How do I combine multiple filters for a precise search?

Introduction #

In today’s digital marketing landscape, precision and relevance are key to successful campaigns. AdSpyder, a powerful advertising intelligence tool, allows users to conduct text-based searches in its vast ad library to uncover historical ads along with their details. With multiple filters available, combining them for a precise search can help users uncover the most relevant data for their specific needs. In this response, we will discuss how to effectively combine multiple filters for a more accurate and targeted search.

Pointwise Information #

• AdSpyder’s Text Search feature allows users to search historical ads based on text content.
• Users can select a platform (Google, Meta, YouTube, Bing, Reddit, LinkedIn, Google Product Listing Ads (PLA), Bing Product Listing Ads (PLA), Display, Amazon, and Flipkart) and type of search (“Broad” or “Phrase”).
• After the search, users can apply filters to refine their results.
• Standard filters include Country and date range, ad copy title or content, and sorting options.
• Advanced filters offer more granular control, such as call-to-action types, ad extensions, sentiment, tone, statistics, question inclusion, urgency words, benefits highlighting, problem-solution dynamic, emotional appeal, social proof, comparison with competitors, target audience identification, localisation elements, seasonal references, discounts and offers, guarantee mentions, brand name placements, product/service category, price mentioned, cross-sell opportunities, technological compatibility, and more.

In-Depth Content #

When conducting a text search in AdSpyder, combining multiple filters can help users uncover the most precise results for their query. Let’s explore how this can be done using an example. Suppose a user is looking for ads related to running shoes for men with discounts and emotional appeal. They would follow these steps:
1. Select the platform (Amazon or Flipkart) and type of search (“Broad” or “Phrase”). In this case, let’s assume we choose “Broad” and type “running shoes men” into the search bar.
2. After getting the initial results, they would apply filters to refine their search:
a. Country: United States
b. Last seen date: within the last month
c. Ad copy content: contains the word “discount”
d. Advanced filter: Emotional appeal = Yes
3. By combining these filters, the user can uncover ads that specifically match their criteria – running shoes for men in the United States, shown in the last month with emotional appeal and containing the word “discount.”

Conclusion and Call to Action #

In conclusion, AdSpyder’s Text Search feature, combined with its powerful filtering capabilities, allows users to conduct precise searches for historical ads that meet their specific criteria. By understanding the various filters available and how to effectively combine them, users can uncover valuable insights to inform their digital marketing strategies. Take action today by logging into AdSpyder and conducting a text search of your own, refining your results with filters for a more accurate and targeted analysis.