4 Data-Driven Insights To Optimize Your Smart Shopping Campaigns

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Jeff Hennion
Jeff Hennion is an e-commerce and digital marketing specialist rewriting the rules of the client/agency relationship.
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This post was sponsored by Adchieve. The opinions expressed in this article are the sponsor’s own.

Smart Shopping campaigns in Google Ads offer a number of benefits that advertisers find attractive – particularly those trying to manage product promotion at scale.

It’s a format that puts Google’s machine learning to work for you by automating bidding, testing, and ad placement, using your product feed to display ads across the Google Search Network, Google Display Network, YouTube, Gmail, and more.

It can be a helpful assist in simplifying and streamlining campaign management – that is for sure.

But having machine learning do the heavy lifting has its potential downsides, too.

Smart Shopping can be something of a data “black box” for marketers.

How can you use the different types of data available to you to better influence the results of this machine-assisted automation?

Once you better understand the inputs and outputs of that black box, you can tinker with the input more effectively.

In this article, you’ll learn how to do just that.

Read on as we explain how you can use combined insights obtained from different types of data to better match your business objectives, drive the best possible ROI, and really move the needle in product sales.

The Unprecedented Importance Of Data Science

Before you can uncover insights, you must first understand the distinction between different types of data.

The 3 data types that unlock Smart Shopping insights
Google Data
What Google gives back
Conversions, costs, impressions, click-through rates, and ad placement data returned from Google's algorithm — less than before, but still actionable.
Use it to track campaign performance and identify ROAS patterns across products.
Company Data
What you know about yourself
Profit margins, stock levels, customer lifetime value, and internal KPIs. This data is yours — no one else has it, which makes it your most powerful differentiator.
Combine with Google data to calculate true POAS — not just surface-level ROAS.
Competition Data
What's happening in your market
Competitor prices, product ranges, keyword rankings, and market share data — the context that determines whether your campaign is winning or falling behind.
Use it to benchmark pricing, spot gaps in your range, and monitor market share shifts.
The best insights come from combining all three. Any single data source tells you what happened. Combined, they tell you why — and what to do next.

Google Data: Data you get back from Google

Although Google discloses less data than ever, there is still a lot of important information that you can use. Think of conversions, costs, impressions, etc.

Company Data: Company-specific data that indicates which KPIs or factors you focus on

Company data is data that you have yourself. Think of insights into margins, stock data, and all kinds of customer data.

Competition Data: Data about what is happening in your market

The third data source is data about the market in which you are active.

  • Are you ahead or behind your competitors?
  • What are your competitors’ prices and which products do they offer?
  • Which keywords do they rank for and you don’t?

Now let’s make the leap to insights.

4 Examples: How Turning Data To Insights Can Give You A Head Start

4 insights that give Smart Shopping campaigns a real edge
Insight 01
POAS — true campaign profitability
Combine Google cost data with your margin data to see actual profit per product — not just revenue. Set different POAS targets for different SKUs to spend where it matters most.
Insight 02
Cross-sell & upsell patterns
Advertising product A doesn't always mean selling only product A. The Product Advertising Contribution Model reveals what customers actually buy — including higher-margin products B and C.
Insight 03
Price impact on rankings
Cheaper products get more impressions and clicks. But the difference in conversion rate is even greater than the difference in impressions. Price doesn't just affect clicks — it affects whether you win the sale.
Insight 04
Keyword-level visibility
Crawling search term data reveals what's happening inside Smart Shopping at the keyword level — showing the effect of ROAS adjustments, price changes, title updates, and new product additions.

Different types of data are needed to arrive at valuable insights.

Sometimes this concerns insights for which you only need one data source, but we think the best insights can be found when you combine Google, company, and competition data.

The following are some examples of insights that you can now build with Adchieve to optimize your campaigns within Smart Shopping:

  • Understanding campaign profitability (POAS).
  • Insight into cross-sell and upsell patterns.
  • Insight into prices and their importance for your rankings.
  • Insight into keywords in Smart Shopping campaigns.

1. POAS Insights

In our journey to understanding Google’s shopping algorithm, we wondered if ROAS is a good objective. ROAS is just a ratio that says nothing about your profitability.

What is the ideal ROAS where you achieve maximum and healthy profit and turnover? And should that ROAS target be the same for every product in your shopping campaign?

That is why more and more advertisers are now using POAS (Profit On Ad Spent) insights.

Where you previously only managed ROAS revenue, now we can gain automated insights into profit by combining Google data (cost data) with company data (margins).

ROAS vs POAS — why the metric you choose changes everything
ROAS — Return on Ad Spend
Just a revenue ratio
Revenue ÷ Ad Spend. Tells you how much revenue each ad dollar generates — but says nothing about whether that revenue is actually profitable.
Ignores margin differences
A 400% ROAS on a 10% margin product is far less valuable than a 200% ROAS on a 60% margin product. ROAS treats them the same.
One target for all products
Setting the same ROAS target across an entire shopping campaign ignores the profitability gap between high and low margin SKUs.
POAS — Profit on Ad Spend
Profit-first measurement
Profit ÷ Ad Spend. Built by combining Google cost data with your internal margin data — the full picture of what each ad dollar actually earns.
Accounts for margin per product
Different POAS targets per SKU mean you spend more on promoting high-margin products — and less on those that erode profit.
Enables cross-sell & upsell insight
Advertising product A may drive sales of product B or C. POAS frameworks can account for these downstream effects on true profit.
A good ROAS does not necessarily mean a good POAS. Optimising for revenue without knowing your margins is optimising in the dark.

Here’s proof that a good ROAS does not necessarily have to be a good POAS:

A table displaying the prices of various items, organized for easy comparison.

Read more about the operation and benefits of POAS in this Adchieve article, Google Ads: Why choose POAS target over ROAS.

2. Cross-Sell & Upsell Insights

When developing POAS insights, we also realized that advertising on product A does not always have to mean that you also sell product A. It is also possible that in addition to A, you also sell product B or do not sell product A at all, but only product C.

That is why we developed the Product Advertising Contribution Model, where the central message is that the advertisement of product A does not always lead to the sale of (only) product A.

Here’s an illustration of the Product Advertising Contribution Model:

Diagram illustrating the product advertising conversion model, showcasing the stages from awareness to purchase.
Source: Adchieve

This is important when calculating your profit margin.

Product C can have a very different margin than product A, and the upsell to product B may also be interesting from a margin-technical point of view.

3. The Effect Of Your Price On Rankings

Do your prices impact your Google rankings? We wanted to discover whether this claim was fact or fiction, so we started investigating.

For a major retailer in the U.K., we adjusted retail prices for a group of random products over a four-month period. The products fell into one of five price ranges around the benchmark price that Google quotes, and the prices were, for example, 15% cheaper one week and 5% more expensive the next.

We took into account movements within the benchmark itself, and for each product, it was randomly determined in which price range the product would fall that week. You can see the result in the graph below.

Impressions
−15%
to −7.5%
−7.5%
to −1%
−1%
to 1%
1%
to 7.5%
7.5%
to 15%
Price benchmark difference →
Below benchmark (more impressions)
Near benchmark
Above benchmark (fewer impressions)
Conversionrate
−15%
to −7.5%
−7.5%
to −1%
−1%
to 1%
1%
to 7.5%
7.5%
to 15%
Price benchmark difference →
Below benchmark (higher conversion)
Near benchmark
Above benchmark (lower conversion)

We saw a clear tapering effect in impressions. The products in the product group that had the most discount were shown the most often and were the most often clicked through.

Conversely, the products that had increased in price the most were shown the least and clicked the least. Google shows you more when you are cheaper, but the difference in conversion rate is much greater than in impressions. So price matters.

By providing insight into competitors’ prices within Google Shopping, we provide an even more precise picture.

4. Keyword Insights

We recently developed a tool that produces insights within Smart Shopping at the keyword level by structurally and automatically collecting search term data through crawling.

This crawl data helps you understand what is happening within Smart Shopping. You can see the effects at the keyword level of:

  • Adjustments in your ROAS.
  • Changes in your price proposition.
  • The effects of improvements in your product scores.
  • The adjustments of titles.
  • The impact of newly added products on your rankings.

The Luqom Group, the largest online lighting provider in Europe, also uses our feature. With the returned keyword data, they can immediately optimize campaigns or see the effect of adjustments.

The data is also strategically important because it allows them to closely monitor their position in relation to competition (we call this the “market share”). It also taught Luqom which products were popular within Google Shopping and those the webshop did not yet have in its range.

Learn more about the topic in this article: Keyword Insights for Google Smart Shopping is back.

Success Factors For Managing Campaigns Differently

4 preconditions for managing Smart Shopping differently
1
Get clear on your business objectives first.
Do you want to maximise margin — even at the cost of turnover? Or grow market share in a specific segment without sacrificing revenue? Your objective determines which data you need, which structure to use, and what a "good" POAS target actually means for your campaigns.
2
It goes beyond the marketing team.
Margin insight requires finance. Assortment decisions need purchasing or category management. Pricing strategy crosses departments. To win in Google Shopping, PPC managers need to work more with colleagues — and less alone in the platform interface.
3
Be open to experimentation — not just direct action.
Smart Shopping gives you fewer levers than manual campaigns. Success comes from the quality of decisions — ROAS targets, campaign structure, price positioning — not the number of bid adjustments. Experiments won't always produce actionable outcomes, but they always produce new insight.
4
Use the right software to act on insights at scale.
Data-driven advertising automation tools turn insights into action — enabling substantiated ROAS adjustments, revenue and margin forecasting, keyword position tracking, competitor content monitoring, and optimal pricing at the product level.

In addition to Luqom and the large retailer in the United Kingdom, at Adchieve, we have conducted research over the past two years with other leading retailers into the success factors for applying surfing the algorithm.

What we have learned is that four factors are important as preconditions.

Get Clear On Your Business Objectives

This may seem like a clincher, but the practice is more unruly. You want to focus on improving your margin, but can that also be at the expense of your turnover?

Or do you want to grow in a specific market, for example, without losing sight of your turnover/market share?

Knowing your objectives is not only important for clarifying where you want to steer. It also influences which data you need and which structures you can best work with during your campaign.

It Transcends The Marketing Department

Anyone who wants to score in Google in the short or medium term should also think about their range and the prices charged. For assortment-related matters, you need the involvement of the purchasing department or category management.

Do you want to provide insight into the margins of your sales via Google? Then you need the expertise from the financial department.

As a PPC manager or online marketer, you work less in the interface of Google and more with colleagues (from other departments).

Be Open To Experimentation & Learning – Not Just Taking Direct Actions

PPC managers are used to taking a lot of action, for example, by directly adjusting bids and keywords. You can control a lot fewer buttons with Smart Shopping.

Therefore, it is less about the number of actions you perform but more about the quality of those decisions. Which ROAS targets and campaign structure will help you achieve your business objectives?

The above requires that you build up new knowledge by keeping up with developments in the market, and also by experimenting yourself and learning what does and doesn’t work in your situation.

Experiments do not always lead to actionable items, but they do lead to interesting new insights which evoke new considerations – helping you get closer to your objectives.

This also requires commitment and involvement from someone high in the organization. This person knows the business goals, can think and direct cross-departmental actions, and can initiate experiments that are not used or dared lower in the organization.

The bottom line
Smart Shopping's black box isn't a wall. It's an input. The more precisely you feed it — with margins, prices, and cross-sell data — the smarter it gets.
The shift from ROAS to POAS, from single-channel attribution to contribution modelling, and from keyword guessing to keyword visibility — each step moves you from optimising for revenue to optimising for profit. The data is already there. The question is whether you're using it.

Put Everything Into Practice With The Right Software

Finally, you are ready, and there is commitment from someone higher in your organization.

Using data-driven advertising automation software means you can act on your insights and manage your campaigns differently – not just to feed the black box, but in our words, “color the black box.”

What will you have insight into?

Some examples:

  • You can make substantiated changes to the ROAS of your campaign.
  • You can predict the effect of a ROAS adjustment on both your revenue and margin
  • Based on your keyword insights, you can estimate how much room there still is for winning positions on important search terms.
  • You have insight into your own content and how it ranks.
  • You see which content your competitors use (titles and images) and whether they rank better with it. Based on this, you can make substantiated adjustments to your own content.
  • What are your most optimal prices? At which prices do you have the most margin but also rank the maximum within Google? In combination with your cross-sell and upsell insights, and with keyword data, you can come to interesting conclusions.

And finally, how great is it if you can even influence your product range?

Based on the insights that we made available through Adchieve, Luqom expanded their range within one of the labels by 50%.

Is data on top of your mind too? Subscribe to our newsletter and read all about our data scientists’ latest researches and new data-driven insights that we implement in our software on a regular basis. Improve your ads campaigns continuously and subscribe.

Authored by 
Jeff Hennion
From the start of his career, Jeff Hennion has held a simple belief to be true: that building success means building connections – between people, between brands, and between ideas.
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