PPC: It All Starts With Data, Especially In The AI Era

DATA

How the raw data becomes the critical point of influence in PPC campaigns … in the AI power era.

Understanding the critical impact of data within the framework of system thinking, machine learning, and AI language models can empower marketers to harness the true potential of PPC campaigns. How?

PPC algorithms and AI language models rely on the same foundation: input data. No matter how sophisticated the algorithms get, the initial data becomes the most powerful means to manipulate, influence, and control the systems.

Consider the following five levels when examining data:

  1. Data – raw material
  2. Information – data in the context
  3. Knowledge – information + how to – skill and instructions
  4. Understanding – knowledge + purpose of the components – explanations – an answer to the WHY question
  5. Wisdom – meta-understanding where efficiency turns into the effectiveness

Efficiency is concerned with doing things right. Effectiveness is doing the right things. – Peter Drucker.

Since AI occupies the most effective data processing levels, we are left only with the Wisdom … and the raw Data. Feed Management Systems deal with the latter. 

Product data in PPC feeds have always been neglected by most PPC professionals since there is so much effort needed to do it right to keep it updated to personalize it to different channels on different keywords with multiple conditions in other contexts.

According to Feed Marketing Report by DataFeedWatch, 7% of all items in the Google Shopping feed get rejected due to data errors. The most common feed errors are related to shipping settings and images – they stand for 44% of all product ad disapprovals.

Zooming in on the errors, we also discover that almost 6% of all submitted GTINs need to be validated, causing product disapprovals, even though retailers can skip over the GTIN attribute and get products up and running without GTINs.

Feed management solutions deal with the problem to the extent it is critically vital for the feed not to cause errors and manage information with the help of rules, and automation, making data processing feasible. 

Paradoxically the single most influential place of competitiveness may be found in raw data, in the non-mandatory fields, additional images, extended product technical information, additional contexts, and variables customized to various channels. Why? A few universal rules apply across all the channels and marketplaces. What are they? 

The PPC algorithms rely on a few rules: 

  1. Accuracy of data – no matter if this is Google, Bing, any channel really, generative AI as well – all the algorithms “prefer” accurate data, relevant, most sought by consumers
  2. Richness of data – algorithms of channels, marketplaces, and search engines “prefer,” give extra value, provide extra visibility, give a different score for additional data, more pictures, more angles, more technical material descriptions, more categories – and with more and additional we mean data that are often not “necessary” to run your PPC campaign, non-obligatory information, the kind of information you typically don’t pay any attention to 🙁 
  3. Following channels, marketplaces rules, and policies on data – what data you provide, in what form, what is not allowed, what is risky, what is ambiguous – if you don’t pay attention to these long stream of policies, regulations you may get in real trouble – you may face account suspension and blocking with a spiral of problems and long discussions extended into weeks and months. 

Applying all the rules at once increases the performance of your PPC campaigns. Only applying 1) or 2) will increase visibility. Only use 3) may get your products blocked and your account suspended. 

Paying more attention to the raw data gives you a decisive advantage over your competition, even though most of us don’t expect to find it there. 

Frequently Asked Questions

What is the significance of raw data in PPC campaigns?
Raw data is significant because it serves as the initial input for PPC algorithms and AI language models. Despite advances in technology, raw data remains the most influential tool to manipulate, influence, and control the systems.

Why is product data in PPC feeds often neglected?
Product data is often neglected because it requires substantial effort to maintain and update it across different channels, keywords, and contexts.

What are common errors in Google Shopping feeds?
The most common errors in Google Shopping feeds are related to shipping settings and images, accounting for 44% of all product ad disapprovals. Additionally, almost 6% of all submitted GTINs require validation, leading to further disapprovals.

What role do feed management solutions play?
Feed management solutions handle the critical task of ensuring feed data doesn't cause errors. They help manage information using rules and automation, making data processing feasible.

Why is raw data considered a competitive advantage?
Raw data, especially non-mandatory fields, additional images, extended product technical information, and customized variables, can be highly influential. Such additional data can enhance visibility and performance across various channels and marketplaces.

What are the basic rules that PPC algorithms rely on?
PPC algorithms prioritize accuracy of data, richness of data, and adherence to channels, marketplaces rules, and policies on data. Neglecting any of these can decrease visibility, or in worst-case scenarios, lead to account suspension.

How can one increase the performance of PPC campaigns?
Applying accuracy, richness of data, and following data policies at the same time can enhance the performance of PPC campaigns. Ignoring these aspects can lead to lower visibility and potential account issues.

How does the neglect of raw data affect PPC campaigns?
Neglecting raw data can lead to missed opportunities for competitive advantages. Such data can be crucial for increasing visibility and performance across various channels and marketplaces.

What happens if GTINs are not validated?
Unvalidated GTINs can lead to product disapprovals. Retailers can skip over the GTIN attribute, but doing so may still result in product disapprovals.

Why is there an emphasis on non-obligatory information in PPC feeds?
Emphasizing non-obligatory information can increase the richness of the data, enhancing visibility and performance. Such data can provide additional value, increasing the visibility score across various channels and marketplaces.

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