I had a recent poser a week or so back for a retail client – How should their sub-navigation be ordered on their website? I wanted to get some thoughts down on this, as long, unstructured navigations are something that highly annoys me on websites - especially ones I’m looking to shop on.

Retail navigation ordering typically follows the standard across the web – by key ‘type’ overall as a main choice, then breaking down sub types of this key type.  For example, a clothing retailer would typically break down their navigation by Gender as a main, and then clothing types within their sub nav (jackets, trousers, etc).  Other products similarly follow this fashion, usually broken down by their main type first, and then split out into smaller divisions within the type currently browsing.  In some cases a third level might be used.

This is generally regarded as a logical way to browse, and works well for the majority – you can quickly refine your browsing to specific ranges, and then filter and refine further as you require.

In terms of the sub navigation (second level), this usually ends up being the most comprehensive nav, typically having anywhere from 10 – 20 options within the sub-nav.  The issue that I have with most sites is their ordering of these options – nothing annoys me more than random ordering!

Random ordering your navigation for your website helps no-one.  It’s a bit of a personal issue for me, as it is such a simple fix and should be common knowledge; there’s no excuse for not delivering.

Randomising your nav provides absolutely no benefit to your visitors whatsoever – you are asking visitors to spend longer on your site, increasing annoyance and spending more of their time looking at your navigation instead of looking at what they want to buy. I’m really not buying the argument that ‘the longer they spend on the site searching, the more they will spend’.  It’s bad usability and bad practice.

As far as I’m concerned, the only ordering that should be used across the web for navigations are a choice of:

• A – Z Product Order
• ‘Popularity’ of Product (or relavancy)
• A combination of both

It’s pretty straightforward really.

• A – Z allow visitors to very quickly and easily scan the product ranges on offer.  In seconds, if they are looking for a particular product range, they can instantly jump around the list to find what they’re after.  It’s the most logical ordering method and one I think which should be adoped by all sites as a minimum requirement – no excuse!
• ‘Popularity’ of Product (or relevancy) lists most popular or relevant ranges closer to the top of the navigation, filtering out to smaller ranges and misc. items down the list.  I think in cases this can work well – if your navigation is quite short (maybe less than 5-6 items) or you are a specialised retailer in one or two particular products but sell accessories also, then putting your key ranges at the top and your accessories lower down can work well in some cases. For long navigations though, where the range is wide, structures like this can become horrible to scan through.
• A combination of both.  Usually the best method, but might require a little more work (whcih means hard cash spent on your website I’m afraid).  Listing one or two key product ranges first in the list (including special offers here is always a good choice), and having these then underlined or shaded differently before you list the whole range by A – Z can work really well.  It drives interest to the ranges you want, while providing a really good overview of your product range.

If the budgets there, I’d recommend option 3.  It gives more promotion to ranges you want to promote, while providing a nice, user friendly, structured nav for everyone.  However, for me, option one should be a minimum for all.

Some examples from the wild:

New Look

New Look order their nav in a related but random order overall.  At least that’s how it appears to the average user.  They win points for listing their new and closing lines first and second, meaning the majority of visitors will be exposed to these, and I’d chance that they are in the top 5 most viewed areas of this nav.  They’ve also dropped Sale in at the end (typically the first and last sections get good exposure) which is a good decision, however, I would recommend trying it at the front and seeing how it does.

They break down main clothing sections by type, and though they are grouped, I don’t think they’re that easy to browse.  I would recommend a feint green line once the main types begin, with them then ordered A-Z.  It could easily be tested for performance, eh?

Topshop

The groups work well, but their ordering can be a little confusing. They’re ordered by type within the groups, but I don’t think this is apparently obvious.  Sorting these by A-Z and separting out further (tops / bottoms) would make it even easier to take in I think. Worth a try!

TopShop get a little closer to the Holy Grail, but still not there yet! They adopt a grouped navigation, which works well with different types separated.  The also include sale and last chance items in their own group, though at the bottom of the page for some reason.

The groups work well, but their ordering can be a little confusing. They’re ordered by type within the groups, but I don’t think this is apparently obvious.  Sorting these by A-Z and separting out further (tops / bottoms) would make it even easier to take in I think.

LittleWoods

Littlewoods do a very organised, logical approach, with a breakdown by group, and then all products broken out A-Z.  This works well, but I think in this case the large product section could probably have done with being grouped out further – it can be a lot to take in all at once.

It does however get a lot of points – by maintaining a consistent A-Z order by Product, it does make it quite easy to scan the overall list and find what you’re looking for.

I’ll be attending another event shortly – IMRG’s Usability Workshop taking place on the 8th July. It’s taking place in London, so I’ll be coming down to the big smoke again in a couple of weeks.

It will be covering off “methods required to build-in good usability practice when considering site enhancements, changes and new technologies.” Hopefully it should provide some new and interesting insights, I’m always welcome to hear new usability practices and methods, especially regarding the implementation of technology developments – an area that can easily be overshadowed by th excitement  of building in new site features.

If you also plan to attend let me know, it’s only a half day event, so I’ll also have the afternoon free if anyone wants to meet up in or around London.

Implementation

Implementation of analytics can be achieved through two main methods, each with their own advantages and disadvantages – via a page ‘tag’ solution (such as Google Analytics, HBX analytics), or through server log file analysis (such as ClickTracks or Affinium NetInsight).

Page tagging provides a relatively quick implementation, dropping a provider’s specified tag onto pages within the website. At its most basic level, this tag will then record and report back customer data to an online system, which you can access. Google Analytics provides a very good solution for this – more so because it’s free – the only cost to you being implementation. More advanced tags can be added where online purchases take place, and the system can be setup to provide you with conversion rates, bestsellers, and revenue generation across pages – all in all quite a thorough tracking solution.

It does however have its limits in terms of reanalysing data and ‘profiling’ visitors – if a tag isn’t implemented and specific information is required then you can’t go back into the data and reanalyse to dig deeper into the information. Generally this tracking would only be recorded going forward, so it’s important to perform a thorough audit of all the tracking and tagging required initially before implementing page tags to ensure no information is missed.

Server logfile analysis can provide more flexibility and depth of reporting, but can take more expertise and time. Database driven log file tools physically analyse the logs generated by the web server each day, compiling the information into a database which can then be manipulated. These logs are stored physically, so data can be queried and filtered, segregated and compared multiple times – once it is in this database format it can be manipulated as required and across multiple tools – something which is difficult for tag solutions to do. This is particularly useful when doing a detailed site analysis as filters can be constantly changed and re-generated as the analysis evolves and more issues are discovered.

Performance Must be Measured

Any company that trades online should have some tracking implementation at a minimum – in the same way shops and superstores change their layout to increase sales and promote product lines. With good analytics a site can be constantly optimised to drive conversions – without analytics, you will lose market share to the competition.

With so many good solutions now on the market such as Google Analytics, there’s really no excuse. Simple on site optimisations through results analysis can boost online sales and provide some informative insight into how your site is being used. Even if making a few simple changes increases conversions by 0.1% – on 100,000 visitors a month that’s an extra 100 orders @£65 AOV = £6,500) – a fraction of setup AND analysis costs.

In our experience, online activity is generally not being tracked as well as it could be across the majority of online ecommerce sites – and those that do have tracking, have it implemented incorrectly or at a very basic level. Usually in these cases, a small amount of work can provide so much more information and insight into how a website is being used – improving performance and sales as a whole.

Since writing this article, Google Analytics has seen some great improvements.  The addition of segementation for one, has been highly valuable and has brought it up to speed with many other analytics packages, allowing detailed analysis of specific visitor types to be analysed.  It’s such a useful tool I can’t recommend it enough – if you don’t have it on your site, implement it now!  For more info on the page tag vs log files debate, see my previous article.  Also, since doing this, HBX to my knowledge has ceased to exist, and has since been bought up by Omniture.  Expect to see some big developments there; it wasn’t a groundbreaking tool but was very straightforward and simple to use.

The morale of the story? If you’re in the business of having a website and using it for any customer/visitor activity – get some tracking on it! Would you open a shop and not be aware of how busy the shop is? How many sales you made? How popular it was? Doubtful!

Previous Blog Post – What to measure Online & How – Part 1

I’ll be exhibiting at the Travel Distribution Summit 2009 for the next two days (over Tuesday & Wednesday).  I’ll be going over Travel website optimisations we’ve done in the past, looking at some new sites, and hopefully helping a lot of travel companies convert more customers online.  We’ll also be covering SEM, SEO, etc, the whole online marketing mix.

I find travel to be an interesting industry to have moved online.  It’s seems like finding your own holiday, doing the research, reading the reviews, finding the ideal time to go at the ideal price can all be fun, and lots of people now enjoy doing all this part themselves.  The problem frequently comes when going to make the booking.

Too many travel companies simply seemed to just upload their entire booking system to the web when they started out online and expect their customers to know how to use it.  And some of them, quite frankly, are just awful.  Over the years, things may have been changed or bolted on, and some of them have got this right, others still have a way to go.  It’s fundamentals are still similar to retail, and I’ve found that experience across these two sectors really can mirror each other sometimes.  Website optimisation works really well for travel – it’s usually one area where looking after customers pays off dividends, as service is a large factor in a considered purchase of such high value.

It’s located at the Business Design Centre, London.  For further details check out the website.  We’ll be exhibiting at Stand 42.

Last year I had an article published in Catalogue e-business magazine (July 2008) under the ‘ask the experts’ feature; the topic being:

“What ecommerce marketers should be measuring & how to do so”

Over the course of this week, I’ll publish the content of that article here in two parts, with some extra comments and observation added.  It at a quite basic level, but provides a good introduction to measurement & analytics for marketers new to the world of online.

Part 1 – Why Measure?

As is being realised more and more in today’s technology driven, fast paced business world – the web can be a highly effective marketing mechanism. It allows seamless communication and interaction with customers on a personal level, allowing companies to market to their customers in new ways. Not only is it effective in its execution of campaigns, but an element often overlooked by many companies new to this form of marketing (or even in some cases to those who have been doing it a while), is that with the right implementation, practically every aspect of its performance can be accurately measured. This in turn, gives marketers a robust feedback loop to their campaigns – the likes of which has never been seen before.

Online marketing is one of the fastest growing marketing sectors with more and more companies leveraging to this form of marketing. In the UK alone we spent £4.2 billion to July 2007 compared with £2.34 billion in the previous year . It is also becoming an increasingly competitive space, and as the playing field is level, even smaller companies with the right strategy and implementation can outperform some of the bigger players online. The number of households online is growing (61% of UK households in 2007 – 7% increase on 2006 ) as well as the audience widening (ABCDE ) – providing essentially a consumer ‘playground’ for marketers to test new ideas and campaigns. Unfortunately with this great opportunity also comes many potential areas to get it wrong – all of which may have a negative impact on a business.

Increasing competition means that pay per click advertising becomes more costly, natural search and affiliate marketing become more important – so we must work smarter not harder. Analytics is fundamental to any campaign; ensuring that whatever media investment we are making, it is the right one.

Establishing Measurements

In terms of measuring, with all the options online gives, marketers must first decide their key ‘primary’ measurements – those that are most important to them, their relative market, business and growth strategies.  These measurements then give marketers and the team as a whole clear direction.  Are they trying to migrate more offline customers to the web (potentially via web incentives and promotions)? Increase average order frequency and encourage repeat visits through loyalty programmes? Campaigns can be performance measured and controlled throughout the process, ensuring the optimum response is achieved and adjusted to compensate for.  These are direct marketing principles effectively applied to a retail environment 24×7.

At its most basic level, measurement must include key top line metrics.  Overall visitor numbers, conversion rates, frequency of purchase, time online, and page information (interest, entry & exit points) can provide enough information to understand how a site is performing, and also establish some KPI’s.  These can then act as a baseline going forward, and monitored regularly based on changes to a site or marketing activity.  Entry and exit points can give a good insight into where visitors are landing on your site through search, and also highlight area that maybe potentially losing too many visitors.

One thing to remember – measurements need to be decided before undertaking improvements, campaign activity etc.  An initial baseline needs to be set and a control measure taken before anything is undertaken in order to measure improvement!

Metrics you should be measuring (at a minimum):

• Unique Visitors
• Conversions (could be orders, sign ups, enquiries, brochure requests etc)
• Online Conversion Rate
• Sources of Traffic (Referrers)
• Referring Keywords (What people are entering on Search Engines to find you)
• Key points visitors Enter the site
• Key points visitors Exit the site

At the advanced level, key metrics can be filtered and manipulated as required – how long visitors spend online before a purchase, optimum number of product views before a purchase, the common customer journey through the site (and performance analysis of each stage), performance of onsite keyword search and other functionality, detailed analysis of the purchase process  – even going so far as to measure which precise form field was last filled in before a visitor left the checkout process.  All of these metrics can be used to keep tight control over things like bounce rate and cart abandonment, and ultimately ensure purchase conversion is at maximum.

In any recruitment campaign our objective is to get that ‘first order’.  Consequently our strategies include landing customers directly onto product pages in order to minimise the number of clicks to purchase and checkout.  These customers no longer enter at the homepage but throughout the site.  A comprehensive analytics setup is the only way of determining (in the event that the campaigns don’t work) as to why they don’t work.

Once these metrics have been established, more detailed marketing measurements can be taken into account and applied – segregating visitors by channels (direct, advertising, natural search, email, etc) and measuring performance of these groups individually.  By looking at these different channels, a site can be analysed specifically for a certain type of visitor – you may find for example that ‘direct’ customers find your homepage great and view three or more products, but those who come in via your non-brand natural search content suffer high rates of drop-off after one or two pages as their expectations are not being met.

Part 2 coming soon…