Paid Search & Display

Google Marketing Platform

More and more of Google’s marketing products & services are integrated in terms of a hierarchy of access, admins and one-click connectors. This includes:

Google Ads, Google Analytics, Google Tag Manager, Looker (Data) Studio & Search Console

It also incorporates Doubleclick and a few other products:

Display & Video 360, Search Ads 360, Campaign Manager, Ad Exchange & BigQuery

That is a lot of enterprise level products all cross connected and talking to each other to deliver an end-to-end solution. Google is getting better at making this process easier and intuitive for small and large business to implement so that there is no excuse for not having GA4, Search Console, YouYube and Google Business linked to Google Ads and for Google Ads to be marketing across the web to users similar to your highest value customers.  

Google Ads

Google Ads is no longer just about buying keywords or targeting specific websites to show relevant Ads. Google’s product integration across its Marketing Platform now combines Automation, Audience Insights and Optimisation powered by Big Data and Artificial Intelligence. Self driving cars may be stealing the headlines but the future is already here when it comes to the machines taking over paid search and display.

There is of course a need for a more nuanced approach that requires a balance between the Human and Machine elements which is what I call “Smart Marketing”.

I aim to:

  • provide consultancy audits and reviews of more mature ad accounts which are run by an internal team or outsourced to an agency

  • help businesses who want to focus on business operations, without the distraction or overhead of a marketing department, with campaign set-up, integration and on-going management & delivery.

Audience Marketing

Audiences have now expanded across every single product, feature and targeting segment that is available on Google Ads. They are simply the 1st, 2nd or 3rd party audience buckets that users get categorised and segmented into as part of implementing tracking. They are powerful because they bleed into everything at every point in the customer journey. Signed-in Google account users divulge 1000’s of data points to Google about who they are, what they are doing and whether they might be interested in your business.

Here are a few places where Google enhances its products with your audiences or with its own rich audience lists:

  • Remarketing Lists

  • In-Market (audiences)

  • Across Search generally

  • RLSA on Search in particular

  • Customer Match on Gmail

  • Custom Affinity or Custom Intent

  • Demographic targeting

  • All Smart bidding algorithms

Audience targeting is also relevant across the whole customer journey:

  1. to re-engage with previous website visitors

  2. to cautiously expand out to new audiences who are similar to your existing users

  3. to more aggressively prospecting to other bucketed audience segments

Automation

In life in general, Automation can be a great thing and in Google Ads, automation now does most of the heavy lifting on our behalf. Campaign set-up, Ad creation and even reporting duties can be semi-automated. Some products are already fully automated beyond providing the raw materials, defining a purpose and setting success criteria (if only life were so simple)!

Should these things be automated?

For some things like Mobile App Campaigns you don’t have a choice and for others if the data quality and volume is available then it should at least be tested. Google introduced some of these automation features to enable small businesses to get up and running quickly with Google Ads with mixed results. Automation can save time and money assuming the quality and quantity of data conforms to the following 3 principles:

  1. tracking and measurement is implemented correctly as bad data “in” gives bad choices “out”

  2. enough good quality website content that Google can crawl to infer its targeting and ad creatives

  3. good site speed and usability to ensure happy customers who convert

With or without automation these things are also a pre-requisite to let the machines do what they do best!

optimisation & machine learning

Machine Learning and Audiences go hand-in-hand because it is the data from Audiences that powers the machine learning. Here are a few places where can you see machine learning in action in Google Ads:

  • Smart Bidding (at auction)

  • Ad Extensions (at auction)

  • Responsive Search Ads (at auction)

  • Universal App Campaigns (and automation)

  • Dynamic Search Ad Campaigns (and automation)

  • Optimised targeting (previously Similar Audiences)

  • Data Driven Attribution (attribution modelling)

At auction this happens in real-time and are continually being refined and tested from data sources not available to the end user from the Google Ads interface.

Manual Bidding

When it comes to bidding and setting Max CPCs, there are a few things that can be manually manipulated in the Google Ads interface such as device, time of day and location. These are all inherently proxy estimations applied universally to all users based on assumptions that are already out of date.

Smart Bidding

Google Ads Smart bidding delivers bid adjustments to provide the highest probability of profit that can factor in not just the keyword but the search query, the persons recent search history, their user profile and how likely your website is to appeal to them. It does all this in real-time for every auction.

“There is no legitimate reason for any Google Ad account to be using Manual Bidding”
— Mark Brownlie

performance marketing in practice

What would all this look packaged up and delivered to you? It would look like optimisation and growth for your business. It would cover the basics like:

  • Account Set-up

  • Campaign structure and analysis

  • Efficient use of budgets

  • Creative Excellence

  • Product testing and experimenting

  • Reporting on business metrics that matter - Improving ROI

  • Telling the machine what to do (and what not to do)

  • Wider Paid Strategy

  • Cross-Channel integration

  • Content Strategy

  • Delivering additional business value through customer insights

Over time, assuming a critical mass of data is achieved, the hands-on element of running the account is reduced in favour of:

“Most often the “strategy” is not the problem. Its Interpretation, implementation and delivery is.”
— I said that