When it comes to analyzing the root cause, we have several diagnostic tools we can use, and they reside on three different levels of data that we can get: the basic behavioral data, the next level data, and the predictive data. Let’s get into each one of these.
The basic data comes from tools that you don’t need buy-in or set up for. One of them is Google Search Console (GSC), which can reveal poor intent match when we look at CTR both from a branded and non-branded perspective. Most of the other data in this bucket is qualitative and allows us to identify common points of frustration both for a pre- and post-purchase journey, like surveys, CX logs, social mentions, and reviews, so make sure you collaborate cross-functionally to have access to what users are asking of you. There’s also live testing, which is the most time-consuming option, but also potentially one of the most rewarding since there’s not much to infer.
If you liked How to Analyze Behavioral Data for Search — Whiteboard Friday by Giulia Panozzo Then you'll love Miami SEO Expert
Workflow 3: Competitive analysis with chained agentsCompetitive analysis is one of my favorite AI use…
So how do I optimize my websites for agentic AI to make sure that it…
Once we move from topics to questions, whether in organic search or LLMs, we naturally…
As shopping agents now research products, compare options, and complete purchases, e-commerce sites will need…
Brand24 combines traditional social listening with AI visibility tracking. It monitors social media, news, blogs,…
Now that I had my high-level competitive analysis done, I wanted to dig a bit…