valuable segments — highest total revenue, average order value and order count.

3. 03

   How to use the feed in your ad account?

   For each segment Data Octopus builds a Customer Match list behind a protected link, refreshed automatically. Upload it to Google Ads or Meta Ads — review takes up to 24 hours.

   Use the list as an audience signal in product campaigns, for direct targeting (e.g. Demand Gen with ad groups by category or brand) or as a lookalike seed.

4. 04

   How to measure results?

   Track revenue and ROAS of campaigns using the list, and list size in Data Octopus and your ad account. Fewer customers in at-risk segments means they're becoming active again.