Google Bridges the Gap: Standard Shopping Gains Independent ‘Maximize Conversion Value’ Bidding

In a move that significantly alters the strategic landscape for e-commerce search marketers, Google has begun rolling out its "Maximize Conversion Value" bidding strategy for Standard Shopping campaigns without requiring advertisers to set a mandatory Target Return on Ad Spend (tROAS) constraint.

This update represents a critical shift in Google Ads’ campaign architecture. Historically, value-based automated bidding in Standard Shopping was tethered to a strict tROAS goal. By decoupling these two features, Google is granting Standard Shopping campaigns a degree of algorithmic flexibility previously reserved primarily for Performance Max (PMax) campaigns. For retail advertisers, this change may eliminate the need to run complex "feed-only" Performance Max workarounds, restoring competitive utility to the more transparent and controllable Standard Shopping format.

1. Main Facts: The Decoupling of Value-Based Bidding

The core of this update is a functional change within the bidding settings of Standard Shopping campaigns.

Previously, if an advertiser wanted to optimize a Standard Shopping campaign for total revenue or margin (conversion value) rather than raw conversion volume, the Google Ads platform required them to input a specific Target ROAS percentage. Under that legacy framework, Google’s Smart Bidding algorithm was constrained to only pursue conversions that it predicted would collectively meet or exceed that specified return threshold.

[Legacy Standard Shopping Flow]
Value-Based Bidding -> REQUIRES -> Setting a Target ROAS (tROAS) Constraint

[New Standard Shopping Flow]
Value-Based Bidding -> CAN RUN AS -> Pure "Maximize Conversion Value" (No tROAS required)

With this roll-out, advertisers can now select "Maximize Conversion Value" as a standalone bidding strategy. In this configuration, the algorithm is instructed to spend the campaign’s entire daily budget to generate the maximum possible transaction value (revenue), without being throttled by a strict efficiency floor.

The change was first spotted in the wild by performance marketing specialist Yash Mandlesha, who shared screenshots of the newly available interface options on LinkedIn. The rollout appears to be phased, appearing gradually across global advertiser accounts.

2. Chronology: The Evolution of Google’s Retail Campaign Formats

To understand why this update is being met with significant enthusiasm by the pay-per-click (PPC) community, it is necessary to trace the technological and philosophical evolution of Google’s retail ad products over the past decade.

  2012–2018: Standard Shopping (High Control, Manual/Basic Bidding)
      │
      ▼
  2018–2022: Smart Shopping (High Automation, Black Box, Value-Based Focus)
      │
      ▼
  2021–Present: Performance Max (Multi-channel, Forced Automation)
      │
      ▼
  Current Era: The "Feed-Only PMax" Workaround (Using PMax solely for bidding flexibility)
      │
      ▼
  Present Update: Standalone "Maximize Conversion Value" in Standard Shopping

The Era of Granular Control (2012–2018)

Following the transition of Google Product Search to a commercial model in 2012, Product Listing Ads (PLAs)—which evolved into Standard Shopping—became the cornerstone of e-commerce advertising. Advertisers maintained complete control over search term targeting (via negative keyword lists), bid adjustments by device, audience lists, and geographic locations. Bidding was largely manual or relied on basic automated strategies like Enhanced Cost-Per-Click (eCPC).

The Rise of Smart Shopping and "Black Box" Automation (2018–2022)

In 2018, Google introduced Smart Shopping campaigns. This marked the company’s first major push toward end-to-end automation for retail. Smart Shopping consolidated search, display, YouTube, and Gmail placements into a single campaign type, utilizing machine learning to optimize bids.

Crucially, Smart Shopping relied heavily on value-based bidding. However, it also stripped away advertiser control: search term reports were hidden, negative keywords could not be applied at the campaign level, and bidding control was highly automated.

The Performance Max Hegemony (2021–Present)

In late 2021, Google launched Performance Max (PMax) as the successor to Smart Shopping, eventually forcing the automatic migration of all Smart Shopping campaigns to PMax by mid-2022.

PMax expanded automation further, dynamically generating creative assets and serving ads across Google’s entire ecosystem (Search, Maps, Discover, YouTube, Gmail, Display, and Shopping). While PMax delivered strong performance for many accounts by leveraging Google’s advanced machine-learning models, it introduced a significant pain point for advanced practitioners: a profound lack of transparency and control.

The "Feed-Only" Workaround

In response to the "black box" nature of PMax, sophisticated search marketers developed a popular workaround known as "feed-only PMax." By creating a PMax campaign but intentionally omitting all text, image, and video assets, advertisers forced the campaign to serve ads almost exclusively on the Google Shopping network.

Advertisers utilized this workaround for a specific reason: it allowed them to access Google’s most advanced machine-learning bidding strategies—such as Maximize Conversion Value without a tROAS constraint—on a product-focused feed, without their budget being diverted to low-quality Display or video placements.

The introduction of standalone Maximize Conversion Value bidding to Standard Shopping directly addresses this dynamic, potentially rendering the feed-only PMax workaround obsolete.

3. Supporting Data & Technical Deep Dive: Decoupling the Mechanics

To evaluate the impact of this update, it is useful to examine how bidding mechanics differ across various strategies.

The "Cold Start" and the ROAS Constraint Problem

Historically, when launching a new Standard Shopping campaign, setting an immediate Target ROAS was highly problematic. Machine learning algorithms require historical conversion data to accurately predict which search queries and users are likely to yield high-value purchases.

Under the old system, if an advertiser launched a campaign with a Target ROAS constraint of 500%, but the campaign lacked sufficient historical conversion data, the algorithm would often fail to serve ads. It simply did not have enough statistical confidence to bid on search terms while guaranteeing a 500% return. This often resulted in a "cold start" problem, where campaigns would stall and fail to spend their budgets.

By utilizing "Maximize Conversion Value" without a tROAS constraint, the algorithm is freed from this performance floor. It can aggressively bid on promising traffic to capture high-value conversions, rapidly gathering the conversion data necessary to establish a baseline. Once a stable volume of conversion data is established, the advertiser can choose to introduce a Target ROAS constraint to transition the campaign toward a margin-preservation model.

4. Official Responses and Community Reaction

While Google has historically encouraged advertisers to migrate fully to Performance Max to capture the benefits of cross-channel machine learning, the company has also faced sustained feedback from mid-market agencies and enterprise brands demanding greater transparency.

The quiet introduction of this feature is widely interpreted by the digital marketing community as a concession to those demands.

Writing on LinkedIn, performance marketer Yash Mandlesha, who first documented the update, noted:

"Standard Shopping is getting stronger! Google is rolling out ‘Maximize Conversion Value’ bidding strategy without needing a Target ROAS… This gives more flexibility to Standard Shopping campaigns while preserving the control and transparency many advertisers prefer."

The sentiment was echoed across industry forums and platforms like PPC Chat (a weekly industry discussion group). Industry experts point out that this update validates the continued relevance of Standard Shopping. For years, digital marketers feared that Google would eventually deprecate Standard Shopping entirely to force absolute adoption of Performance Max. By updating Standard Shopping with advanced bidding capabilities, Google has signaled that the format remains a core pillar of its retail offering.

5. Strategic Implications for E-Commerce Advertisers

The decoupling of Maximize Conversion Value bidding from tROAS in Standard Shopping has broad strategic implications for campaign structure, budget allocation, and agency operations.

                                  [Advertiser Goal]
                                          │
                  ┌───────────────────────┴───────────────────────┐
                  ▼                                               ▼
         [Need Max Control]                              [Need Max Reach]
     (Negatives, Search Queries)                     (Cross-channel, YouTube, Maps)
                  │                                               │
                  ▼                                               ▼
      Standard Shopping + MCV                              Performance Max

Simplification of Account Architecture

For many retail accounts, campaign structures have become overly complex due to the use of feed-only PMax campaigns alongside Standard Shopping campaigns. Marketers often maintained both to balance control and automation. With this update, brands can consolidate their efforts. They can run Standard Shopping campaigns with value-based bidding, eliminating the operational overhead of managing "empty" PMax campaigns that require constant monitoring to ensure Google does not auto-generate unwanted text or display assets.

Enhanced Seasonal Performance

During high-velocity retail events—such as Black Friday, Cyber Monday, or seasonal clearance sales—the primary objective of an e-commerce brand often shifts from maintaining a strict ROAS to capturing maximum market share and liquidating inventory.

Under a strict tROAS bidding strategy, campaigns can artificially limit volume during peak shopping hours if average order values fluctuate. By switching to Maximize Conversion Value without a tROAS constraint during peak periods, advertisers can instruct Google’s algorithm to capture every possible dollar of revenue available in the market, maximizing gross merchandise value (GMV) when demand is at its absolute highest.

Improved Control Over High-Margin vs. Low-Margin Products

Many advanced e-commerce advertisers segment their product catalogs into custom label buckets based on profit margin (e.g., "High Margin," "Medium Margin," "Low Margin").

With this update, advertisers can place their high-margin products into a Standard Shopping campaign using standalone Maximize Conversion Value bidding. This allows them to bid aggressively to capture maximum revenue for their most profitable items, while maintaining negative keyword lists to prevent their ads from appearing on generic, low-intent search queries that would otherwise waste ad spend.

The Agency Perspective: Restoring the Value of Professional Management

For digital marketing agencies, this update represents an opportunity to demonstrate sophisticated strategic management. While Performance Max has democratized basic retail advertising for small businesses, it has simultaneously reduced the competitive advantage of professional media buyers who excel at granular optimization.

The ability to combine the algorithmic power of value-based bidding with the precise steering mechanisms of Standard Shopping—such as negative keywords, bid adjustments, and search term isolation—gives agencies a powerful toolkit to drive superior performance for their clients.

Conclusion: A Balanced Ecosystem

Google’s decision to bring standalone Maximize Conversion Value bidding to Standard Shopping campaigns represents a pragmatic compromise between automation and control. By narrowing the feature gap between its legacy and modern campaign types, Google is acknowledging that a one-size-fits-all approach to retail advertising via Performance Max is not suitable for every business model.

For advertisers who require absolute transparency over where their budget is spent and which search terms trigger their product ads, the updated Standard Shopping campaign format is now a far more powerful, flexible, and viable long-term solution.