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To help analyzing a site's user flow, I wrote a test bed in JavaScript, creating a new fake tracker, sending a few fake pageviews in like 1-2 second intervals according to a pretty extensive, randomized graph of expected views. I then set up goals in GA, containing funnels through certain pages. Then I left it running for a few hours, accumulating a few hundreds fake users.

Raw goal conversion percentages look good, page content flows too, BUT... when I'm looking at Goal Flow, some of the connections in the funnels don't make sense. For example 80% of my fake users seem to go from step "about" directly to step "success", skipping "product" and "payment", while - according to my test setup - that can't ever happen. (Step names used are examples to match the code below.)

I'd like to see exactly what paths did these particular users take - did some pages just not register, or did they register out of order, or what? Is there any way I can view RAW user journeys in GA, page by page?

For those interested, the testing code is basically like this:

    ga("create","UA-0000000-2", "auto", "testtracker", {
        'cookieName':"_ga_test_"+Date.now(),
        'cookieExpires':120,
        'clientId': 'cid-'+Date.now(),
    });

    var spd=1500;
    var delay=0;

    function pageview(page) {
        setTimeout(function() {
            ga("testtracker.send","pageview",page);
            console.log("Sending: "+page);
        },delay+=spd);
    }

    pageview("start");
    if (Math.random()<.60) pageview("about");
    if (Math.random()<.30) {
        pageview("product");
        if (Math.random()<.20) {
            pageview("payment");
            if (Math.random()<.70) {
                pageview("success");
            }
        }
    }
Sinus the Tentacular
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1 Answers1

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Apparently, I still have a lot to learn about GA.

The solution is to use Audience -> User Explorer and defining a very specific Section based on the suspicious sequence of pages does show individual users matching that pattern. And indeed somehow GA logged a pretty large number of such odd users for me, perhaps failing to register pages visited in too narrow time intervals.

I'm leaving the question for posterity, and perhaps for those who can find my code snippet useful.

Sinus the Tentacular
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