Being brought up as a farm boy, I like to think of web real estate in terms of farm real estate. Find fertile grounds; nurture them to derive the most optimal output that will fetch the greatest value on the market. Web real estate is the same, only without and geographic boundaries.
Use analytics to identify the fertile ground. Structure your creative proposition to be planted on this real estate (and the real estate along the conversion funnel) such that it will return the greatest fruit bearing yield. Learn from historical trends and evolve methodologies. This metaphor lends itself to an even more important lesson for retailers – you’ll grow more fruit if you plant seeds in places other than your backyard.
Traditional retailers are reclaiming the ground lost to ‘e-tailers’ (online only retailers) over the past few years, with over 3.5 million unique visitors searching catalogues online for in-store offers over the December shopping period.
Bricks-and-mortar retailers reclaimed market share from e-tailers over the Christmas shopping period, with more than 3.5 million unique visitors searching the catalogues of retailers published on Salmat DigitalForce’s Lasoo.com.au and Dynamic Catalogue platforms during December.
The figure is an aggregated total of unique visitors throughout the month to Lasoo.com.au and the 20-plus Dynamic Catalogues hosted within the sites of individual retailers, including major brands such as Target, BIG W, Myer and Dick Smith.
Previous Christmas retail periods indicated a trend towards consumers engaging more with e-tailers’ at the expense of the bricks and mortar retail brands. This was largely attributable to the fact that time-poor consumers were easily able to find exactly what they were looking for on the internet from the online retailers, while traditional retailers struggled to make their brands and offers discoverable online.
Since the November 2007 launch of Lasoo.com.au, which allows consumers to search catalogues and offers from various retailers; and Dynamic Catalogue, a managed catalogue hosting solution that sits within the retailer’s own site; offline retailers have had an effective way of making their catalogue offers visible to consumers online. What’s more, the technology behind Lasoo.com.au and Dynamic Catalogue allows these offers to appear towards the top of search results from search engines such as Google. Until Lasoo and Dynamic Catalogue, these search results pages were previously dominated by e-tailers.
Pre-Shopping has become a growing trend for online shoppers seeking instant gratification, as witnessed by e-tailers with conversion rates around 1% to 4%. Retailers have capitalised on the behaviour in 2008, clocking up a 24% conversion rate from online–to-offline transactions.
Lasoo analysed Hitwise data by comparing a custom category of the Top 25 Retailers (traditional bricks and mortar retailers) against a custom category of top 25 E-tailers (pure online retailers) based on market share of Australian Internet visits. As a result the year-on-year comparison of the market share of traditional retailers v e-tailers[1] during Q4 clearly demonstrates this trend, with the retailer Christmas traffic surpassing the benchmark previously set by e-tailers as they now seem to have reached a ceiling over the last 2 years.
E-Tailers vs Retailers Q4 06
Etailer vs Retailer Q4 07
Etailer vs Retailer Q4 08
[1] Using custom categories (see endnote) comparing weekly visits against traffic in “All Categories”
E-tailer traffic included:
shop.lego.com www.1-day.com.au www.abebooks.com www.allposters.com.au www.altech.com.au www.amazon.com www.ap.dell.com www.apple.com.au/itunes www.avon.com.au www.bargaindeals.com.au www.bigpondmusic.com www.bodybuilding.com www.booktopia.com.au www.cafepress.com www.catchoftheday.com.au www.crazysales.com.au www.dailydeals.com.au www.deals2u.com.au www.dealsdirect.com.au www.dinosaurdeals.com.au www.dstore.com.au www.ezibuy.com.au www.ezydvd.com.au www.factoryfast.com.au www.fishpond.com.au www.graysonline.com.au www.hp.com www.isubscribe.com.au www.itvsn.com.au www.latestbuy.com.au www.lenovo.com www.liteneasy.com.au www.modyourcar.com.au www.moshtix.com.au www.mwave.com.au www.oo.com.au www.ozstock.com.au www.play-asia.com www.redbubble.com.au www.shoppersadvantage.com.au www.shoppingsquare.com.au www.simplymobile.com.au www.soldsmart.com.au www.strawberrynet.com www.streetsmartshopper.com.au www.techbuy.com.au www.ticketek.com.au www.ticketmaster.com.au www.topbuy.com.au www.wickedweasel.com.au www.winemakerschoice.com.au www.zazz.com.au www.zazzle.com.au www.zodee.com.au
Retailer Traffic included:
catalogues.bigw.com.au shop.telstra.com.au store.three.com.au store.vodafone.com.au www.abcshop.com.au www.aldi.com.au www.angusrobertson.com.au www.bcf.com.au www.bigw.com.au www.bigwentertainment.com.au www.binglee.com.au www.borders.com.au www.bunnings.com.au www.coles.com.au www.crazyjohns.com.au www.davidjones.com.au www.digitalcamerawarehouse.com.au www.digitalhome.com.au www.dse.com.au www.dymocks.com.au www.ebgames.com.au www.fantasticfurniture.com.au www.flightcentre.com.au www.freedom.com.au www.game.com.au www.harveynorman.com.au www.ikea.com www.jaycar.com.au www.jbhifi.com.au www.jbhifionline.com.au www.kmart.com.au www.loadit.com.au www.mitre10.com.au www.msy.com.au www.myer.com.au www.officeworks.com.au www.petersofkensington.com.au www.rebelsport.com.au www.retravision.com.au www.rivers.com.au www.sanity.com.au www.spotlight.com.au www.supercheapauto.com.au www.supre.au.com www.target.com.au www.target.dynamiccatalogue.com.au www.teds.com.au www.thegoodguys.com.au www.toysrus.com.au www.umart.com.au www.videoezy.com.au www.westfield.com.au www.witchery.com.au www.woolworths.com.au
This question is a great one that confuses many – even the Wikipedia page it references could be made a little clearer…. maybe in my spare time I’ll update it 
“This information was referred to me but it has sort of confused me more. Its called The Hotel Problem. http://en.wikipedia.org/wiki/Web_analytics
I understand what it is saying but why doesn’t it apply to First Time Unique visitors which gives you the same total for the month in comparison to adding up the value for every individual day?
It will explain how Prior Unique Visitors is different depending on the date range.
Any further thoughts?”
This is a common question and basically it comes down to the measure of “uniqueness”.
Prior unique visitors seems to be a “return unique visitor” while the Ffrst time unique visitor is an absolute unique visitor.
Your total unique visitor count should be a combination of Prior Unique Visitors and First Time unique visitors.
If you look at the table below;
| Day |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
| Visitor A |
1 |
|
1 |
|
1 |
|
1 |
|
|
1 |
| Visitor B |
|
1 |
|
|
|
1 |
|
|
|
1 |
| Visitor C |
|
|
1 |
|
1 |
|
|
|
1 |
|
Then you get this result,
| FTUV |
1 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| PUV |
0 |
0 |
1 |
0 |
2 |
1 |
1 |
0 |
1 |
2 |
| TUV |
1 |
1 |
2 |
0 |
2 |
1 |
1 |
0 |
1 |
2 |
When you look over different time period and add these visits together you see a lot of variance that seems contradictory.
| 1 Day granularity |
10 Day Granularity |
| 3 |
3 |
| 8 |
0 |
| 11 |
3 |
FTUVs will never change with granularity because a visitor can only be new to your site once (unless they delete a cookie, and then they are a new visitor).
