Hi all!
At the moment we are currently struggling to find a way to accurately track ROI from composite emails being sent through WordFly to our Database. The thing is, we can track back how many tickets and how much revenue we've made on said emails if we suppress any current bookers from the extraction. (For example, we recently sent out a What's On in December style email which included several different shows. We need to track ROI on this particular email for reporting). When we go to our analytics dashboard and fill in all the criteria, the figures that come back are pulling any bookers through. For instance, if we sent the email with let's say 5 shows on, and the ticket total paid amount comes back in at £450,000, we would know this is far too much to have been raised from that particular email.
We know that when we suppress any current bookers from the main extraction, the results that come back in analytics appear to be accurate. However, as soon as we don't suppress any current bookers, the results become skewed. Is there a way we can get the system to pull through figures of only tickets that were bought via that specific email? We are using the same filters as we do for other results tracking (including things like order date [when we sent the email out up until a week after] and list filters using the list number that was attached to the email), but to no avail. In short, suppressing current bookers gives us accurate data but narrows our potential audience reach whilst not suppressing current bookers broadens our reach but doesn't give us accurate data. Is there something we're missing?
Any feedback or ideas would be appreciated,
Alex.
Hello Alex - Please add a few missing but key details:
I don't get to spend as much time on this analysis as I would prefer, but I can load up Sales by Source per Prod Season or whatnot, and could certainly filter it against a List of Constituents who got the email if I so choose. You might also just filter by that same List against all sales for X during whatever time period you deem relevant. This will get you non-attributed sales too, and you can decide if it feels right to credit them to the promotion or not.
I also imagine you might be able to construct a widget filter within Analytics directly based on constituents who have the designation Source, but that might take a bit more thought than using a List configured via List Manager. Another reporting option is to see what returns via Google Analytics if you use WordFly's auto-append GA option. That limits you to only web sales of course, but it can be a reasonable option if that's a majority of orders and/or your team is fine with that caveat for the analysis.
Plus 1 for Jamie O'Brien's first bullet point. We have that enabled on TNEW as well as our custom/marketing site via Javascript, and it is EXTREMELY useful.
In addition, since the web tables are cleared every night for data beyond the last 14 days (for performance reasons related to table size), I also created web table back-ups which allow us to not only report on successful transactions against those sources but to also look at and evaluate the frequency of what performances are being carted but not purchased against the frequency of purchase via those same source codes. This has aided in terms of dynamic pricing.
(Your own use/application of these examples may vary) As an example, we have found that, with our social ads/sources, our average purchase/carting ratio to be about 1/3. So, as an example, we have found that few purchases but LOTS of carting compared to the average purchase/carting ratio likely means prices are too high since people want it enough to put it into their cart and think about it, but not enough to actually spend the money. Versus the other side of things, when we see a purchase/carting ratio that is well above 50% that usually means we can safely raise prices and still expect to see a pretty good return on our ads.