The Glossary

You stop setting « 2 € max per click ». You give a goal (conversions or value), and the algo adjusts the bid on every search: higher for a ready buyer at 10pm on mobile, lower for a browser on Monday morning. It reads dozens of signals per auction (device, time, audience, history) you cannot process by hand.

Fed with clean conversion data, the algo beats manual bidding on the vast majority of accounts. This is the foundation of Google Ads performance today.

You set a target CPA of 50 €. Google aims for an average of 50 € per acquisition: some cost you 30 €, others 80 €, but the average trends toward your target.

This is the go-to strategy for lead gen and businesses with a controlled cost of acquisition. You steer profitability through cost.

You set a tROAS of 400 %. For every 1 € spent, Google aims for 4 € of revenue. It bids hard on high-value carts and eases off on low-value conversions.

This is the default e-commerce strategy. It optimizes for value, not count: one 500 € sale weighs more than five 20 € sales.

You give a daily budget, Google spends it in full to bring back the most conversions, whatever their unit cost.

Useful in the learning phase (new account, new campaign) to gather data fast, or when your goal is volume: filling a calendar, clearing stock.

Same logic as Maximize Conversions, but the algo optimizes for value, not count. It prefers one 300 € sale over three 40 € sales.

This is the e-commerce starting point before moving to tROAS. You gather value data, then add a profitability target once you have enough.

You put 1,000 € into Google Ads, it generates 4,000 € of revenue: your ROAS is 4 (or 400 %).

The metric that tells you at a glance whether your ads are profitable. Fast, universal, comparable across campaigns.

Ad, landing page and keyword well aligned give a high score, so a cheaper click for the same position. Three parts: ad relevance, expected click-through rate, landing page experience.

A good Quality Score can halve your cost per click. At the same budget, you get more clicks and better positions.

You do not code « if the user is 25-34, bid higher ». You show the algo thousands of past conversions, and it works out on its own which profiles convert, often combinations a human would not have guessed.

This is what powers Smart Bidding, predictive audiences, recommendations. The more clean data you give it, the more precise it gets.

Trained on billions of texts, it learns the regularities of language. You write a prompt, it generates the most likely continuation, word after word. From this mechanism come summary, translation, writing, code.

For a marketer: writing ads at scale, analyzing customer verbatims, sorting search terms, brainstorming angles. A productivity lever, with your judgment still in charge.

The algo serves, sees who converts, adjusts, serves better, watches again. Every reported conversion feeds the loop. Broken tracking or false conversions, and the loop learns the wrong pattern.

This is why reliable tracking is a direct competitive edge: a competitor with better data trains a better algo, and the gap widens on its own over time.

« Save 50 € » converts less than « Do not lose your 50 € discount ». A cart countdown, « only 2 left in stock », a free trial ending: all of it triggers the fear of losing, which drives more than the desire to gain.

Understanding this bias changes how you write an ad or an offer: you frame the message around what the prospect risks missing, not only what they gain.

A crossed-out price of 199 € before the real 99 € makes 99 € look cheap, because 199 € became your anchor. Without the anchor, 99 € might have looked expensive.

Anchoring shapes a pricing page, a quote, a negotiation. Showing the premium offer first anchors high and makes the standard offer look reasonable.

« 12,000 customers », star ratings, known brand logos, « 8 people are viewing this product »: all signals that say « others trusted this, you can too ». The brain takes a shortcut instead of judging alone.

One of the strongest conversion levers on a page. Placed well, next to the action button, social proof removes the last hesitation.

Instead of the browser sending the info to Google (blocked by adblockers, iOS, the end of third-party cookies), your server sends it. You control the data, and it clears most of the barriers.

You recover 10 to 30 % of otherwise lost conversions, the algo learns better, your performance climbs. It has become a direct competitive edge, not just a technical detail.

When a visitor refuses cookies, the tags do not fire normally: they send anonymous, cookieless pings. Google then models the missing conversions statistically.

In Europe (GDPR), this is what lets you stay compliant without losing too much data. Without it, a refusal equals a conversion the algo never sees.

Emails, purchases, on-site behavior, CRM: data you own, against third-party data (cookies from other sites) that is going away. You can load it into Google or Meta to build audiences and feed the algos.

With the end of third-party cookies and tighter privacy, this is the fuel that remains. Advertisers who structure it keep high-performing algos; the others operate with less visibility.