5 AI workflows under the "Traffic Source Analytics" topic. Each includes a copyable prompt and FAQs. Paste them into your preferred AI assistant or Spark agent and run it.
Every source label in the reports is spelled differently, so the merchant can only rank channels on session counts. In this case, the immediate task is to report traffic volume and quality by source. The workflow should produce a channel traffic analysis with measurement caveats, ranking sources on quality beside volume and isolating unattributed traffic.
Search visitors arrive steadily, but the merchant has no matched periods to compare them against. In this case, the immediate task is to analyze organic traffic performance over matched periods. The workflow should produce a channel traffic analysis with measurement caveats, holding attribution rules fixed while comparing landing pages and orders.
Ad-tagged sessions keep arriving, yet the merchant cannot separate campaigns that produce orders from campaigns that only add visits. In this case, the immediate task is to analyze paid traffic quality and conversion. The workflow should produce a channel traffic analysis with measurement caveats, matching each campaign's sessions and orders to its spend.
Posts go out across several platforms, each sending its own traffic, and the merchant must decide where the next campaign goes. In this case, the immediate task is to compare traffic from social media sources. The workflow should produce a channel traffic analysis with measurement caveats, tying each platform's volume and orders to the posts published then.
Visits keep coming from directories, blogs and partner sites, and the merchant suspects some domains send traffic that never shops. In this case, the immediate task is to analyze referral traffic and its purchase behavior. The workflow should produce a channel traffic analysis with measurement caveats, judging each domain by its landing pages and orders.
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