Engage-Digital

This is an article I wrote for issue 176 of .net magazine in the UK.

I used to be Head of Online Planning and Buying at a London based media buying agency. I was there for 3 years between 1999 and 2002. In my first year our nascent online media planning and buying department experienced a 1000% growth in billings and some growing pains. Of course overall spend was much lower then than it is now as online media was also in its infancy relatively speaking.

Then in 2001 things slowed dramatically. At the time, growth in online media had been fed by new internet start ups with lots of VC capital looking to advertise to help grow their businesses and drive inexorably towards IPO! Additionally it was driven by a growth in interest from mainstream advertisers looking to dip a toe in and check the temperature.

Advertising is often considered a bellwether of economic decline as it’s one of the first things to be cut from budgets as belts tighten and when the slow down came in 2001 billings pretty much flat lined in our corner of the online media world, but other channels fared worse.

Part of the reason why online advertising may have fared better is due to much greater levels of accountability compared with other forms of advertising. Now consider the level of accountability we have with web analytics.

Back then in the early “naughties” web analytics was barely a twinkle in a webmaster’s eye, now it is proudly sitting at the boardroom table.

Not only can web analytics bring even greater accountability to on and offline advertising (if set up correctly) but it also completely opens up the level of business accountability for the website itself. It can be used to drive growth and cut costs through improved efficiencies across the whole spectrum of online communication.

If we are truly staring down the barrel of worsening economic conditions, especially looking forward into 2009 then arguably the worst thing any organisation could do would be to cut its web analytics budget.

Back in January I was working with a client that operates in an industry that is itself suffering but the saving grace for this particular client was their new website which had proved a great success in the face of a generally poorer trading climate.

If economic conditions deteriorate web analytics and the insight that it provides should be safeguarded and pored over with even greater intensity in the same way that normal business reporting and results are.

Analytics seems almost joined at the hip with conversion but improving profits doesn’t just have to be about selling more.

As times (look set to) get tougher improving operating efficiencies can be as important to the bottom line as improving on-site conversion rates. Spending money on valuable resource when it’s being under utilised is effectively wasted capital.

Thinking outside the web server

Improving operating efficiencies of a website is what web analytics was made for but it can also provide valuable information that can guide off-line operating strategies, an example of this would be in businesses running call centers.

Some businesses that have a presence both on and offline, and I refer not just to the “clicks and mortar” (hackneyed expression!) operations but also to others such as catalog retailers, may have found that their offline channel customers behave differently in varying degrees to their online punters. There are also those customers that come through both channels.

For potential customers driven by the web it’s not unusual to see day part website visitor patterns showing two spikes, one at lunchtime and one later in the evening after people have gone home and had supper.

For business that drive response to their call centers the online phone number will most likely be prominently displayed on the site.  A call me back form may also be provided so customers don’t have to waste their money waiting on hold & listening to mind numbing elevator muzac as they move up the queue.

Whether it’s via call me back forms or via the web only contact number, potential customers will pick up the phone at a time that will suit them but staffing call centers is not as easy.

Within in normal working hours businesses can run fully staffed call centers at standard rates but after hours rates for call center staff typically increases by 50% and between 200 & 300% on other “special” days such as Christmas and Easter.

If there is a lull in call center traffic at any point within normal working hours then staff will be under utilised and money potentially wasted. This becomes more acute if call center traffic peaks after hours when either there isn’t the staff to deal with it resulting in lost revenue or there is the staff to deal with it but the associated cost is higher.

To mitigate increased costs through up-weighted call centre staffing at peak times after hours it makes sense to re-coup as much as possible at other slack(er) periods.

Using web analytics to shed light on when web traffic is likely to put pressure on a call center can help improve efficiencies and bring down running costs while keeping customers happy and revenue flowing in.

Where the web is driving a significant contribution to revenue it can pay to keep the web analyst up to speed with issues that don’t necessarily relate directly to the website.

I whole-heartedly agree that visitor engagement is a concept that needs to be considered as an aggregate of several elements covering both data and, crucially for me, context. I also think it is quite subjective.

I have recently done a piece of work for a client who put a new site redesign live at the beginning of January. Looking at the data before and after the live date there were three very clear changes:

1. Performance to the required goal has dramatically increased

2. Average time spent per visit has increased by c. 50%

3. Average pages viewed per visit has more than doubled.

I was only interested in comparing the data within this one particular site and not with others in the same industry since I accept that competitors design their sites slightly differently, may have different goals and different acquisition strategies – and so may view engagement differently. For this purpose I was interested in our little world only and I will try to justify that later.

Looking at the post redesign data I was initially tempted to think that if overall site performance, as measured by conversion to one specific goal, had increased at exactly the same time as a change occurred in the average visit length and pages viewed per visit and that the occurrence of that change was at the time of the site re-launch then it could be said there is a correlation between the three.

In an effort to try and filter out as much noise as possible, I looked at one referring source which has been a constant over the past 10 months – pay per click marketing. I also know from looking back over the ppc performance data in this particular business that seasonality in market demand appears to have a limited impact on conversion.

Looking at just pay per click (from Google only) the results were the same – a marked increase in conversion occurring at the same time as a marked increase in average visit length and PVs/visit.

Theo Papadakis talks about the idea of positive and negative engagement in an article recently posted on Occam’s Razor by Avinash Kaushik. I like this idea and would consider what I have seen here as an indication of positive engagement.

Looking further into content popularity it became clear that the new internal search function had started receiving much more traffic and now forms the backbone of the site’s navigation. This element of the site functionality was given much greater prominence in the new re-design.

So, what can be observed?

1. It’s easy to see that all 3 key changes occurred at the time of the site re-launch (in this respect we were lucky to have such a marked even to punctuate the data)

2. The same behaviour appears to be the case with a single source of referring traffic.

3. The increased conversion, average visit length and PVs / visit appears to be linked to a change in the sites primary navigation

4. Seasonality in the business cycle can in the main be discounted

This all points to the suggestion that visitors who convert tend to spend more time on the site and view more pages per visit. Given that the conversion goal is a positive outcome for us, then a simultaneous increase in average time on site and average pages viewed per visit must also be positive suggesting that visitors are more positively engaged with the content.

What do we do with this engagement?

I don’t propose to use it as an indicator to drive change in its own right. I see it as a “soft”  indicator; I prefer to think of it as a stalking horse. One which will prompt further investigation should a significant change occur. Additionally, where we have other referral sources I would like to use it to help assess relative value.

One final factor that will have to be taken into consideration and which cannot be accounted for so soon after the site launch is the novelty factor of the new site itself. This particular site sees a high proportion of returning visitors and customers, because of that we will have to see if the new re-design has prompted repeat customers and visitors to stay and look around partly out of curiosity. This should be born out in time.

My view is that engagement should largely be considered on an individual site by site basis. That is why I prefer only to look at engagement in the context of one particular site over time. It may be interesting to compare with other businesses but brand recognition and loyalty will most likely skew results to some degree regardless of site design.

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.