Expanly and your existing tools
Already using Google Ads, a feed tool, or a profit tracker? Good. Here's the layer that connects them to your business strategy.
Feed management tools
Feed management tools like Channable solve an infrastructure problem: getting your product data formatted, cleaned, and distributed to advertising channels. They handle thousands of channel templates, attribute mapping, and feed rules. If your feed data is messy, fix that first.
Expanly is not a feed tool. We don’t format data or distribute feeds. We assume the feed is already in good shape, and add strategic intelligence on top of it.
A feed tool can create custom labels based on any attribute in your feed. That works for simple, single-dimension rules. Where it gets difficult is combining multiple business dimensions into one prioritization logic: margin above 40%, stock cover over 30 days, rising demand, return rate under 15%, and part of a strategic category push. Building that in a feed tool is technically possible with enough rules, but there’s no way to validate whether those rules are actually driving better business outcomes over time.
Several Expanly customers use a feed management tool for data quality and Expanly for product prioritization. The two work together without conflict.
They format. We prioritise.
Profit-based PPC tools (POAS)
Profit-based PPC tools solve a real problem. Ad platforms optimize for revenue by default, but retailers care about profit. These tools calculate profit per order, feed that data into Google and Meta, and switch the optimization target from ROAS to POAS (Profit on Ad Spend).
That’s valuable. Knowing which products are profitable per ad euro is better than optimizing blind.
But profit is one dimension. A product can be highly profitable and still be the wrong product to push: it might be almost out of stock, or it might be in a category the business is deprioritizing, or it might have a 35% return rate that wipes out the margin. A new collection launch might have lower short-term POAS but is strategically important for the next six months.
Real product strategy balances multiple factors at once: margin, inventory, returns, seasonality, category goals, strategic launches. Profit-based tools are built around one metric and expanding from there. Expanly is built from the ground up to combine all of these into one prioritization model.
Some Expanly customers use a profit tracking tool alongside Expanly. The profit data feeds into Expanly as one input among many, and Expanly turns the full picture into daily prioritization signals for ad platforms.
They optimise bids. We set priorities.
Google Performance Max on its own
Even the best PPC specialist hits a ceiling with native tools alone. PMax optimizes based on what Google can see: clicks, conversions, revenue. It cannot see your margins. It doesn’t know your stock levels. It has no idea which categories are strategic priorities this quarter, or which products have a 40% return rate.
The result: Google allocates budget brilliantly for Google’s goals. Whether that aligns with your business goals is left to chance.
This is not a PMax problem. PMax is a powerful machine. The problem is that nobody is telling it what matters to your business. Expanly feeds that context into PMax through custom labels in Google Merchant Center, so the algorithm optimizes within your strategic framework instead of operating blind.
Google optimises. You decide what it optimises for.
Business intelligence and analytics tools
BI and analytics tools for e-commerce give you visibility into what happened and why. They combine data from multiple sources, build dashboards, and surface patterns: which channels drive profitable growth, where spend is inefficient, how product categories perform over time.
Good analytics makes you smarter. It helps you spot problems and opportunities. What it doesn’t do is act on those insights inside your ad platforms.
A BI tool might show you that a specific category drives strong long-term customer value, or that a product line has declining margins. That’s an insight. The question is: does that insight actually change where your ad budget goes tomorrow? In most setups, it doesn’t. Someone has to manually translate the insight into campaign changes, and that translation often gets lost or delayed.
Expanly closes that gap. Insights from your analytics become rules in Expanly. Those rules become daily priority signals that flow into Google and Meta. The conclusion reaches the ad platform, automatically.
They analyse. We execute.
One stack, not either/or
Expanly works with whatever you already have. Some customers use it alongside a feed tool and a profit tracker. Others connect it directly to their product feed, nothing else required. The best-performing setups tend to combine clean feed infrastructure with Expanly as the strategic layer, but the starting point is flexible.
Each layer does what it's built for. The feed tool keeps your data clean. Your analytics tells you what's working. Expanly makes sure your commercial priorities reach the ad platforms every day. And the ad platforms do what they're good at: spending your budget. Now on the right products.
Scroll to see more →
| Category | What they do well | What Expanly adds | How they coexist |
|---|---|---|---|
| Feed management | Formats and distributes product data to channels | Adds strategic prioritization on top of clean feeds | They format. We prioritise. |
| Profit-based PPC | Switches optimization from revenue to profit | Balances margin with stock, returns, seasonality, and strategy | They optimise bids. We set priorities. |
| Google PMax (native) | Optimizes campaigns based on platform signals | Feeds business context (margins, stock, strategy) into PMax through custom labels | PMax still runs. Now it works on the right products. |
| BI & analytics | Shows what happened and why | Makes sure conclusions reach ad platforms daily | They analyse. We execute. |
Already have your stack in place?
Add Expanly in 30 minutes. No engineering resources required. Your feed tool, your Google Ads account, your GA4 setup stay exactly as they are. Most teams see the first impact within two weeks.