Google’s Product Feed Strategy Points To The Future Of Retail Discovery via @sejournal, @brookeosmundson

For years, many advertisers treated product feeds as a channel task tied mainly to Shopping campaigns.

If you were running Shopping ads, feed optimization likely got attention. If you weren’t, it often slipped behind priorities for the PPC campaigns you were running.

Now, that approach is starting to show its age.

Google’s recent Ads Decoded podcast episode suggests that mindset may need to change. Product data was discussed in connection with free listings, AI-powered search experiences, YouTube formats, Lens, virtual try-on, and newer e-commerce surfaces still evolving.

That reflects a much broader role than many advertisers have historically assigned to their feed.

Google appears to be positioning product data as a larger part of how products are discovered across its platforms, not just how Shopping campaigns perform.

Advertisers who still view Merchant Center as a side task may be underestimating how much visibility now starts with product data.

The more interesting question is what that shift tells us about where Google wants retail advertising to go next.

Merchant Center Is Starting To Look Like Retail Infrastructure

What stood out most in the podcast was how broadly Google described the role of Merchant Center data.

Nadja Bissinger, General Product Manager of Retail on YouTube, described Merchant Center feeds as the “backbone that powers organic and ads experiences,” adding that merchants should submit the most robust product data possible to increase discoverability.

That is a wider role than many advertisers have traditionally associated with Merchant Center.

Google said in a 2025 retail insights piece that people shop across Google more than 1 billion times per day. It also highlighted Search, YouTube, Maps, and visual discovery as key parts of modern shopping journeys. That helps explain why reusable product data is becoming more valuable than channel-specific assets alone.

Google also said Google Lens now sees more than 20 billion visual searches per month, and 1 in 4 Lens searches carry commercial intent. That is another signal that structured product data is becoming more important outside traditional Shopping ads.

For years, many brands viewed Merchant Center as a necessary setup for Shopping campaigns. Google now appears to be positioning it as a core input for how products are surfaced across its platforms.

That should change how feed work is prioritized internally.

Feed optimization is no longer just a PPC responsibility. It can influence:

• Organic visibility
• Merchandising strategy
• Creative presentation
• Promotions
• How products appear in newer AI-led experiences.

For larger organizations, that may require closer coordination between paid media, SEO, e-commerce, merchandising, and product teams.

For smaller brands, it may be as simple as giving feed quality the same level of attention already given to ad copy, landing pages, and campaign structure.

Many advertisers still treat feed work as cleanup work. That mindset is becoming expensive as product data plays a larger role in who gets seen across Google.

Why Is Google Pushing Product Data So Hard Right Now?

Google’s direction here makes sense when you look at where its retail products are heading.

The company wants more e-commerce activity to happen across Search, YouTube, Maps, AI experiences, and future agentic tools. To support that expansion, it needs merchant data that is accurate, structured, and easy to reuse across different surfaces (as Google refers to them as).

Google has financial reasons to expand e-commerce activity beyond traditional ad clicks. In their 2025 Q4 Earnings Release, they reported a 17% growth in Google Search, and YouTube revenue across ads and subscriptions over $60 billion.

A strong feed helps Google understand:

• What a product is
• Who it is for
• What makes it different
• Where it is available
• What it costs
• How the product should be presented

That matters even more as retail experiences, paid or organic, become more visual, more personalized, and more automated.

Traditional search ads leaned heavily on keywords, headlines, and landing pages. Newer e-commerce formats can also depend on product images, attributes, ratings, promotions, availability, shipping details, and other feed inputs that help match products to user intent.

Better data can lead to better experiences for users. It can also create more places where merchants can appear across Google’s properties.

Google is building more e-commerce surfaces, and product data is the fuel behind them. Advertisers who ignore that may keep optimizing campaigns while missing the larger shift happening around them.

Is Google Prepping For A More Strategic Shift?

From my perspective, there is a larger strategic shift behind Google’s product data push.

I don’t see this as a routine push for better feeds or cleaner campaign inputs. I see Google working to become more of a growth engine for advertisers, with a role that reaches beyond media buying and campaign delivery.

That expansion is moving into areas that shape business performance, including merchandising, product discovery, pricing visibility, local commerce, measurement, and newer purchase-ready experiences.

Google is not only trying to improve how ads run. It appears to be building a deeper position in how products are surfaced, how demand is created, how buying decisions are influenced, and how performance is measured.

My view is that the more Google becomes embedded across those moments, the more connected it becomes to broader business growth rather than media performance alone.

Why Many Advertisers Are Still Measuring Feed Value Wrong

One reason feed optimization still gets deprioritized is simple: many teams are using an outdated scorecard.

Google cited a 33% conversion uplift for advertisers using Demand Gen with product feeds during the podcast discussion. Even if results vary by account, it is another sign that feed quality is being tied to campaign types beyond classic Shopping ads.

If the main question is whether Shopping ROAS improved last week, it becomes easy to undervalue the broader impact of stronger product data.

That measurement approach came from a time when feeds were more closely tied to Shopping campaigns. Google is now using the same data across a much wider set of retail experiences, including discovery surfaces, visual placements, AI-led results, and other formats that do not fit neatly into one campaign report.

That creates a gap between where feed work adds value and where many teams are looking for it.

A stronger title may improve discoverability. Better imagery can increase engagement in visual placements. Accurate pricing and promotions can improve click appeal. Richer attributes can help Google better understand relevance. Availability data can support local and omnichannel visibility.

Those gains may show up across multiple touchpoints, assisted paths, and blended performance trends rather than one Shopping dashboard.

That is why some advertisers continue to underinvest in feed quality. The value is there, but their reporting model was built for an earlier version of Google.

As Google expands where products can appear, feed optimization deserves to be measured more like a visibility and growth lever, not just a Shopping maintenance task.

One of the more important quotes from the podcast came from Ginny Marvin, Google Ads Liaison, as she wrapped up the episode:

Merchants with the most structured, high quality data foundations will be positioned to win.

Winning will not come from uploading a feed once and forgetting about it for months at a time.

It comes from treating product data as an ongoing optimization just like your existing campaigns.

What Google’s AI Max Focus May Be Signaling About Search

One of the more revealing parts of the podcast was how often Search strategy was discussed through the lens of AI Max for Search, while traditional standard Search campaigns were barely mentioned.

During the episode, Firas Yaghi, Global Product Lead for Retail Solutions, talked about how advertisers should be thinking about different campaign types:

I think the role of each campaign really depends on your high level objective. Whether you’re prioritizing cross channel efficiency, granular control or hybrid approach that balances top line sales with OKRs.

He mentioned a lot around Performance Max, Demand Gen, with a little bit of AI Max for Search.

I would avoid treating that as proof that standard Search is going away. There is still clear value in campaigns built around tighter search control, brand protection, and proven high-intent terms.

At the same time, it’s hard to ignore the direction of Google’s messaging.

When Google talks about growth, expansion, and newer retail opportunities, the conversation increasingly centers on AI-assisted campaign types. We have seen similar signals elsewhere, including Google’s announcement that Dynamic Search Ads will upgrade into AI Max for Search and that AI Max represents the next step for search expansion.

My read is that standard Search remains important, but it is no longer the only story Google wants advertisers thinking about.

The company appears to be steering incremental growth toward campaign types that rely on broader matching, stronger inputs, automation, and first-party signals.

I think that Search strategies built around legacy structures will become less competitive over time. I’m not confident enough yet to say that standard Search campaigns will go away completely in the near future, but the increasing signals around keyword-less technology has me thinking more changes for Search campaigns are bound to happen.

What This Means For Your Campaigns

The bigger risk for PPC managers is assuming the teams responsible for merchandising or product data already understand how much feed quality can affect campaign performance.

In many organizations, merchandising, e-commerce, product, or development teams control what goes into Merchant Center. Their priorities may be centered on inventory, pricing, site operations, or category management, not media efficiency or visibility across Google.

That is where PPC managers can add real value.

If product information is influencing how products appear across paid, organic, and AI-led surfaces, someone needs to connect those decisions to marketing outcomes. PPC managers are often in the best position to do that because they can see changes in impressions, traffic quality, conversion trends, and missed opportunities firsthand.

That may mean bringing examples into weekly meetings, showing where missing attributes are limiting reach, flagging weak imagery, highlighting pricing issues, or sharing results from tests that improved performance.

You may not own the feed, but you can help the business understand why it deserves greater priority and where better inputs can improve campaign results.

Put More Focus On Inputs That Can Scale Performance

Many teams spend valuable time on small bid changes, minor budget moves, or endless rounds of creative tweaks while core product data remains incomplete or outdated.

Those tasks still have value, but the upside is often limited when the underlying product information is weak.

If titles are thin, images are poor, attributes are missing, or product details are outdated, fixing those gaps may create more value than another round of minor account adjustments.

Add Feed Health To Regular Performance Reviews

Most reporting cycles focus on spend, ROAS, CPA, and conversion volume.

Those metrics are important, but they do not always show whether product data is helping or limiting visibility.

Feed health deserves a place in regular reviews. Look at disapprovals, missing fields, image quality, pricing accuracy, promotional coverage, and product-level gaps with the same discipline used for media metrics.

Broaden How You Test For Growth

Many retail accounts still treat Search, Shopping, YouTube, and newer campaign types as separate lanes.

Google’s recent direction suggests those lines are becoming less rigid.

Growth testing should include where products can appear across newer surfaces, how feeds support Demand Gen and AI-led placements, and whether stronger product data can unlock reach that existing campaigns are not capturing today.

Treat Better Product Data As A Competitive Advantage

Some advertisers will wait until these newer placements are fully mature before investing seriously in feed quality.

While that delay may be costly for them, your proactiveness can pay off significantly.

What PPC Professionals Are Saying

Recent LinkedIn discussions suggest many practitioners are viewing feed quality as a larger performance lever.

Comments from the podcast episode have been overall positive and has many marketers agreeing that feed management needs to be routine.

Zhao Hanbo commented:

Really interesting to see how something that used to feel mostly like ad ops plumbing is now becoming core infra for AI commerce.

Sophie Westall had similar sentiments, stating that “feed quality is quickly becoming a core part of overall media strategy, not just a hygiene task.”

In a recent LinkedIn post, Menachem Ani said that by fixing a product feed, “campaigns start working harder without touching a single bid.”

More marketers appear to be focusing less on isolated settings and more on the quality of the data – regardless if they’re running paid campaigns or not.

What Comes Next For Retail Marketers

Some advertisers will hear Google’s renewed focus on product data and assume it mainly matters for brands running Shopping campaigns.

That interpretation misses how much wider the opportunity has become.

Google is quickly expanding how products can show up across paid placements, organic surfaces, visual experiences, and newer AI-led formats. As that happens, feed quality becomes more connected to visibility and performance than many teams have historically assumed.

In many organizations, product data still gets treated as maintenance work. It gets attention when something breaks or when Shopping results decline, then falls back down the priority list.

That approach may be harder to justify going forward.

Product data needs a larger role in planning, testing, and cross-functional discussions because it can influence far more than one campaign type.

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