Source: Kiwi Flickr

This year was the third time I’ve been to Webstock. I go for a few reasons: to visit Wellington!, to get perspectives on web design & web development that I wouldn’t normally, to let my brain think about things other than digital marketing and to catch up with people.

Of course, it isn’t easy just to turn off from the digital marketing side of things so I spend a lot of my time at Webstock thinking about the impact of changes & future trends to the digital marketing industry.

Here’s what I learnt online businesses need to be doing this year:

• Iterate. Listen to your customers, watch your analytics, learn what needs improving and optimise like a crazy person. The website that is most agile will win.
• Don’t be late to the mobile party, be early. How does your online audience want to engage your business via mobile? Does that exist? Is there a business case for it?
• Be wary of “gut feel” or “I just know” interpretations of data by your staff or your third party providers. Expect empirical evidence that backs up that gut feel.
• “If you review the first version of your site & don’t feel embarrassed, you spent too long on it” – Reid Hoffman, LinkedIn.com
• For Barack Obama’s US presidential campaign, his online team were tracking how dollars spent on online ads were turning into dollars received via fundraising. If a campaign that complex can achieve it, no-one has an excuse for not knowing their ROI from online spend.
• Jeff Attwood’s description of social software was very good: “tiny slices of frictionless effort, spread across an online community”. A good reminder that to leverage user-generated content you need your users to want to contribute and make it super-easy to do so.
• I thought Daniel Burka’s recommendation that “subtraction is iteration too” was a good reminder. Don’t be afraid to subtract

The talks & presentations are going to be made available in the near future so keep an eye on the Webstock blog for those.

You can also follow Webstock on Twitter: @webstock.

Do you know how well your online marketing tactics are performing?

How much does a conversion cost from your pay per click campaigns, search engine optimisation efforts or your email marketing campaigns…? – Do you know the answer?

Most Marketing Managers would answer yes to this question. For example: “Our PPC campaign costs us $6 for every sale”. For the majority of organisations, the data would come from Google Analytics or another web analytics platform.

But what does “$6 cost per sale” really mean?

You would probably agree with me that the data provided from any of the major web analytics platforms (including Google Analytics) can actually be quite misleading. Especially if data is used from analytics software that is installed using the “default” parameters, without correct configuration and expert interpretation.

Interpreting Analytics Data

Let me give you an example: Let’s assume your website sells Sony TVs.

A searcher on Google searches for a Sony TV and finds your Google Adwords PPC ad. They click on the ad (and if your PPC account is set up correctly) they land on your website and are presented with a range of relevant Sony TVs. They find the “SONY Bravia KDL40X4500 model”, they like the look of it and decide they want to buy it. Let’s assume they do this on a Monday.

But before they purchase, let’s assume the consumer wants to do a bit more research the next day on other websites. In the end they find that the product is cheaper on your site and that your delivery and returns terms are more favourable. So they decide to buy the product from you.

However, this particular consumer didn’t bookmark the product page – and can’t remember what your web address is! But they do remember what your company is called. So they type in your company’s brand name into Google, and click the top natural listing. They navigate around your site, find the TV that they liked, and finally, purchase it.

Here’s how that process would look:

The default setup on most analytics packages would register the sale under the branded keyword clicked in the natural results. Is this fair? What about the paid search click that happened first?

By comparison, the conversion tracking option within Google Adwords would attribute that same sale to the click on the paid search ad. The data within Google Adwords and Google Analytics would fail to match up and there is a strong possibility that sales would be “over-reported” using Adwords data only. The reason behind this is due to the differences between first-click and last-click conversion attribution.

Google Adwords Conversion Tracking

Google Adwords employs first-click attribution. If Google sends a visitor to the website because the visitor clicked on that paid search ad, Google Adwords would always attribute any sale to that initial click. The cookie is not over-written and even if Google Adwords was further down the buying cycle, it would always attribute a sale to the click as long as the sale happens within 30 days of this click.

Google Adwords employs post-click tracking, which is initiated when the user clicks on a paid ad that has been assigned a tracking URL. From that moment, a cookie is stored on the user’s machine and if they visit the website’s complete page within 30 days, the Google tracking pixel meets with the cookie and reports back to Google Adwords which click brought the sale, and on what date.

Google Analytics Conversion Tracking

Google Analytics (and the majority of the other analytics packages), as a default, employ last-click attribution. This means that the cookie will always overwrite itself based upon the last referrer to the website. This means that no-matter what medium referred the latest visit to the website, the sale would always be attributed to that medium (other than direct – Google Analytics doesn’t overwrite direct traffic). This means that the website that initially referred the visitor gets no credit for the initial introduction.

This is where first-click and multi-click attribution comes in.

First-Click Attribution

For a Google Analytics installation, First Rate has produced a product called “Acquisition by Referrer”. This product changes the way data appears in Google Analytics and attributes the sale to the first click the visitor made (much in the way that Google Adwords would record it). In the above case, Google Analytics would record the sale as a coming from the PPC advert, rather than a branded organic search phrase. (Note: The script records both first-click and last-click – it doesn’t stop the default nature of GA recording last-click.)

Another interesting thing to note is the cookie length set by Google Analytics. The cookie that stores where the visitor came from, what link in an email was clicked on (it is possible to tag the links to tell Google Analytics about the email campaign and each individual link), what keyword was used if they came from a search engine and also other data such as screen resolution and browser language used when the website was accessed – all of that is stored in the Google Analytics UTMZ cookie.

The UTMZ has a 6 month life-span. This is adequate for most websites, but for some websites it may be necessary for this period to be longer, or potentially shorter. First Rate can recommend a suitable cookie length to suit your company’s business model (eg. time it takes for customers to make a purchase decision or a cookie length that aligns with your own understanding of your customer’s loyalty/lifecycle).

Multi-Click Attribution

For the serious analysts out there, it is possible to assign multiple values within the JavaScript employed in the implementation of the Google Analytics tracking code.

The implementation of multi-click attribution is quite tricky and not for the faint-hearted. It requires JavaScript programming to draw data out of the website and send it to Google Analytics within a field reserved specifically for advanced reporting.

In addition, because of the overload of data, the results will become illegible within the Google Analytics interface. The best way to make sense of the data would be to export the data into excel and then use pivot tables to analyse the data.

A reason why multi-click attribution is becoming more popular is due to the ‘weighting’ of visits to the website. How much weight should the first click have, then a potential second, and what about a third or fourth?

Of course we can go another step further – what if you have a traditional ‘bricks and mortar’ store. The TV example above is a perfect example – a visitor goes online, researches the product that has the required specification, and then goes into a store to look at it, or even a competitor’s store! The salesman tells them about the TV, gives them a demonstration that could never happen online, and then the shopper returns home, goes on the net and buys from your website. How much emphasis should be placed on the in-store visit, but more importantly – how can we measure it? How can an analytics package possibly tell that the customer went in-store? At the moment, we simply can’t.

Website Analytics Recommendations

First Rate suggests initially using first-click attribution to see how the data is affected to get a ‘clearer’ picture as to how each marketing is acquiring traffic and sales (and at what cost!)

As a Google accredited partner (GAAC), First Rate can certainly help with custom Google Analytics implementations, please do contact us if we can assist in any way.

Google Analytics is a comprehensive website tracking and analysis tool provided by Google. There are a number of other tools out there that can provide similar information about your website visitors, some are free and some you have to pay for, but more and more website owners are choosing to use Google Analytics because it is free, easy to use, and it provides all of the information that most webmasters could ever need.

Plus they keep making it better and better. Have a look at this blog post from the Google Analytics team that lists the changes they made during 2009.

Here I just wanted to discuss two of the new features that have been added recently.

Analytics Intelligence

Google Analytics Intelligence is a new beta feature that can be used to automatically alert you of any significant changes in visitor behaviour, so that you can focus your analysis on understanding the causes behind these changes and making informed strategic decisions around future changes.

For example, say you have just launched a new TV ad that directs viewers to your website. You might reasonably expect Analytics Intelligence to alert you to an increase in both Visits and Pageviews, but a wealth of other useful information may also be uncovered, i.e. if you see a large increase in Bounce Rate and drop in Average Time on Site, this might indicate that many of these new visitors aren’t finding what they expected to see on your website.

Armed with this information you might choose to make some changes to your website landing page so that it better fits the expectations of visitors who have just seen your TVC.

Analytics Intelligence will automatically look for a wide range of traffic pattern changes, but if there is something specific that you want to watch out for, you can also create your own custom alerts.

Annotations

Annotations allows Google Analytics users to write (campaign-specific) notes directly on the over-time graph, which makes data analysis much easier later on.

For example you could embed notes such as:

• Launched new pay per click campaign using Facebook advertising.
• Enabled Google AdWords content network campaign.
• Search Engine Optimisation project started / ended.
• Search Engine Advertising was changed to focus more on the company brand in ads.
• Webserver down for 15 minutes due to crash.

Notes added directly into the Analytics data allows you to gain more meaningful insights from the Analytics reports, and helps you understand the reasons behind the peaks and troughs in visitor usage or sales patterns much more easily.

Annotations were announced in December 2009 and are being gradually rolled out to Google Analytics user accounts, so if you can’t see this feature in your account yet, don’t worry it should be available soon.

How Can First Rate Help?

First Rate is the first Trans-Tasman Google Analytics Qualified Company (GAAC) and has a team of Google qualified consultants who are experts in installing, configuring and analysing the data provided by Google Analytics. Contact us, we are ready to help.

So, Google Analytics reports the search keyword that was used to find the website – you can also see the number of sales or other conversions that resulted from that query. However for Adwords traffic the keyword that is reported is the “bid term”, the keyword that is targeted in the Adwords account. This is different from the real search term that people used in their search, because Google matched the real term to your bid term using “broad match”.

It is possible to get the real search term to be shown in Analytics, and therefore to look at the performance of the real keyword using the metrics available within Analytics, (e.g. Bounce Rate, Time on Site, Goals and Ecommerce). This is done using a custom filter for Analytics. This will rewrite the campaign term to show both the bid term and the real search term in brackets:

As you can see, often the bid term is the same as the real search term, but sometimes it is not. In the example above, the 4 entries for ‘Clinicians’ would normally be combined into a single entry for that keyword.

You can use this information to adjust your Adwords campaign, for example you can add additional keywords into the Adwords account (e.g. “new zealand clinicians” shown above) and depending on the ROI of the keywords you could adjust the bids or even prevent the ads being shown for a particular variant if that didn’t convert well.

Instructions

First of all, remember, as with all filters for Analytics, make sure you test the filter out on a test profile, and always have a Raw profile to which no filters are applied.

This requires 2 custom filters …

1. This filter restricts the data to CPC / PPC traffic only, using a Custom -> Include filter. If this filter were not in place then natural search traffic would also have a second keyword added, and this would always be exactly the same as the first one. The details are:

Filter Type: Custom Filter -> Include
Filter Field: Campaign Medium
Filter Pattern: (cpc|ppc)

2. This filter extracts the real search term out of the referrer string and also extracts the campaign term (the bid keyword) and then it writes both the bid keyword and the real search term back into the campaign term. The details are:

Filter Type: Custom Filter -> Advanced
Field A -> Extract A: Referral: (\?|&)(q|p|query|search)=([^&]*)
Field B -> Extract B: Campaign Term: (.*)
Output To -> Constructor: Campaign Term: $B1 ($A3)

Contact First Rate to maximise the return your organisation gets from Google Analytics.

So what does it take to win the SEM war against your competition? Extensive keywords lists? Award winning creative? Clairvoyant bid management system?

Keyword lists, creative and bidding technology are all fairly well understood and relatively easy to deploy. So, if this is the case, what is to stop your SEM strategy deteriorating into a bidding war against your competitors where the choice is to either buy traffic at a level that is not profitable or have your ad pushed down into obscurity? 

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