After managing over $350 million in Google Ads spend across hundreds of accounts, I can tell you that bidding strategy selection is still the single most debated — and most consequential — decision you'll make in a Search campaign. A common question in the r/PPC community right now is whether practitioners should go straight to Max Conversion Value for ecommerce, or if there are still legitimate reasons to lean on tROAS, Max Conversions, or even manual CPC in 2026. The honest answer is: it depends on your data quality, your margin structure, and how much trust you're willing to extend to Google's auction-time algorithms. Let me break down exactly what's working, what's not, and how to think about each scenario.
Google's Smart Bidding has come a long way, but it hasn't eliminated the need for strategic thinking — it's just shifted where that thinking needs to happen. The algorithm is no longer your primary lever; your inputs are. Conversion tracking integrity, value rules, seasonality adjustments, and portfolio structure now matter far more than which bidding strategy you pick in isolation. That said, the choice of strategy still creates hard ceilings and floors on what's achievable.
Here's a quick reference of the core strategies and where they sit on the automation spectrum:
| Strategy | Best For | Data Requirement | Control Level |
|---|---|---|---|
| Manual CPC | New accounts, low-volume niches | None required | High |
| Enhanced CPC (eCPC) | Transition phase, testing | Low (<30 conv/mo) | Medium-High |
| Max Conversions | Lead gen, volume building | Medium (30+ conv/mo) | Medium |
| Target CPA | Lead gen with stable CAC targets | Medium-High (50+ conv/mo) | Medium |
| Max Conversion Value | Ecommerce, value-differentiated leads | High (50+ conv/mo with values) | Low-Medium |
| Target ROAS | Mature ecommerce, tight margin control | Very High (100+ conv/mo) | Medium |
As practitioners often discuss in forums like r/PPC, the debate between Max Conversion Value and tROAS for ecommerce is really a debate about when to impose constraints. Max Conversion Value without a target gives Google maximum latitude to chase revenue. tROAS tells Google to chase revenue only at a specific efficiency level.
Starting new campaigns or entering new markets? Max Conversion Value without a ROAS target is almost always the right call. You need Google to gather data across the auction landscape before you impose efficiency guardrails. I typically run unconstrained for the first 4–6 weeks, or until I've accumulated at least 50–80 conversion events with associated values.
It's also worth using Max Conversion Value when you're intentionally in a growth phase and your business can absorb lower initial ROAS in exchange for market share. Think new product launches, seasonal ramp-ups, or competitive land-grabs. The algorithm will find volume you'd never reach under a tight ROAS constraint.
Once you have a stable conversion history — I'd say a minimum of 100 conversions per month at the campaign level — tROAS becomes a powerful efficiency tool. The key is setting your target based on actual business economics, not what you wish the ROAS was. I've inherited accounts where someone set a 900% tROAS on a campaign averaging 400% historical ROAS. The campaign spends nothing. The math has to work.
A practical starting point: take your trailing 30-day actual ROAS, subtract 10–15%, and use that as your initial tROAS target. Then tighten or loosen in 10–15% increments every 2 weeks, watching impression share and conversion volume alongside efficiency metrics.
Lead gen bidding is messier than ecommerce because lead quality is rarely uniform — and Google doesn't know the difference between a garbage lead and a six-figure contract opportunity unless you tell it. This is the core problem that makes default Max Conversions or tCPA strategies underperform for most B2B advertisers.
The single biggest performance unlock I've seen in lead gen accounts over the past two years is importing offline conversion data and switching from tCPA to Max Conversion Value or tROAS. When you can pass back actual deal values — even rough pipeline stage values — the algorithm immediately starts optimizing toward higher-quality traffic.
For a SaaS client we managed last year, we assigned values to three conversion stages:
After 90 days, cost per qualified call dropped 34% while form volume stayed roughly flat. The algorithm learned to avoid the traffic sources that generated form fills but no downstream pipeline.
Not every team has CRM integration set up. If you're optimizing purely on form fills, tCPA is usually better than Max Conversions once you have the volume to support it. Max Conversions without a target has a dangerous tendency to find cheap, low-quality conversions — especially in B2B where geography, company size, and job title dramatically affect lead quality.
Set your tCPA target slightly above your historical average CPL to give the algorithm room to operate. A target set at or below your current CPL essentially asks Google to do better than it already is doing, with no room for exploration. I aim for 110–120% of current CPL as a starting target.
Here's an unpopular opinion: for campaigns generating fewer than 30 conversions per month, Smart Bidding often hurts more than it helps. The models are data-hungry, and in low-volume environments they spend a disproportionate amount of time in exploration mode — paying inflated CPCs to learn things they won't retain.
In these cases, my preference is still Manual CPC with aggressive use of bid adjustments for device, audience, location, and time of day. Yes, it requires more active management. But when you're running a niche B2B product with 15–20 conversions a month, manual control consistently outperforms an underfed algorithm in my experience.
eCPC serves as a useful middle ground. It preserves your base bids while allowing Google to adjust in real-time for high-probability auction signals. I've seen eCPC consistently outperform pure manual in mid-volume accounts (20–50 conversions/month) without the instability that comes from fully automated strategies in the same volume range.
One of the most underutilized tools in the Google Ads arsenal is the portfolio bid strategy. As practitioners often discuss, most accounts are structured with campaign-level bidding — but this fragments your conversion signal unnecessarily.
Portfolio tROAS or tCPA strategies work exceptionally well when:
By pooling conversion data at the portfolio level, you can run Smart Bidding meaningfully on campaigns that would otherwise be too thin to support it independently. I've managed portfolios of 8–12 campaigns where the combined conversion volume hit 200+ per month, even though no single campaign cracked 40. Performance was dramatically more stable than campaign-level bidding.
Counterintuitively, over-segmentation of campaigns is one of the primary reasons Smart Bidding fails for practitioners who feel they've "tried everything." When you've split campaigns by match type, by device, by audience, by day-parting — you've fragmented your conversion signal into pieces that are individually too small to sustain the algorithm. Google's current recommendation to consolidate is annoying to many practitioners but it's mechanically correct. Smart Bidding needs volume. Segmentation destroys volume at the campaign level.
The 2026 approach I recommend: consolidate to broad match + Smart Bidding + strong audience signals at the campaign level, and use ad group structure and negative keywords to maintain relevance without fracturing conversion data.
The frontier of bidding optimization in 2026 isn't which strategy you choose — it's how well you engineer the inputs that feed the algorithm. This is where most practitioners leave significant performance on the table.
Value rules let you adjust the value Google attributes to conversions based on audience segment, device, or location — without needing separate campaigns. For example, if mobile conversions from new users have historically closed at 30% lower rates than desktop conversions from returning customers, you can instruct Google to value them accordingly. The algorithm will then naturally shift toward higher-value traffic without you explicitly bidding it that way.
I've used value rules to adjust conversion values by:
Seasonality adjustments are criminally underused. They're designed for short-duration events (1–7 days) where you expect a significant change in conversion rate — Black Friday, a flash sale, a product launch. Without them, Smart Bidding will initially underspend because it's still modeling "normal" conversion probability, and by the time it catches up, your sale is over.
Apply a seasonality adjustment 12–24 hours before the event. For a typical sale event where conversion rates might lift 40–80%, I set an adjustment in the 40–60% range to give Google a signal without overcorrecting. Remove it as soon as the event ends.
If you've read this far, you know there's no single "best" bidding strategy — there's only the right strategy for your current data quality, business model, and growth stage. Here's how to audit and improve your current setup:
Bidding strategy isn't a set-it-and-forget-it decision in 2026 — it's an ongoing calibration between your business data, your conversion architecture, and the signals you're feeding Google's models. The practitioners who are winning right now aren't necessarily using a different strategy than everyone else. They're just feeding the algorithm better data and giving it appropriate operational room to work.
