| 4 min read

When To Switch To Smart Shopping

Written by Simon Bateman

Smart shopping has been around for a few years now, but many people still ask the question “should we switch to smart shopping?” to improve performance of their Google accounts.

What is smart shopping?

Like most of Google’s latest products, Smart shopping is almost fully automated, with little available inputs from those that manage it, and runs across most of Google’s networks (very unhelpfully grouped by Google as “cross-network”).

When To Switch To Smart Shopping

This comes with drawbacks, primarily not being able to see what is causing good (or bad) performance, or differentiate brand and non branded traffic/revenue. 

It also makes you unable to draw many insights (i.e. what search terms are converting) to help scale other parts of your Google accounts.

However, there are some huge benefits. Smart shopping campaigns are able to essentially utilise all of Google’s networks in  campaign, providing the ability to cherry pick the most valuable users across them in a single campaign, and potentially capture those users in places you wouldn’t normally advertise. 

It also connects your prospecting and retargeting activity together to be managed more effectively by one single automated bid strategy, to not only serve an ad in the right place, but also at the right time.

An example scenario

  • User A searches on Google and clicks on your smart shopping ad, but does not purchase
  • A few weeks later, User A watches their favourite YouTube channel and watches a video. User A sees your smart shopping ad, but does not click
  • A week later, User A checks their Gmail inbox and see your smart shopping ad
  • User A then searches for your brand, clicks on your ad and makes a purchase

This purchase may not have happened unless you had separate campaigns to retarget YouTube and Gmail.

When should you use smart shopping?

If it’s new, it must be better, so we should switch to smart shopping now, right?

Not so fast… There are a few things that standard shopping provides that can help put you in the best position for smart shopping to succeed.


Before you switch:

> Optimise your feed

Product feeds help Google to know which auctions to serve shopping ads in, and therefore can be optimised towards search terms that drive revenue.

Whilst there is no definitive timeline for this, once you’re happy that you know what search terms drive most of your revenue, you can re-word your titles and descriptions in the feed, and be confident of the signals you’re providing Google once the blindfold goes on.

> Measure brand vs generic mix

Revenue from brand ads is largely a slam dunk. Revenue from generic keywords (i.e. users that are still deciding where to buy) is what drives growth, and ultimately what is most valuable. 

There isn’t currently a way to differentiate brand and generic performance from smart shopping, which makes it almost impossible to measure the incremental value.

By using standard shopping data to see what proportion of traffic, spend, revenue etc comes from generic terms, you can at least try to answer that question in the future.

> Wait for the right moment

Google doesn’t allow smart shopping to be run simultaneously as standard shopping (it just won’t get any delivery), so there isn’t a way to test the incrementality. 

In order to mitigate any short term dip in performance whilst smart shopping gets going, wait until you’re out of sale, or any peaks in demand.

What should I expect from smart shopping?

Typically we see a much lower cost per click, largely due to the fact that it operates in cheaper auctions outside search which drags the cost down.

Similarly, conversion rate also falls because these networks aren’t always as high-intent as search, despite the lower cost.

The main reason smart shopping normally performs better, is because the drop in cost per click surpasses the drop in conversion rate, leading to a cheaper acquisition cost and higher return on ad spend – which ultimately allows you to then scale the channel.

Automation and machine learning are undoubtedly the future, and will help improve account performance, but similar to painting a room, success is determined by good prep work.

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