Engage-Digital

Lately I have been coming across a series of small but potentially significant shortcomings in the web analytics tools I have been using. I only unearthed them as I was playing around with different ways of getting the same output, in other words sense checking the data I was looking at.

The trouble is if I hadn’t done that I might have taken the first answer as gospel and moved on, unaware that the insight I was inferring was based on incorrect data. I’m talking about the kinds of things that are genuinely obscure and might not impact that many users but for those that do they could make a big difference.

Given that the industry’s mantra is broadly ‘rubbish data = zero insight and worse, possibly damaging action taken as a result’, it seems as though the suppliers of web analytics tools have a responsibility to document and make freely available the shortcoming of their products especially where those shortcomings could have a serious impact. Of course the trouble that would be suicide.

It’s a catch 22, keep quiet and hope that you don’t do too much damage to your client’s site’s or take a more responsible standpoint, ’fess up and deal with implications that come with it.

Bounce rate is a kind of standard bearer metric for measurement in web analytics, it’s up there with conversion. Even novices in web analytics know what bounce rate is, and when asked what should be the objective regarding bounce rate you’d have to be a lunatic to say anything other than “try to reduce it”. But increasingly, I think there are some misconceptions about this metric. Remembering that bounce rate applies to both entry pages and referring sources of traffic, two thoughts that come to mind are as follows:

1. When thinking about bounce rate in the context of entry pages it is hardly surprising that it’s lower on the home page than on a product page. I’ve seen very few sets of data in which the situation is reversed. I think this is because the home page offers a bigger target, i.e. there are more options for a visitor when they arrive on the home page than if they arrive on a highly specific product page. Trying to reduce the bounce rate on a product page is worthy and will yield results for sure but don’t expect to get it down to home page levels.
2. Lower bounce rate = more actual conversions. I’m not disagreeing with this but increasingly as I look at weekly and monthly trended data for various clients I see examples where BOTH bounce rate and conversion actually go UP against a particular referral source. This in turn quite often results in higher yield volumes as well.

This isn’t to say that it’s OK to let the bounce rate metric rocket up, retaining more visitors at the same conversion rate WILL of course produce greater conversion yield volumes. It’s simply to say that it’s not necessarily worth freaking out the minute a bounce rate shows signs of edging upwards. I would always look at the surrounding metrics to build a bit of additional context before deciding on a course of action.

The old adage ”quality not quantity” comes to mind here. A higher bounce rate might mean lower visitor retention but if more of those visitors are converting and the overall conversion yield is going up then that might prompt another old adage “if it isn’t broke….”

I see that Eric Peterson has written a nice white paper on what he refers to as ”The Coming Revolution in Web Analytics”, it can be downloaded  here. In it he talks about the future of web analytics and in particular what he calls 3rd generation web analytics.

I won’t paraphrase what he says about 3rd gen WA (really better to read the white paper) except to say that he no longer describes it as  web analytics as it starts to move into the realm of general business and customer intelligence.

Among the thoughts that occured to me whilst reading his white paper, two stood out:

1. What he says about 3rd generation web analytics / business / customer insight at a practitioner level sounds a lot like the kind of thing econometricians have being doing for years although initially they weren’t including heavy weight web data. But the kind of modelling he talks about is already being done by econometrics units in many media and advertising agencies.
2. What he describes as being 3rd gen (web) analytics is no doubt advanced stuff but I think the problem will be uptake. I think that there will be a small cadre of trail blazers who will get heavily into all the mechanisms he outlines such as cross channel data mining, predictive modelling, confidence analysis of customer segmentation etc. but the trouble is this will be for the big guys who can afford it and even then precisely because it is complex it will probably only be taken up by organisations who have the right people in the driving seat. i.e. despite having a highly capable team of analysts and statisticians, a C level director who’s head is filled with many things may find it hard to champion this stuff unless s/he has a reasonable to good understanding of it his or herself. For the rest of the world – i.e. the majority of small and mid-sized businesses it’s still a long way off.

None of that is to say that A) Peterson isn’t correct in his overview or B) it isn’t what should happen, just that the main obstacle may be one of human resource more than technology, much as it has been up until now.

Google’s Chief Economist Hal Varian recently posted a note on the Inside AdWords blog stating that ad position on Google’s search results does not affect on site conversion. This may not be supprising given that the comparison is made using the same ad on the same search results page clicking through to the same site, the only difference being psition.

Varian acknowledged the widley known fact that a higher position does however yield more clicks. Google positions ads based on bid price and quality so better quality ads and higher bid prices will result in better positioning, more clickthroughs and ultimately more conversions, but the on site conversion rate will most likely be the same or similar compared with ads that appear lower down.

Does this insight affect PPC strategy?

It depends. PPC doesn’t just have to be about clickthrough rates and conversion rates. Volume and cost of aquisition / margin also come into the equation. A lower bid on a high quality add will probably drop it down the pecking order restuling in fewer clicks and few conversions but because the bid price is lower the cost of sale will also go down and margins will go up. However gross sales and revene will suffer.

A higher bid on a high quality ad will have the opposite effect with gross sales and revenue going up but at a greater cost which in turn may reduce overall profitability. Equally, money saved by bidding low could be siphoned off into other strategies such as SEO which in the longer run could yield both high volume at a lower cost.

Today we have more choice than ever before. More choice in almost anything we can think of to consume and this is generally regarded as a good thing.

I’m of an age in which my parents were alive during the Second World War and they remember rationing and less choice. The mantra in the UK at that time was “mend and make do”, something that has been dusted off recently as we all struggle with the harshest economic climate since the First World War. Back then being paralysed by choice wasn’t an issue.

The web has had a very significant impact on the level of choice over the last 15 years or so. We have more choice than we know what to do with across such huge range of areas from the media we consume, to the way we search for places to live and holidays to go on, entertainment and means of communicating with other people.

Given the human imagination it would be fair to assume that our capacity to absorb choice would be almost unlimited; they say “if you can think it, it’s probably been done”. Amend that to “if you can think it, it’s probably been done and you can find out about it on the web”. As a group the human capacity for choice is practically unlimited but individually, I think not.

So Google has played a key role in all of this. It’s mission statement being to.. “organize the world’s information and make it universally accessible and useful”. Whether it’s organised it or not is another matter but it has certainly made it much more accessible.

What it means for the retailer

Dial that back now and consider the much smaller universe of an online store. One of the benefits of ecommerce is the lower costs of doing business. These come about as a result of lower overheads due to stock being held in cheap warehouses in business parks and on trading estates instead of held on more expensive shop floors. That also means there’s a lot more space available – Amazon’s warehouses are enormous – and that in turn means a huge selection of stock that can be sold through the online store. So we come back to ever increasing choice for the consumer and how to wade through it especially if you’re shopping online.

What it means for the punter

The fact is, if you’ve decided take up running you’ll probably want a pair of running shoes but if you arrive in an online store and you’re presented with a choice of over 200 different pairs of shoes, being faced with such a huge range may actually be more of a hindrance than a help; back to the paralyzing  tyranny of choice. The end result for the retailer being a no sale situation.

Just as Google has tried to do with the world’s information the key for the retailer is to organise and make stock more easily accessible. More than anything else this will help the customer, more than beautiful product shots,  clever copy or fancy widgets and tools, if a customer can’t find what s/he’s looking for and narrow it down to a manageable choice then there is no deal.

What it means for the website’s store developer

Success means that navigation and organization are co-dependent. Tools like Omniture’s Merchandising, Fredhopper, Endecca or Celebros will all help with both organisation and narrowing down the product search through the mechanisms of both free text search and more importantly guided navigation but there is still the most important job to be done of categorising and tagging products so they can be easily filtered by the customer using these tools.

The point here is not at all about the technology but about the need to create a framework which will do as much of the decision making for the customer as possible with the end result that the final decision, the one to buy, is as simple and straight forward as can be.