Engage-Digital

I may get shot (down in flames) for writing this post.

Web analytics is not just about data, this is well documented and blogged by far greater minds than mine – so I won’t get shot for that I hope! Web analytics is simply the engine behind driving better performance online. Better performance online for most organisations that actually engage in web analytics is usually about driving more revenue and improving cost efficiencies- and of course improving conversion.

99% of companies in the UK are SMBs and I think this is the great challenge for the web analytics industry. Many SMBs have websites and many of those websites perform a function, but the hard reality is that amazingly they don’t have the same size budgets as the average blue chip fortune 1000. They still need to invest to improve performance so they must approach their performance optimisation from a different perspective.

Usability is arguably a part of web analytics (2.0 as it has been labelled). There are many great usability experts out there and several different ways of approaching usability; these range from individual lab based usability tests, remote sample based usability tests using services such as Ethnio to journey replay solutions like Tealeaf.

To be clear, after looking at click-stream data and having identified where a problem might lie, if usability is what’s needed to unearth the truth then the methods just mentioned should be the preferred route; but they aren’t cheap.

A more cost efficient option would be to use a click based heat mapping product such as ClickDensity or CrazyEgg. These are not new products, they’ve been around for a while and they’re like click maps on steroids. They record clicks regardless of the presence of a link or not. They show the results either as actual clicks on the part of the page where the click was made or aggregated as a heat map. The advantage here is that where a standard link overlay will only record a click if it occurs on a link (assuming the tag is set properly) these tools will record click activity regardless. In other words, if a visitor reaches a page and attempts to click on something that looks like a link but isn’t, it will be recorded and show up.

So how do you get the most out of these tools in 5 ½ steps?

1. Assume a customer journey based on a task – making a purchase or signing up to an email
2. Replicate the customer journey as best as possible using a funnel or scenario in your analytics tool
   • Start with the most popular entry page
3. Allow enough data to collect
4. Identify main points of attrition (try and think why this might be happening i,e, form a hypothesis for each page where there is considerable drop off)
5. Look at the offending page using the heat mapping tool. The heat map will of course only show where your users have clicked but because it records every click there may be some surprises regarding where activity has and has not occurred and this could lead to action resulting in improved performance. For example there may be a high volume of clicks on a piece of text which has been mistaken for a link, this is potentially lost traffic and could go some way to explaining the drop off.

Any tweaks to the page that are implemented can subsequently be A/B tested to verify performance.

Cons

• Again, I should state, this is not the real deal in usability circles (don’t shoot!)
• You can’t talk to the people viewing the page and you can’t hear their thoughts as they navigate the page
• You can’t see cursor movements
• You can’t run the test with users instructed to carry out specific tasks

Pros

• For the budget conscious business it is much cheaper and more cost efficient. Even for large organisations it is a good practice
• The sample size includes everybody that interacts with a given page
• You can run A/B tests using these tools and compare your results instantly and run the best performing page.

This final point is perhaps the crux of it. The objective here is to amend the page design so that it makes life easier for the visitor and thereby unblocks the path to customer satisfaction.

This post has been written in the hope that it will prompt the more budget conscious business to think about how they can approach usability from a standing start. It’s not an attempt to provide a definition.

Please feel free to comment with your own thoughts and experiences.

Measuring conversion on an ecommerce site pretty much always involves establishing an overall site conversion rate. For most ecommerce sites this figure seems to hover around the 2% mark. Overall conversion rate seems like a hallowed metric – the one true “anchor metric” by which overall performance is measured. As a result there seems to be a slavishness regarding the site conversion figure. I think this can be misleading.

Firstly, to be clear, increasing the conversion rate is an excellent goal to aim for, but if it drops off it is worth considering two other performance metrics:

1. Total volume of sales
2. Cost per sale

What are overall sales doing? Are they increasing or decreasing?

Has there been a marked increase in marketing spend or spend in any other areas of acquisition?

Volume Vs conversion
As a rule, the more paid for (solicited) traffic driven to a site the greater the pressure the site is under to perform.

Demand generated traffic, by which I mean the likes of online display, tends to deliver visitors with lower levels of interest and a lower pre-disposition to take a desired action. It’s not surprising that this often has a negative impact on overall conversion. However, driving traffic to a site is crucial to growth for obvious reasons.

Affiliate marketing is a good case in point. Say an agreement is made between a client and an affiliate network (such as TradeDoubler or Commission Junction) with remuneration being established on a cost per sale basis, effectively the client’s acquisition (CPA) cost is fixed at a certain rate. The result is that the cost of driving the mix of volume and quality traffic is passed on to the affiliate network. The affiliate network’s strategy (to begin with) may be to drive a large volume of extremely low cost traffic, with the result that conversion goes down while sales volume is met and CPA is met.

Because the affiliate network is paid on every sale that is attributed to them they are incentivised to provide as many sales as possible at the lowest possible cost to them. There could also be an additional incentive if they reach a certain target volume in a given time period. In other words these combined conditions can give rise to a situation in which volume of sales increases while conversion rate falls.

I have seen instances reflecting this where conversion has taken a sudden dip while volume of sales remained steady; on further investigation it was traced to an increase in traffic which in turn was traced to one specific site in another country – a direct result of rogue affiliate action.

Cost per sale Vs conversion
In the case of an e-commerce site where the desired outcome is generally pretty simple by definition – sell something – all efforts can be said to contribute towards that one goal. Therefore all expenses incurred can be said to be as a result of pursuing that goal. It would be reasonable then to establish a cost per acquisition figure which should also act as a key performance indicator.

The issue becomes how to measure cost per acquisition and what to include in the cost of sales: advertising, site updates, internal labour costs, 3^rd party costs (professional services, systems etc), administration and so on.

The more included the higher the CPA. But, fixing the equation will at least allow the CPA to be used as a benchmark performance metric over time.

It seems to me that if sales are increasing and overall cost per acquisition is falling then performance can still be viewed positively despite a conversion rate which may also be suffering as a result.

By contrast, if the conversion rate is going up but sales are falling and cost per acquisition is increasing in part due to an expensive but highly targeted acquisition strategy which has a low yield then the increasing conversion rate can be misleading.

Doubtless this is all stating the obvious but it is done so in the aim for a more balanced perspective.

I’ve worked with quite a few e-commerce sites over the past few years and in our dashboard of metrics visits reaching a product page has always been there. This is for two reasons:

1. In (almost) all cases its possible to add a product to the shopping cart page from the product page
2. Because the product page naturally contains the greatest volume of information relating to a product.

So it has always been considered good to get visitors to the product page because shop owners stand a better chance of selling from the product page.

On that basis marketers often have a fairly obvious eureka moment and decide what a good idea it would be to land traffic directly on their product pages. No!

Product pages are just that, they aren’t landing pages. There is a significant difference and it is hard to find a page that will do both.

Because of this strategy it is possible for the “Get to product page” conversion metric to vary from anything between 40-75%. I think there are two problems with this.

Firstly this standard way of viewing this conversion metric doesn’t take into account traffic that was just dumped there by an adword campaign or a banner of affiliate campaign.

Secondly, by including visits that enter on product pages it masks the ability of the site to actually drive traffic through to these pages.

Funnels
Ah, but what about using a funnel to accurately track conversion to product page?

It depends on which analytics tool you use but many now, including Google Analytics, quite correctly (in my view) do not base their funnels on rules that require a visitor to have passed through the previous step in order to be counted I the next step. That means all visits reaching each step are counted – including those that enter directly.

Don’t forget bounce rate

How could anybody forget bounce rate. In this instance bounce rate queers the pitch because not only do these visits enter on a product page but they also disappear again immediately without doing the one thing we want them to. In other words not only did the site play no part in driving these guys to a product page but also they were totally disinterested in what they saw. Definitely not to be included in a performance metric like “get to product page”.

In short then, first know what you want to measure.

1. Is it the site’s ability to convert visits to a product page or…
2. …just the total number of interested visits that arrive at a product page.
3. Or do you really want to know the total figure, warts and all.

If it’s 1 then look at total volume of visits reaching the product page less the total volume of visits that enter on a product page.

If its 2 then look at the total volume of visits that reach a product page less the total volume bounce visits on a product page.

If it’s 3 then send an email, I’d love to hear from you.