CIQ's Market Insights platform makes it easy to see the Share of Voice (SoV) of brands in real-time and utilise it for strategic insights and to drive SoV aware automated actions.
The process involves sifting through and analyzing crawled data across thousands of keywords.
The keyword generation process includes combining multiple sources to generate keywords, scraping through associated data and filtering these keywords based on various metrics like Estimated Attributed Revenue (EAR), Ad spend, Volume and Share of Voice (SoV) to get relevant keywords for tracking on shelves.
CIQ's AI model automatically organizes and clubs keywords into specific categories or 'Digital Shelves'.
Every Digital Shelf setup activity involves having an input hierarchy and mapping the keywords generated earlier to this hierarchy.
The different hierarchy approaches for Shelf setup:
Using Internal / Amazon Categorization
Using Custom hierarchy
Using No input hierarchy
Keyword harvesting is currently done using Amazon advertising API and product recommendations for the same set of Amazon Standard Identification Number (ASINs) are done using the recommended product APIs.
Keyword prioritization is important as Amazon advertising APIs gives out a lot of keywords at an ASIN level but to understand how much revenue and search volume is driven by these keywords at a brand level is something that needs to be metricized.
Methodology
Step 1 – Harvest Keywords
Step 2 – Scrape Keywords
Step 3 – Calculate SoV
Step 1 – A number of sources are leveraged to identify keywords to scrape
Advertised Keywords
Suggested Search Terms
Search Frequency Reports
Keywords identified from other Retailers
Step 2 – Once a day the keywords are scraped for each retailer
All products displayed on page 1 of the retailer are scraped through
Note that number of products displayed on page 1 can vary for different retailers
'Sponsored' tag indicates organic vs. paid
Layout of the page identifies sponsored brands
Item details includes Brand Name, Item ID, Title, UPC
Step 3 – Customer provides their catalog so that their brands can be identified within the data
Individual keyword level SoV is then calculated based on:
Number of slots taken up by the brands
Placement of brand items
Aggregated SoV across multiple keywords also takes into account relative keyword volume (ranking converted into volume)
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