Date: 8th December 2010
The online Christmas plans are pretty much put to bed now, and many websites are entering their CodeFreeze – time to leave the site alone, not change anything, and pray that key routes like the CheckOut pages will handle the traffic peaks OK through to 2011!
Despite CodeFreezes, it’s not too late to make sure right now that you are actually measuring the user experience 24/7 on your core money-making Journeys. This is not web analytics, but 24/7 Mystery Shopper monitoring: if you haven’t got access to graphs of this performance, then move quickly, and focus on having measurements of your core ROI drivers maybe Journeys like CheckOut, or Add to Basket. It’s vital that the website monitoring follows Journeys that you yourself have specified, ones that really ‘do what the customer’ does, including a few of the real world things like choosing a product at random from a screen of choices after a search. If the business teams find the journeys make sense on your web site, confidence in their value as meaningful metrics will grow.[ This Article by SciVisum’s Deri Jones was first published 7 December 2010 in Retail Technology Review ]
But once you’ve got the 24/7 measurements running – then you can start to plan 2011 in January. But how are you going to look back and review your online store’s Christmas performance: what data do you need to pull together; and how will you determine where the ROI can be improved next time?
It will take some data crunching, and a few days without distractions to focus on it, but the result will be that you’ll have a clear strategy of what you want to do differently next time, you’ll have identified the key benefits, and you’ll be halfway to having a business case to get the extra budget!
First off and most obviously, it’s a number crunching task for your Web Analytics staff member. An effective person won’t need much guidance to know what kind of data to pull out. The obvious conversion ratios that you track you’ll want to see plotted: but also it’s worth digging in a little deeper into some of the key pages that make up your CheckOut Journeys, or Add to Basket ones.
Also have visitor numbers per hour plotted. Did the drop off in some of the Journeys itself drop off? You need to look particularly at the keynote data for peak traffic days and hours.
Secondly, pull in the financial numbers. Whilst it may take some concerted asking to get it, you need to get sales per hour for the whole period. In both £ currency, but also in terms of orders placed. A number per day is just not granular enough given that each day it’s only a few hours of the day that produce 90% of the sales.
You’ll be looking for any ‘plateau’ effects. Is the peak sales hour each day, pretty much at the same level? That could be a clue that despite your best marketing and merchandising efforts, it is the performance of the website technology that may be a bottleneck preventing you from getting your sales to the next level.
Thirdly, you’ll need to take the two data sets from above, all plotted per hour and introduce the 24/7 data from the Mystery Shopper of your key User Journeys, that you hopefully had running through out the season.
The task now is to shed light on what the financial numbers above may have hinted at by plotting all three graphs next to each other. Is there a visible correlation between the worst hours for drop off in the analytics data from your CheckOut journey with the order quantity, and Sales value graphs? Also look at how the time periods when the CheckOut journey is most slow and error prone, compare with the plateau from the analytics graphs, and the sales graphs.
That’s a key question to get out at the top of any report you have to provide to management – whether there’s evidence to suggest that spending more on the technology of your website would give more headroom, and hence better peak sales.
Until that question is covered, you can’t be certain that your marketing messages, online campaigns, mailshots and so on are not already absolutely spot on and perfect! If they are, you want to leave them alone of course! But if you have ruled out technology issues as a cause for some sales disappointments, then do drill in to each of your marketing and merchandising areas, to see if the data from Christmas points up successful moments that you can build on organically for 2011: or disappointing results, that highlight where more drastic re thinking is needed.
So, looking ahead to the data you’re going to need in January to do your 2011 planning, now is exactly the right time to set the scene: chat to the WebAnalytics person in your team, chat to Finance about the kind of breakdown you’re going to want. And make sure you’ve given thought to what the key User Journeys you want your Mystery Shopper supplier to monitor 24/7 throughout the season.
2011 will start on a high, despite the hangover, if by the end of the first week you’ve got an evidence-based plan to make it better than 2010 was!
This Article by SciVisum’s Deri Jones was first published 7 December 2010 in Retail Technology Review