How the Buyer Journey Really Works in Ecommerce Google Ads

One of the biggest misunderstandings around Google Ads is the assumption that people are either ready to buy or they’re not, and that advertising success is simply about catching them at the right moment.

In reality, ecommerce buying decisions are rarely that immediate.

Most people move through a process of discovery, comparison and reassurance before they ever reach the checkout, and Google Ads performs best when it is set up to reflect that behaviour rather than ignore it.

Google Ads Learns From Behaviour Over Time

Google’s advertising system does not respond to intent in isolation. It responds to patterns.

Those patterns are formed through repeated searches, return visits, engagement with listings, and eventual conversions that may happen days or weeks after the first interaction.

When an account is given enough stability to learn properly, Google starts to recognise which products attract meaningful attention, which search terms lead to considered decisions, and which users are more likely to convert later rather than immediately.

Frequent changes to budgets, bidding strategies or structure interrupt that learning process and make performance harder to interpret.

Visibility Plays a Role Before the Sale

Not every search is a buying search.

Early searches are often about understanding what’s available, how products differ, and whether the price point feels right. Later searches tend to become more specific as confidence builds.

A well-structured Google Ads account allows both stages to exist without forcing them into the same outcome.

Visibility at the early stage contributes to familiarity, and familiarity plays a significant role in which brand a buyer returns to when they are ready to act.

This is particularly relevant in ecommerce, where choice is abundant and trust takes time to form.

Performance Max Reflects the Signals It Receives

Performance Max is often described as unpredictable, but in practice it is highly dependent on the quality and consistency of the signals feeding into it.

Product data, conversion tracking, pricing accuracy and availability all influence how the system prioritises spend.

When Performance Max favours certain products or categories, it is usually responding to accumulated behavioural data rather than making arbitrary decisions.

Treating that behaviour as insight rather than error allows for more informed optimisation, particularly at feed level.

Why Patience Matters More Than People Expect

Delayed conversions are a normal part of ecommerce behaviour.

People research, leave, come back, compare again and then decide, especially when price, trust or suitability matters.

Judging campaign performance only on immediate return overlooks this reality and often leads to premature changes that undermine longer-term results.

Allowing campaigns time to stabilise gives Google the opportunity to distinguish between short-term fluctuation and genuine performance trends.

Structural Issues That Commonly Limit Performance

Certain issues appear repeatedly in ecommerce Google Ads accounts and tend to reduce clarity rather than improve results:

• budgets adjusted too frequently to allow learning to settle
• multiple changes made at once, making impact difficult to measure
• conversion tracking that does not accurately reflect revenue
• product feeds written for internal use rather than search behaviour
• limited segmentation between products with very different commercial value

These issues don’t always cause immediate failure, but they do make performance less predictable and scaling more difficult.

Alignment Is What Creates Stability

Strong ecommerce Google Ads performance comes from alignment between how people search, how products are presented, how the website supports decision-making, and how success is measured.

When those elements work together, optimisation becomes calmer, data becomes easier to interpret, and growth becomes more sustainable.

My Last Word

Google Ads does not work because people are pushed into buying decisions.

It works because it supports the way people already make them.

When accounts are built around that understanding, performance improves as a natural outcome rather than something that has to be forced.