Make inhouse SEA teams more successful

How can my SEA team focus on high value projects?

Ask your SEA team the following question: “How much will your three most important projects add to our top and/or bottom line?”

Usually, you will not receive a straightforward answer nor a number. This single number per project, however, is not only necessary to prioritize you own ressources, but also to successfully align for shared IT & product develoment ressources

Why is value orientation difficult?

SEA managers are busy people

SEA managers are mostly busy with two activities:

Managing & monitoring the accounts/ campaigns
Coordinating initiatives within marketing or with other departments (mostly product, IT, and business intelligence)

While none of the two activities are wrong, they do not directly add value to your SEA performance. Put differently, your SEA team is too busy getting stuff done.

Why should you quantify business value?

Leadership should focus on business value

Once our customers start to quantify value and complexity for each SEA project, we see a major change in how ressources are allocated. The biggest changes are:

1. Increase in acceptance for you priorization, as you do no longer soley rely on your expert opinion

2. Discussion on value and complexity will not only create common knowledge in your SEA teams, but also increase value orientation

Quantifying business impact and how machine learning comes into play

Map your SEA projects according to business value

The beauty of google ads is, that the google ecosystem provides highly structured data, which is easily assessible via their Ads and Analytics API.

Unfortunately, we do not see SEA teams using this data as they lack coding as well as statistical capabilities.

In addition, there is large number of SAASsolutions in the market, either aimed at bidding optimization and/or automating your campaign mgmt.

All these solutions are geared towards operational improvement, rather then quantifiying business impact. This is exactly, where we see our solution ValueMap coms into play. It allows you to quantifiy commercial impacts by running simiulations on each SEA Core Process.

In addition, we do not require IT ressources nor will we ask you to commit to certain software or technical stack for running you SEA operations.

Learn more about ValueMap

Isn’t Google already using Artificial intelligence for my accounts?

The short answer is “Yes”. Our philosophy is to use the power of google as much as you can. On the other hand, you also need to be able to challenge the google optimization. Is this really the best you can get? Therefore, teams which run a hybrid approach (both Google and their own intelligent set-up) will be most successful.

Benefit & Learn from Google

Google is using machine learning in their smart bidding algorithms.
Google is using machine learning in RSA (Responsive Search adds), creating new combinations for adcopies
Google is using machine learning, in their adcopy rotation or any other creative test
Google is using machine learning in their audience design, e.g. who is “in market”, similar audiences, and so on
Many more..

Challenge Google with processes&experiments

We believe that smart bidding, which is essentially a black box, should be challenged by our own bidding algorithms
Try RSA, but challenge it by your own data-drive adcopy tests and pattern detection.
Challenge the google adcopy rotation, but looking at the KPIs, e.g. Revenue per Impression, which matter to you
Use proprietary date from you data warehouse or Ecommerce shop to build new audiences.
Many more..

Learn more about our best practices

We are already data-driven in SEA. Are you really sure?

Take in expert views on this journey

Once you stop learning, you start falling behind. Even in mature disciplines as in SEA, it is important not to be satisfied with the status quo, but to constantly challenge the status quo.

Make sure you have the right skill set

What makes your SEA Ttam succeed? The answer is easy as it applies to data science project in general: “The right mix of business know-how, statistical know-how, and coding know-how”.

Our approach

Our approach originates from years of line experience, working with integrated teams online marketing managers, marketing tech experts, and data scientist.