Google has released a metric that finally puts a number on something B2B SaaS advertisers have argued about for years: how many conversions your tracking setup is actually recovering. The Data Strength Uplift Metric, announced in September 2026, estimates the additional conversions your first-party data infrastructure recovers — the sales and signups that were happening all along but were invisible to Google Ads because of cookie loss, consent gaps, and long cross-device journeys. It reframes measurement work from an abstract "best practice" into a countable figure you can defend in a budget review.
This matters disproportionately for software companies. As ppc.land describes it, the metric “estimates how many additional conversions an advertiser recovers through its first-party data setup.” For a B2B SaaS funnel where a click becomes an MQL, then an SQL, then a closed deal weeks later on another device, the recovered number is usually large — and every recovered conversion is signal that Smart Bidding was previously missing. This post explains what the metric measures, why SaaS sees the biggest gap, and the setup that moves the number.
What the Data Strength Uplift Metric actually measures
The Data Strength Uplift Metric quantifies the conversions your first-party data setup recovers that would otherwise go uncounted. When you implement enhanced conversions, improve tagging, or connect offline data, measured conversions rise — but until now it was impossible to tell how much of that rise was genuinely new performance versus recovering conversions that had always been happening but were unmeasured. The metric isolates that second bucket. It answers the question “how much of my reported conversion volume exists only because my tracking got better?” with a specific figure rather than a hand-wave.
Google introduced it alongside a wider expansion of Data Manager, integrating that tool directly into Google Analytics and Display & Video 360 so first-party connections are easier to manage across products. In Google’s own words, the update is about giving advertisers “more visibility into the impact of improving their measurement infrastructure.” The metric is the visible output of that theme: a scorecard for how complete your data foundation is. It sits on top of the same plumbing covered in our Data Manager API migration guide, so if you have already moved your uploads across, you are positioned to read the metric meaningfully.
The numbers: 14% on average, 20%+ for Demand Gen
Google reports that advertisers who build their data strength with the Google tag gateway see on average a 14% conversion uplift, rising to over 20% for Demand Gen campaigns. Read those as recovered conversions, not incremental sales: they are deals and signups that were already occurring but were not being reported back to Google Ads, so the bidding system could not optimise toward them. A 14% larger conversion dataset is a materially cleaner signal for Smart Bidding, and the effect compounds — better signal begets better bidding begets more of the right clicks.
Be careful with the framing you will see in some coverage. A few write-ups cite a “26% incremental ROAS” figure, but that is a different, broader claim about connecting offline and app data, not the tag-gateway conversion-uplift number. The defensible, Google-stated figures are the 14% average and 20%+ for Demand Gen, confirmed in the Search Engine Journal report on the launch. When you take this metric to a finance conversation, use the conservative, sourced number — a recovered-conversion story that survives scrutiny beats an inflated ROAS claim that does not.
Why B2B SaaS sees the biggest gap
B2B SaaS loses proportionally more conversions to measurement gaps than almost any other category, which is exactly why the Data Strength Uplift Metric tends to read high for software accounts. An e-commerce purchase completes in one session on one device, so a standard tag captures most of it. A SaaS conversion is a chain — demo request today, MQL next week, SQL after a sales call, closed-won a month later — and each hop is a chance for the conversion to detach from the original click. Add consent-mode traffic, ad blockers, and buyers who research on mobile and convert on a work laptop, and the default setup misses a large share of real outcomes.
That structural leak is the same reason we keep returning to offline conversion tracking as the backbone of SaaS measurement. When the deal closes in your CRM weeks after the click, only an offline import reconnects the two — and the Data Strength Uplift Metric now quantifies what that reconnection is worth. If you have not built the pipeline described in our offline conversion stack for B2B SaaS, expect a low uplift figure and, more importantly, a Smart Bidding system optimising on a fraction of your true conversions. The metric makes that invisible cost visible for the first time.
The setup that moves the number
Four foundations drive the Data Strength Uplift figure, and each closes a specific leak. First, enhanced conversions for leads recover hashed first-party identifiers so a conversion still ties back to the click when cookies fail. Second, the Google tag gateway or server-side tagging keeps your tags firing under browser restrictions that break client-side tracking. Third, Consent Mode v2 lets Google model the conversions lost to consent refusals rather than dropping them entirely. Fourth, offline conversion imports feed CRM stages back into Google Ads through Data Manager.
Treat these as a stack, not a menu — each one raises the metric because each recovers a different slice of lost signal, and the gains are additive. If you run consent-mode traffic in the EU or UK, the pairing of consent handling and server-side delivery is where most SaaS accounts find the largest recovery; our guides on Consent Mode v2 and enhanced conversions and server-side tracking with sGTM cover the implementation. Work the stack top to bottom, re-check the metric after each addition, and you get a clean read on which layer recovered the most.
How to read the metric without over-reacting
The Data Strength Uplift Metric is a diagnostic, not a bidding lever — do not change targets in response to it. Its job is to tell you how much of your conversion signal is now real that used to be missing. A high number means Smart Bidding is optimising on a fuller, more accurate dataset, so bidding improves on its own without any manual intervention. A low number means you have unrecovered conversions and the algorithm is flying with incomplete data, so the correct response is infrastructure work — close the tracking gaps — not a target CPA adjustment.
The trap to avoid is reading a jump in the metric as a jump in demand. Recovered conversions are not new customers; they are customers you already had, now correctly attributed. If you see the number climb after connecting offline data, resist the urge to declare a performance win and raise budgets on the strength of it. What actually improved is the trustworthiness of your reported CPA and ROAS. That is valuable precisely because it lets you make budget decisions on real numbers — a theme we develop in why B2B SaaS CAC keeps rising, where measurement gaps routinely make CAC look worse than it is.
What B2B SaaS teams should do this quarter
Start by finding the metric in your account and treating its current value as a baseline for how complete your tracking is. If it is low or the underlying data connections are missing, prioritise the four foundations above over any campaign-level optimisation — a broken measurement layer caps the return on every other change you could make, because Smart Bidding can only optimise toward what it can see. There is no point tuning bids on a dataset that is missing a fifth of your conversions.
Once the stack is in place, use the recovered-conversion figure as the number you bring to finance and leadership. It converts the historically fuzzy case for measurement investment into a concrete claim: “this setup is recovering X conversions a month that we were previously blind to, and Smart Bidding is now optimising toward them.” That is a far stronger argument for engineering time on tracking than any best-practice checklist. Pair the metric with a clean offline-import pipeline and honest attribution, and you turn Google’s new visibility into a durable advantage — cheaper, more accurate bidding built on a conversion dataset your competitors are still leaking.