Paid video ads work in a very similar way to standard search adverts. Much like AdWords, you choose your ad text in the form of a video description, choose the search terms that you wish to bid on and specify maximum cost per click values and budgets for your campaign. Instead of being taken to a conversion oriented landing page however, they will watch on page, play the video on your channel page or view on a specific URL.  It is therefore vital to analyse and optimise these campaigns in order to maximise profit. The Analytics tab can be found on the ‘Video Manager’ page on YouTube.

Know your audience:

In any advertising campaign you must identify the demographics of your customers to better target your ads and videos to them. Within YouTube Analytics on the ‘View reports’ drop down, the Demographics tab gives an excellent break down of the age, gender and location of viewers.

In the example above we can see that the largest group of viewers for this particular video are male, between the ages of 35-44 and from English speaking countries. With this in mind it would be wise to tailor videos for a middle aged, male audience. These results may not be what you expect and can help to expand your options. For example, if your top locations are not English speaking countries, you may consider translating the video to further appeal to that audience. It is a safe assumption that optimising for your demographic in this way will improve the campaigns performance.

Analyse your traffic sources:

It is now easy to see which sites your videos are being viewed on (whether on YouTube or embedded elsewhere) and which search terms were entered for the video to be displayed. With this information, viewed on the ‘Traffic sources’ tab, you can gain insight into the most popular search terms, gain ideas for new keywords to add to your list and see which keywords you should be bidding more for.

In this case, drilling down into the ‘YouTube search’ traffic source displays the top search queries that have led to a view. With this in mind, you know that ‘skydive queenstown’ is the best keyword on YouTube search, accounting for 13.5% of the views. It would be wise to review the bids on this and similar keywords to increase exposure.

Improve user engagement:

A particularly interesting new feature, available on the ‘Audience retention’ tab, allows you to see exactly where viewers are dropping out. This can be used to see which sections of videos are holding the attention of the viewer and are therefore more likely to lead to a conversion and which sections are leading potential customers to leave. In the example below we can see that at 00:48 seconds through the video, user interest drops dramatically. This is a clear indication that this section of the video should be altered or replaced, as the all-important call to action may be given at the end of the video which will be missed because this section failed to keep viewers interested.

Along with the aforementioned features there are a number of other useful metrics within YouTube Analytics which can be taken into account when analysing and optimising paid video campaigns. By testing different videos, ads and keywords it is possible to improve user engagement, better understand your audience and increase your profit from PPC while improving brand awareness.

On first look, the mountains of data coming through your PPC Reports can be daunting for anyone. Excel is a great tool for making sense of the masses of PPC data available from your sources and bringing it to life. Excel is the board you can use to tame and explore that mountain, as well as carve your epic lines of analysis. Better yet, a well-constructed, all-mountain board of a spreadsheet is a great way to demonstrate the success of your hard work to clients.

Here are 3 practical tips and techniques to get a PPC Account Manager started and making the best of what Excel has to offer.

1 | Correct Your Stance For Beginner Users

Compatibility is essential for all clients. And as you wouldn’t set an aggressive stance for a grommet, don’t go full throttle on advanced 2007 formulae until you know all users are ready. The differences in the functionality of Excel versions mean that there are several formulae that are valid in 2007 but will return #NAME? errors when the spreadsheet is opened in 2003.  See our previous blog PPC Using Wacky Excel Spreadsheets for more details. Also, simply because your direct contact uses a newer version of Excel does not mean that their colleagues do, and you will want your great work shown throughout the whole company. Best practise is: save time and play it safe, use only the formulae available prior to 2007.

If you do decide to use newer formulae, make sure that you are familiar with techniques valid in older versions of Excel that can replicate the functionality of your spreadsheet should the time come that you need to deliver an alternative.

2 | PPC Account Structure Is An Excel Tool

Tempting though it may be to name your campaigns after your epic hits such as Big Shaq and Raptor’s Ride, it can soon become impractical. Excel has a variety of text functions that can manipulate your data and help create some super useful fields within your data.  This gives you the opportunity to use the names of your PPC Campaigns and AdGroups to create quite intelligent filters and charts in your spreadsheet. For example, if a Campaign is running in London, Leeds, and the rest of Yorkshire and you can separate Product and Brand AdGroups, using some unique characters and some simple text formulae will help you create criteria for IF functions.

Given this client I’d create the following structure and apply these formulae in Excel:

With some very quick text manipulation using TRIM, LEFT, RIGHT, LEN and FIND, Excel is capable of giving your report data rows some useful attributes or tags. The result is a very practical set of criteria which can be used in your reporting in formulae like this:

-          =SUMIF( Location , ”Leeds”, Impressions ) which would return 2,000,000

-          =AVERAGEIF( Type, ”Brand” , Clicks ) which would return: 100,333

The great thing about applying this type of naming convention is that it is becomes very easy to create and display data, in both tables and charts.  Furthermore, using this method allows you to simply construct advanced tables and charts which are very easy to adapt and expand as the scope of your campaign grows.

3 | Spreadsheets at Warp-Speed

A long-managed and complex account is bound to accrue masses of data and eventually your spreadsheet will grind to a halt like a chairlift in a high wind. Good news though buddy, there are several tricks to improve your spreadsheet in order to keep it fast and usable in the long-term.  A bonus though, is that by focussing on calculation speed you can ensure that when the spreadsheet is run in older versions of Excel it remains sharp and sleek.  Here are just a few tips you can follow:

• Referring to whole columns in a calculation is slow.  Where possible, create specified ranges with absolute cell references or dynamic ranges using COUNTA and OFFSET.  This reduces the amount of data Excel will have to evaluate when calculations change. But do use caution: if ranges from the same worksheet of an equation do not have the same number of rows, formulae will either omit data or return an error.

• Use numbers where possible and use TRUE() and FALSE() in calculations, Excel handles numbers much more quickly than text.  Try to create IF calculations where number conditions and logic is used.

• If you can avoid using volatile functions such as TODAY(), INDIRECT() and INDEX(), do.  For most cases there are quicker alternatives such as CHOOSE(). However, if you have to use volatile functions, calculate them only once and have all other instances refer to this single cell as a value.

• Database functions such as DSUM, are great at calculating formulae on large amounts of data very quickly and allow you to calculate IFs with multiple criteria even in Excel versions prior to 2003, on top of which they are very simple to set up.

Summary / TL;DR:

Excel is the perfect tool for most PPC duties, most-of-all reporting. Make sure your calculations are compatible with all your users’ and clients’ versions of excel, taking care of the major differences between 2003 and 2007. Good PPC Campaigns and Account Structure can give you a head start in designing your spreadsheet tables and charts.  And finally, keep it all-mountain; simplicity will deliver speed and compatibility.

By way of an example, a Hotel Chain owns multiple Hotels of various sizes across the UK. They all run adverts every day and a conversion is counted when someone books a room in the Hotel. We can parameterise the Hotels by which Hotel it is and which day of the week the adverts are appearing. We would expect that each Hotel would do proportionately well on any given day of the week. E.g. if Hotel A converts twice as much than Hotel B on Mondays then we could expect that it did so on Tuesdays as well, without any more information to sway our decision (maybe Hotel A is in a town with a regular Monday tourist event that would attract more business).

The key statistics we can investigate with this method are Impressions, Clicks and Conversions. It can be applied further but caution must be exercised. Suppose we want to know if Hotel A is getting as many Impressions as expected on Mondays – what do we do? Well, since all the Hotels can be differently-sized, we would like to know how all the other Hotels perform and compare Hotel A’s performance with that. We therefore take for each other Hotel the number of Impressions on Mondays divided by that Hotel’s total number of Impressions. We then average those daily Impression-shares, and can see how Hotel A’s Impression-share compares. If it is more then we are happy with it and if it is less then we may be unhappy with it.

In the example above, we see that Hotel C in London had 20,088 of its 164,931 Impressions (about 12.18%) on Sundays, but Hotel B in Leeds had 6,399 of its 46,896 (13.65%) and Hotel A in  Birmingham has 17,481 of its 137,936 (12.67%), so it appears that Hotel C may not be performing as well as expected in terms of Impressions on Sundays.

This isn’t the whole story though! If we get 9,990 Impressions but were expecting 10,000 then we probably don’t need to worry too much – how do we know when we are really receiving a bad number? We need to get an indication of not only how many on average we should be expecting, but how spread around that average the data is likely to be (what Mathematicians call “Variance”).

***Mathematics Aside – We can model the aforementioned statistics as Poisson Processes (Homogeneous on each day, Non-Homogenous taken across the week) since they are independent discrete events occurring over continuous time intervals with a constant average rate. A random variable which is the sum of independent Poisson random variables is itself Poisson (with parameter equal to the sum of the individual parameters), and (Raikov’s theorem) a Poisson random variable which we know is the sum of independent random variables must be the sum of independent Poisson random variables.***

The Variance for one of these statistics is equal to the average value itself, and it is a mathematical fact that 99% of the time a result will be received which is within three times the square root of the Variance away from the average. Any result outside of that range is quite a surprise and we should be aware that this is actually a good or bad result.

So how do we use this information? Well, that is another question altogether really. The mathematics shows you when something is surprising, but often it is not because something out of the ordinary has happened. Most of the time it is the case that you simply overlooked something, or made a bad assumption. Hopefully performing this analysis will help you to get a better insight on your own accounts – Happy optimising!

Impact

Social media has been growing in power over the past few years and although it is still unclear how it directly affects your brand page’s SEO, Google and the other major search engines are factoring it in more and more with each algorithm update. I’m sure many of will have noticed that your SERPs are noticeably different when logged in to Google+, as shares and +1s from your connections help to boost certain pieces of content for relevant keywords.

Fundamentally, it is these shares that matter most to those seeking an audience. A post that has been shared numerous times by individuals with large spheres of influence should in theory prove that it is of good quality, interesting or funny. In order to track these interactions, social media platforms Facebook and more recently Google+ now offer updated data services by which users can see a wide range of information about how their content has been shared. Twitter is yet to provide any sort of statistical data but has also received an update to its service over the last few weeks.

However, while it’s interesting and fun to have a look through the numbers and see how your content spreading, there is still some debate as to how useful the data actually is for businesses looking to act upon it. As these new developments have been in place for a few weeks, now would seem an appropriate time to weigh up the pros and cons.

Facebook Insights

There was a big fuss over the last Facebook update. Its complete revamp of the timeline and other user interface properties caused the usual outcry about change and was followed by threats from members about leaving the site. In reality few probably did, especially when those with brands began to explore the new Insights tab on their page. The update allows brands to extract physical data in the form of a .CSV or spread sheet and use it to analyse brand visibility and their ROI.

Page owners are now able to see the demographic of the people that are liking their pages and sharing their posts. Posts can therefore be tailored to the demographic that is interacting on the most regular basis. Conversely, if content that was aimed at one age group is actually being picked up by another, future posts can be adapted. The impact of events that a brand is involved in can be tracked directly via the timeline shown below.

The frequency that people are shown content over the week can also be accessed, which allows the owner to view both unique and previous visitors to the site side by side. This is a distinct improvement in accuracy over their previous service, which only offered one impressions figure. Also the source locations of likes, visits and people talking about your brand have been added. A brand could therefore use this data to geotarget posts for a select group of their audience.

However, for all this useful data, the service lacks the details of actual individuals interacting with your page and how those interactions are then passed on. The nearest you get to this stat is the percentage ‘virality’ of each post. This is an area which Facebook will surely be quick to catch up on, with the potential of the Google+ metrics system being realised.

Google+ Ripples

As noted by Casey on the SEOmoz blog last week, Google+ Ripples feature went largely unnoticed when it was launched almost three weeks ago. However on closer inspection, it becomes apparent that this is a tool that brand owners and social media execs should not be overlooking. Just like a dropping a stone in a pond, Google+ tool places the source at the centre of a visualisation and then displays how the content spreads throughout the social network in real time.

Let’s take this post by Will Wheaton on the eviction of Occupy from New York’s Zuccotti Park. Its Ripples page can be seen below, accessible on G+ by clicking the drop down menu to the right of the post itself. The most recent and total number of shares statistics can be seen at the top left, above the visualisation. The graphic itself shows how the post has been shared via arrows to each user doing the sharing. Circles around the arrowheads indicate that particular user has a sphere of influence that people within his connection group are sharing the same post within. You can zoom in on each of these sections to see the individuals within these groups.

Below is a very cool time line feature, which allows you to playback the sequence in which the post was shared and a graph showing the peaks and troughs of sharing frequency over time. Finally, you can see the main influencers, i.e. users with most re-shares, a few stats on how the post spread and the different languages it was shared in.

There are currently a few limitations to the Ripples feature though, detailed by Ryan Crowe. First off, the post has to be public in order for you to view its Ripples. They also only date back to August 31^st at the moment and you can only access the Ripples of a post if it has been publicly re-shared once. You are able however, to re-share a Ripples page by linking to it.

The main advantage of this Google+ feature for businesses over Facebook Insights is obviously the ability to view the individual main influencers of content. Brands producing content can actively hunt for shares via certain highly influential users. If they don’t already have a connection with the individual they can look to build a relationship with someone who is active within the desired user’s group of connections. This could be done through LinkedIn or any other contact info on their page.

Conclusions

In short, Google+ appears to have one-upped Facebook Insights in terms of how actionable the data is, although it does lack a downloadable option. Whilst brand owners have been able to track social interactions via Google Analytics for some time, these new updates have opened the door for increasingly targeted social activities.  As social media becomes more and more influential to SERPs, brands will need to be completely switched on to maximise their impact.

This week Google have made a significant change in the way their search engine will work. It is a change that is likely to affect every digital marketer – not just those using Google Analytics for insight into their website.

Google announced that searchers who are logged in to their account will now be redirected to search Google on an https:// (an SSL or secure) domain rather than on the old http://www.google.com domain.

Google’s new change will only affect data gathered from users who are logged into their Google account and by Matt Cutt’s estimation this only accounts for approximately 10% of searches each day. There is some speculation over whether this figure is accurate or not and a good point to note here is that with the advent on Google+ it is likely that the number of users searching, while logged in to their accounts, is likely to be on the increase.

What does this mean for marketers?

SEO is a hot topic amongst marketers right now with more and more businesses harnessing search engine optimisation to generate more revenue online. Knowing what keywords and phrases prospects use to search for your business is valuable insight, and data which a business can use to tailor its SEO strategy.

The key implication is that marketers will still be able to see organic (unpaid) traffic in their Analytics, but the data will no longer include the search term (or ‘referrer’ data) used by logged in searchers. Essentially information is now encrypted by Google.

Previously, had you wanted to see what each and every individual prospect had typed into Google before they landed on your site organically – you could. Many marketers used this information to shape on-going SEO efforts and used it to help determine a) how well certain brand terms might be doing, b) the quality of the lead and c) the lead nurturing approach they were to use moving forward. This is no longer possible as all the searched keywords will be hidden and private for anyone who has searched while they are logged in.

Webmasters will have less of an understanding of what keywords attracted visitors to their sites and this is a considerable loss.

Marketers using Google Analytics can still view the top 1000 searches in Webmaster Tools but will not be able to identify which users used which term.

What do I need to do?

Consult your web analytics provider to find out how organic traffic will appear. We expect that data should remain the same for organic traffic but just exclude the keywords. We should stress again that this applies across all analytics packages; it is not just Google Analytics users who will lose visibility on keywords used.

In Google Analytics, search data that was previously available is now labelled “not provided”. Please see the example below:

What about Paid Search?

Paid search (PPC) is not affected by this change and keyword data will still be available for marketers to use.

Why is Google Changing the Way We Search?

The change has come about to protect the privacy of Google’s users; it is an especially important change at this pivotal time when Google is becoming an ever more personalised service.

Logging in to your Google account now means you will automatically be sent to the new secure Google.com when you conduct a search – what you type in will be invisible to the website owner and all other third parties.

At a time when the way in which search engines use personally identifiable information is under scrutiny – Google is clearly making a stand in favour of its users. This change may not be popular amongst marketers; but I think it is clear that Google’s intentions are wholly admirable.

What next?

It’s not known if this will be the start of something much bigger in the privacy arena for Google. It could be possible that this will roll out across all organic searches in future but for now this is pure speculation.

Will the loss of keyword data in your analytics affect you? What problems might it pose for lead nurturing and conversion? We’d love to hear your thoughts on this matter… please leave a comment if you have an opinion on the topic.

Since Google bought Urchin back in 2005 it has revolutionised the web analytics industry with it ‘free to all’ offering.  Suddenly even the smallest websites had access to enterprise level analytics software.  Google’s motivation was to make the web a better place (Read – “make more money through AdWords”).  However Google has struggled to get larger organisations to adopt its service for a number of reasons. No SLA, unsuitable security control and lack of customisation and integration features to name a few.

Today is an exciting announcement for the analytics industry as Google have made some massive changes to address the concerns of larger corporations.  Please note though that to the company with basic needs then the functionality is not massively different – maybe people will now understand more what a great tool the free GA really is!

Some of Google Premiums New Features:

Dedicated Processing

• Massive hit limits in the billions per month

• Access to download unsampled reports

Advanced Features & Functionality

• Get conversion attribution modelling.  Don’t worry if you can’t afford the premium version and still want this – we have a great free tool here that gives you Google Analytics attribution modelling !

• 50 custom variables  – allowing you a massive potential to segment and analyse you visitor data.

Support

• Dedicated support from Google.

Service Level Agreement (SLA)

• Explicit Data ownership

• 99.9% on data collection, 99% on reporting and 98% on data freshness.

So what does this mean for Google Analytics Standard Edition? Is Google aiming to start charging everyone?  The answer to this is definitely not!  In fact the pace of features added to the standard version is growing rapidly!  And Google’s plans to extend this are ambitious to say the least.  Here is a list of new features recently added to the standard product.

• Version 5 – As well as a slick new interface there have been substantial changes under the bonnet  – promised to allow faster, more and better additions to the product over the coming months!

• Multi-Channel Funnels – Much awaited ability to analyse all the sources that contribute to a sale or goal.

• Social plug in tracking – track the interactions with your social plugins

• Real Time Tracking – LAUNCHED TODAY! – This puts data in your reports within 1-2 seconds.  Watch traffic levels as it happens.

• Site Speed Reports – see how fast your various pages are loading.

Search Laboratory are one of just over 220 worldwide Google Analytics Certified Partners (GACP’s).  For help with installing, using or analysis using GA then please visit our Analytics services page.

On the face of it, it looks fantastic, a big stride forward in my opinion. This is going to be really useful for all sorts of reasons. For agencies and in-house marketers alike, it will help justify exactly what they are getting back from their digital campaigns, whether it is SEO, PPC, Social or email.

There’s already been plenty written about the topic such as explaining the power of channel groupings by SharkSEO on SEOgadget. In it he explains how to set them up and suggests creating a ‘Brand Intention’ grouping which incorporates branded traffic from organic, cpc and direct. I found this very useful in establishing the true value of your incremental search traffic (traffic whereby the user was not directly looking for your site).

David Whitehouse also wrote a post reviewing Multi-Channel Funnels, he highlighted the value of the assisted conversions report in showing the wider role of SEO in conversion attribution, instead of just attributing the last click with the conversion. In it he was able to show £64k of revenue through SEO (last click attribution) and SEO contributing to a further £82k of revenue – meaning that SEO played a part in acquiring £146k worth of revenue.

This statement is absolutely true; however, if paid advertising also plays an ‘assist’ role in a number of those conversions, then the PPC guy will also be trying to claim some of that same revenue. Both the SEO and PPC guys would be correct in saying that their medium played a part in getting £x amount of revenue, but ultimately there will be no exact £ value that you could assign to either, as the numbers just wouldn’t add up.

This has led me to try and find out how we can assign a true value to each of the channels (or channel groupings), using attribution modelling. I’ve been able to produce a sheet in excel that can help work out the true value of each of these channels.

Download the Excel Template

Here’s what I did:

Getting the data and formatting it

Select the ‘Top Conversion Paths’ report in the Multi-Channel Funnels section of GA.

Select a single conversion (not all) and all path lengths (default is set to two).

Using the channel groupings function, you can split up the traffic however which way you want. As mentioned previously, I used the great tips in SharkSEO’s article on SEO Gadget, to split out branded traffic from both organic and cpc, and placing it together with Direct to create a ‘Brand Intention’ grouping.

Make sure you extend the number of rows showing to the maximum, so you have all channel grouping paths showing in the table, then export to ‘CSV for excel’.

Unfortunately at the moment the new version of GA doesn’t export as smoothly and its previous guises. It all comes out in just the one cell, so we have to reformat the data ourselves in order to get to work on the good stuff. Maybe this will get fixed when the new interface comes out of beta, but until then we will have to do the following:

First of all we need to separate conversions & conversion value. The ‘Text to Columns’ function in excel is great for this reformatting. Just separate the conversion data from the channel grouping path (delimit using commas).

We then need to formalise the grouping path data and remove all the white space, using find and replace (find on a ‘space’, replace with nothing).

We then need to split out all the groupings from one another using the ‘Text to Columns’ function again. This time delimiting using ‘Other’ and specifying ‘>’ (see below). This will split out all the data into separate cells.

Conversion attribution for each channel

Once you’ve got this data, you can then play around in excel to find the true value of your channels. You can do this in any number of ways. In the following analysis I chose to use three separate attribution models and compare them:

• Linear Attribution – Whereby each step in the path is given equal credit.

• First Click Attribution Weighting – 50% credit goes to the first click, the remaining 50% credit is split equally between the other steps in the path.

• Last Click Attribution Weighting – 50% credit goes to the last click, the remaining 50% credit is split equally between the other steps in the path.

Using a test dataset it was apparent that there wasn’t a great deal of difference in revenue between some of the models.

These weightings are just arbitrary, so you may want to use different weightings in your own analysis.

I’ve produced a conversion attribution cheat sheet that you download here. You can then paste in your own data. You will need to edit the following:

• Channel Grouping names (must have no spaces) – these names must match the channel grouping names exactly

• Average Conversion Value – input your average conversion value

• # Conversions – Paste in from GA export

• Channel Grouping Paths – Paste in your paths in the Linear Model tab (in the box shown below)

When the data has all been pasted into the ‘Linear Model’ sheet – then just make sure that in the ‘First Click Weighting’ and ‘Last Click Weighting’ sheets, that the table range is dragged down to the same row number as the data extends to in the ‘Linear Model’ sheet.

Limitations

This sheet was designed as a basic level of this type of analysis. I’m sure that more excel savvy people will be able to take the principles highlighted in this post and build upon it. You may wish to consider the following when using my example sheet:

• All references to channel groupings (including column headings) must match your channel grouping names exactly.

• Without editing, this sheet can only handle path lengths of 204 steps – it will break unless you amend the sheet.

• I’ve used an average conversion value, which means that it would be more accurate to use just one type of conversion at a time. For ecommerce sites I would recommend using actual conversion value (this will require you to ‘paste values’ the conversion value in the ‘Total Revenue’ column manually).

• At the moment the sheet will only handle six channels / channel groupings

Summary

In summary Multi Channel Funnels is without any shadow of doubt, a major step forward for GA and I feel that this is really going to help digital marketers out with many issues, the most important being:

• Help report on and prove the true benefit that a particular channel or channel grouping is having for them.

• Address the issue that’s dogged us for some time…  Easily measuring the impact of social and its part in contributing to conversions.

Unica (an IBM Company) conducts an annual study of marketers. In this report they compare European and N. American marketers, and survey 300 people who work in businesses with annual revenues of in excess £100m (the majority actually cite revenues of $1bn or more in fact).

OVERVIEW OF 2010′S REPORT

Last year’s study was focused on the anxiety marketers felt over an increasingly rapid move toward online and digital marketing. While this was the main concern, website personalisation was also mentioned; along with dissatisfaction with technology’s ability to keep up with marketers needs. The latter concern being one I personally struggle with the most.

The main focus in 2011, which largely included similar concerns as in 2010, was the need to put all the data we create as marketers to good use. It’s clear that while we as marketers become increasingly data rich (particularly with the mass of online data we collect) we are struggling more and more to find time to analyse this data and pull out implementable improvements that we can use to increase revenue in our business.

“Marketers appear ready to bridge the gap between analytics and action. Respondents identified ‘turning data-into-action’ as their #1 organisational issue.”

“Web data is cited as being highly prized; 9/10 of marketers appreciate the value and importance of web data however less than half apply that data to campaigns. Of those that do, less than a third believe their efforts are very effective. “

SEARCH MARKETING

The survey concludes that search marketing is still immature in relation to the rest of the marketing activities. Only a quarter of companies use any third party software for bid management and 37% rely on free tools, such as those provided by Google AdWords. Respondents also indicated that search wasn’t very well integrated with overall marketing efforts. Marketers spend more on paid search than any other online media and most of the large firms surveyed use an external agency for this function (almost 50%).

The report spoke of Unica’s belief that businesses should ‘close the loop’ in SEM value, and the sharing of vital information, such as top performing keywords, should be encouraged between all marketing functions and not isolated to the online / search manager.

Reputable agencies managing PPC campaigns will always give complete visibility to their clients and encourage information sharing between teams, especially between the paid and organic search teams, if they are separate. This is why we always promote a centralised search strategy. Success comes from an integrated approach and a shared wealth of user behaviour.

Approximately half of marketers use specialist agencies for SEO and PPC, while the rest use full service agencies who offer a much wider range of marketing services.

Further to this, and a key insight for the SEO world was that 32% of respondents cited ‘creative development and strategy’ as one of the main bottlenecks in their marketing process. Creative strategy, such as that needed for successful content-rich link building and SEO is something marketers still struggle with.

The chart shows that marketers clearly understand the need for more content rich marketing strategies, rich media marketing and social media both rely on interesting and sharable content and happily, all this activity can feed your natural search optimisation campaigns as well.

SOCIAL MEDIA

Out of the top 3 important issues to marketers, those that they felt they needed to address, surprisingly a shift to social media for marketing was not high on the list. It seems marketers are not keen to adopt paid advertising via social media just yet. European marketers were more concerned; with 27% saying it was a top 3 issue, however only 14% of N. American marketers felt this was a priority.

North American marketer’s use of social media channels however actually outpaces European usage. European scepticism seems serious with one in four European respondents says they have no plans for social media whatsoever.

Determining the correct channels, turning actions into data and attributing clear ROI were cited as the most important issues. As Social Media is still hard to monitor and derive ROI from without paid tools, this might explain why a shift to PPC on social media sites like LinkedIn and Facebook are a low priority for marketers. Adoption of social media monitoring tools was deemed important with 26% of marketers surveyed saying they were keen to understand and derive ROI from social media – perhaps marketers want to see ROI before they actively assign time and budget to Social Media marketing. As many of the respondents were in enterprise level businesses, they may choose to monitor brand mentions and user sentiment before embarking on a shift to social media marketing.

As far as social media is concerned, those who are using it are using a more sophisticated approach. “Instead of thinking tactic by tactic, marketers are beginning to think strategically across three major areas of social content: owned (what they create), earned (what customers create), and paid (what marketers spend money for)”.

ANALYTICS & DATA

65% + felt that the use of web analytics was very important when it came to making decisions about marketing offers and campaigns however they struggled to put the data to good use. Amazingly 14% had no intention of using their web analytics at all.

Around half say they currently use individual online visitors web data but only about 22% of respondents believed they were using the data very effectively. It appears there is room for improvement in this area. Improved segmentation and the use of engagement metrics would be a good place to start for marketers who feel their use of data could be improved. In addition, social traffic should be set aside for separate analysis. According to the survey, almost 70% of respondents either use, or plan to use social media data in their segmentation.

“Too many social media strategies treat their audiences as one, undifferentiated mass. Marketers should collect social media data and attributes in their customer profiles and use this information to enrich segmentation strategies. Social data compliments traditional demographic and transactional data and the web behavioural data with insights into likes/dislikes, interests, and brand disposition.”

Unica suggest that social segmentation can be simple suggesting marketers follow these steps;

1. Look at who is active where? What networks do your clients use?
2. How often do they interact and comment? Optimise your strategy to target the most active and engaged customers.  Those making the most noise are likely to have larger networks.
3. Create content specifically for the most influential people within your social network – they have the largest reach and are most valuable people to have distribute your content.

MOBILE

Over 40% of marketers are already using mobile marketing tactics, with an additional 25% planning to use them this year. With more and more content being accessed via smart phones, there is no doubt that in 2012, mobile will be the main topic of conversation. I believe uptake of mobile is much less the 40% cited in this study as smaller business struggle to conceptualise how mobile apps and websites will benefit them.

Of those who do use Mobile marketing, 15% say they still don’t measure their mobile marketing efforts. This astounds me – why use this method if you cannot tell whether it is useful and returns

I think this report brings out some interesting points for marketers to consider moving forward. It gives us a benchmark for our own progress as we are all trying to create the perfectly balanced (and most effective) marketing mix possible.

I predict that over the next year, online advertising, particularly search, and mobile will become increasingly important to marketers and will be used in a more sophisticated way. We will all begin to use the granular data we collect from our to find out key behaviours that will allows us to sell more – using this insight can help us integrate all our on and offline marketing activities. It is only a matter of time before social networks such as LinkedIn and Twitter will develop their own commercial advertising offerings further allowing us marketers to assign more time and budget on these channels. Currently using these channels effectively is difficult as the sites and their tools are basic in comparison to the tools offered by Google or Bing for example.

Please feel free to leave a comment and tell us whether you think your marketing plans match those of the marketers surveyed here and if you have any predictions for the coming year in marketing. We’re keen to hear your insight.

You have a business advertising a high value product, and you’re running a PPC campaign for it. However, you’re not tracking many conversions because people are choosing to ring up and enquire/order over the phone. This means that you’re not seeing many conversions reported against your keywords, and it’s making it difficult to optimise the PPC campaign. This head-scratching scenario can drive a PPC manager to the brink of madness.

Your PPC data may look something like this:

Although you’re seeing a few conversions, you’re not getting enough data to make solid decisions. You therefore need greater clarity so that you can identify which groups are only delivering a general supply of ‘Steve Searchers’ rather than the much more sought after ‘Colin Converters’ and ‘Brian P. Buyers’.

The Solutions

There are many ways of increasing the volume of conversion data:

1. You can add extra enquiry forms on your website which people can complete. People are far more likely to submit an enquiry form than buy an expensive product from a site that they’ve never used before.

2. Sign up for telephone tracking. There are a number of packages which will integrate with your Analytics and AdWords account. They record conversions when people ring up after clicking your ads – and can be tracked all the way through to the point of sale. These provide highly valuable intelligence, though there is usually a monthly cost involved.

3.  Measure website interaction statistics. You can study the behaviour of customers when they visit your site, and setup the Analytics account so that it records a goal when one or more of these conditions are achieved. These are called Engagement Metrics…

Engagement Metrics

In order to maximise conversions, you want to increase the volume of good traffic that comes to the site. Signs of good traffic are as follows:

• Low bounce rate – a measure of how many people leave after viewing only 1 page

• High time on site figure – average time spent on the site is well above normal

• High number of pages viewed – average number of unique pages viewed is higher

• Adding products to a shopping basket – entering the checkout process

• Viewing a key page such as “Contact Us” – indicating that they intend to phone you

Defining Your Engagement Metrics

You need to identify which of these is going to be most relevant to you and setup appropriate engagement metrics. Here’s an example:

1)      Your average time on site is 2 minutes and 59 seconds. You could set up an engagement metric to record a goal every time someone spends 3 times as long on site as the average person – 9 minutes in this case.

2)      Your average number of page views is 4.1. You could set up an engagement metric to record everyone who views 12 pages.

3)      Customer ads a product to the basket and enters the checkout process. This is a clear and definite sign of interest.

So these are your chosen metrics to record as conversions. We now need to set them up…

Setting up Engagement Metrics

Here is a step by step guide for setting up your engagement metrics in Analytics and AdWords…

• Log into Analytics

• Select Analytics Settings in the top left:

• Select Edit next to your profile name…

• Select Add goals form the Goals section…

• Complete the form as follows…

This will trigger a goal when a customer spends 9 minutes or more on the site. You can specify and goal value you want. In time you may discover that some goals generate more valuable leads than others, so you can assign a greater value to those. You can enter a currency amount here if you know that a lead is worth, for example, £500.

• Click Save Goal and you will see it appear in your goals list…

• Repeat this process for the second goal that records when people view 12 or more pages…

• Click Save Goal again and both will now be setup.

• Add your third goal for when people enter the basket process…

Here we’ve entered a goal value of 100 to represent that it’s a potential sale.

• You will now start to see conversions being recorded against your new goals, and you can access them in the Goals report – so it will hopefully start to look like this…

Importing Goals into AdWords

You now need to import these goals in AdWords so that they can be recorded as conversions against your keywords and adverts. To do that, follow these steps:

• Login to the AdWords interface
• Select Reporting/Conversions from the menu bar…

• Select Imported from Google Analytics…

You should see a list of the new goals you’ve created, though they must have already recorded a conversion in order to be imported. You can’t import goals that haven’t tracked any activity yet.

To import them you click the tick box next to the goal name and select Import.

• You will now start to see more conversions being recorded in your campaigns. This data will enable you to better understand the conversion rates of different keyword themes. Groups that you thought were spending a lot without generating many conversions may turn out to be generating highly relevant traffic. On the flip side, keywords that you assumed would be really good may be spending a lot without generating many leads. Hopefully your data will end up looking more like this…

How Do You Use This Information to Your Advantage?

Making the most of your new conversions will be very important. As you can see from the list above, Dockside Cranes has the highest conversion rate. Every visitor satisfied at least one of the engagement metrics, so you know that the traffic coming through that ad group is highly relevant. This means you can increase your bids on it and ensure you’re always appearing as high up the search list as possible.

Patterns will appear in the data – most of the best converting terms relate to “dock” / “dockside” and “cargo” keywords. This shows you that you need to be getting more of this traffic, and you can look at raising your bids and expanding your keywords. You should also optimise your site for these keywords.

At the other end of the scale, the Heavy Lifting Equipment/Machines keywords are not getting very high conversion rates, and they are spending a good percentage of the budget. This would suggest that you need to lower those bids down and spend more money on the better converting groups.

All of a sudden, you’ve gone from being in the dark to being well informed. You’ve taken the first steps along the path that leads from PPC Drudgery to PPC Ecstasy (via PPC Enlightenment) – and it was all thanks to the splendid bounty that burst forth from your voyage into the warming seas of Engagement Metrics.

Is Google Trying Too Hard?

It seems that recently Google has been releasing all kinds of new features, not exclusive to just AdWords either. With Analytics getting a complete overhaul, the new social network Google+ and a plethora of other small tweaks and additions Google is definitely trying to innovate rather than imitate.

This post will talk about a few of the more well-known additions as well as some of the more covert ones that may have slipped under your radar as a consumer or as an advertiser.

I’ll start with general additions to the search page…

The first thing that you may have noticed is the face lift that the results page may have had:

As you can see the biggest two changes are the inclusion of this big black bar at the top, as well as the red headings and grey subheadings down the side.

This is still in a beta mode and hopefully, in my opinion anyway, they ditch it and go back to the old cleaner results page.

The other main addition for the average Steve Searcher is the seemingly unavoidable Google+. I think that NEWgle has been clever by making it invite only, causing Steve to desperatly want to be a part of it. However, once he had been granted access to this fancy new social network he immediately closed it down, went on Facebook and got on with his life.

The problem is that normal people use Facebook, it’s not like MySpace used to be when it was just a communal pit of depression for emo’s, people were crying out for a Facebook. Now there is one, it seems like Google is trying far too hard to knock it off it’s perch. I can’t imagine that 750,000,000 (yes that many) users will want to re-upload hundred’s of pictures for no reason. Perhaps Google should have been a bit more FRUgle with their money on this one…

Next let’s look at:

Moving on from things that will affect the average Internet enthusiast and onto more technical features/additions Google has made to the AdWords platform. Some of these you may have heard of, others possibly not.

Here are the 3 feature that I will go into:

• Display Campaign Optimiser
• Mobile Landing Page Designer
• New Columns

Display Campaign Optimiser

This is a great new feature that basically let’s you give a lot less attention to display campaigns. To be able to use it you must be getting at least 15 conversions a day. You also have to be comfortable with Google taking control of your campaign and letting it have a few weeks to ‘Learn’ (some cynics would probably think that this is a way of Google getting out of it not working properly straight away) but being a PPC Account Manager I am happy to at least try taking the required leaps of faith.

Basically what it does is, based on your target CPA, creatives and budget, Google will find lots of new conversions for you on websites that ordinarily you probably won’t have targeted. It is great for people who have huge display campaigns and don’t have time to optimise them effectively. Definitely worth a try if you’ve got the traffic.

Mobile Landing Page Designer

This, in the words of well known decking/fence stain product, ‘does exactly what it says on the tin’.

It allows you to very quickly, and very easily create as many Mobile landing pages as you like, saving hundreds of pounds for the advertiser.

Looking at the sample below, you can see how much scope you have for customisation. It isn’t a perfect solution by any means, as I’m sure that there are soon to be a million companies with the same mobile site, but it does exactly what you need it to so why spend £1000’s on getting one built 3 weeks after it was supposed to be finished?!

This isn’t one that web companies are too pleased to see that’s for sure.

New Columns in the Interface

There have all of a sudden been an influx of new columns to the interface, these include exact match impression share, relative CTR as well as 4 that I have only just noticed whilst writing this blog! These, hot off the press metrics display statistics on the number of times your phone number is displayed on a device that can’t make phone calls, as well as the number of calls that are attributed to your ads. This is done by having a unique number assigned to your campaigns which is inserted into your ads as a 3^rd description line. The number of calls you get from this number (which can only be obtained from seeing the ad) is listed in AdWords. All in all a seemingly easy, if untested, way to monitor offline conversions.

The relative CTR is a way of seeing how well your display campaigns are performing compared to ads on similar websites, basically the number that is displayed tells you how much better your CTR is. A stat of 10x means that your campaign’s CTR is 10 times better than other ads on the same site.

The Exact Match IS is a metric that tells you the impression share of your campaign of when the search term matches exactly the keyword in your account. The higher the number here the better, as it means that all your keywords are getting good impression share.

As far as the new Analytics is concerned, I’m sure that blogs have been done to death on this so I shall leave it be for the time being, but rest assured there are some useful things coming along soon, one that will certainly help to clarify the sometimes blurred line between SEO & PPC.

As we come to the end of this blog it seems fitting to end with a Jerry Springer style Final Thought, I think it is fitting as Google’s antics sometimes seem like they should be accentuated with taunts of Jerry Jerry! Especially when they are going to be locking horns with Facebook, there is definitely going to be some tantrums being thrown.

Anyway, as I mentioned earlier, it seems that Google is trying to set the pace with new ideas left, right and centre. Some very, very useful (mainly for advertisers and businesses), however their big one Google+ has not hit the right chord with me. It’s main USP is this “Circles” idea, saying that you can guarantee that you keep things separate from people you don’t want to see it. But, as sure as “life found a way” in Jurassic Park, your boss will see that witty rant about his half-mast trousers or piece of food stuck to his face. So it seems that maybe Dante had it right in his Divine Comedy, he was just talking about the wrong place. It wasn’t the underworld, it was Google+.