Getting better insight into your online marketing campaigns and why this matters

OK, I’m guessing that many of you already know which websites send you what kind of traffic.  I don’t just mean whether search engines send 60% of your traffic but also what other sites are sending you that other 40% of visits.   Such as press mentions, local directories, online articles, blogs that mention you etc.

But if this is all you know, then you could still work your data a lot harder - with the ultimate goal of less spend, more results.  With a little bit of web analytics customisation to your campaign activity, you could be able to answer questions like:

• Which paid button on XYZ page gets me more traffic - the one in the section about golf or the one in the section about fishing?
• Do either of these buttons lead to more people booking than the free text link also on that site or the direct email I sent to my newsletter subscribers?
• Is the banner ad I ran on the front page of a directory three months ago more successful than the one I am running there at the moment?
• I’ve been pushing a special offer to my email list and online - what’s the value of each approach?

What we are doing here is moving from just tracking generic sites and marketing efforts as a whole, to tracking specific Campaigns.  To do this you need Goals.  And for a travel and tourism company wanting to maximise their return on investment in today’s climate, this is a vital step forward.

So,  if you cannot yet answer questions like those above about your site, then you need to look at some form of campaign returns analysis.   This involves campaign link tracking, setting specific goals within your web analytics tool and pulling results together in a way that factors in cost.  This is something you can do easily through most web analytics packages and a simple Excel spreadsheet.

Tracking Campaigns - an example.

Imagine that you run a hotel in Scotland and you decided to place an advert with a link on the front page of a  site like http://www.extramilescotland.co.uk/ to link to a great deal you have for golfers. In addition you also want an advert on the same page linking to a great deal for anglers. Just looking at your traffic sources in your Google Analytics data will not let you tell these adverts apart.   One of them may have worked, one may be a complete waste of money.

And, at the same time, you decide to email your past fishing customers telling them about a deal with a link to your site and you do the same for the golf customers.   It is starting to get really difficult to isolate precisely which of your activities are moving the needle.

BUT - there is a way round this.  Just a little tweaking of the names you give those links, you can tell all your ads apart without needing to do anything to your website.

Not only that, once you tweaked that URL, you would start to get really detailed marketing effectiveness information that would tell you a lot more than just where the visitor came from.  This is the wonderful world of campaign tagging (OK, not really that exciting - but so very useful!)  The “how to do this” is spelled out further down the post.

By identifying how people responded to different promotions, you can start to take control of what’s working for you.

But you need to take just a few more steps to start to make this really really powerful stuff.  You need to define what success is for you. You need to define what you want you visitors to do.  You need to define your Goals.

Campaigns + Goals = now analytics gets actionable

As Vicky argued in a previous post,

“online success is not about how many people come to your site in total, its about those people that come to your site and then do what you want them to do (or not!).”

In other words, you need goals.

Let’s revisit that example above and, had we tracked each different campaign correctly, we might get some figures like those shown in the table below:

The table above shows us

• The number of visitors to the site each type of campaign attracted,
• How many completed goals can be attributed to those visitors attracted by the particular campaign,
• What percentage of visitors per campaign achieved the goal.

If you did not have a goal defined, then you would simply know that more people came to your site but you would have little understanding of how they behaved.  It would be a bit like advertising a shop opening but not bothering to record what your customers bought - or if indeed they even bought anything at all.

Put simply, Goals allow you to assess how successful you are at getting your customers to do something you want them to do.  And some campaigns will be more successful at getting them to do that special something than others.  In the example above, we can see that the ‘golf email’ link was the campaign that was the most successful in getting customers to do what you wanted them to do.

A goal can be anything from a sale through to anything other tangible action you want a visitor to do on your site - for example, a brochure download or visiting the directions page.

But if you do sell (or make reservations) through your site, then we can take the final steps and start to measure very exactly what these different campaigns did for your bottom line.  If we assume that your site is ecommerce enabled, then the table above could start to look something like this:

And what could we conclude from these (fictitious) figures?

• A lower percentage of ‘fishing banner’ visitors’ complete their goal (’make a sale’ in this example) than ‘golf banner’ visitors - but the ‘fishing banner’ visitors spend more when they do get to the site.  The activity cost more than the email activity, but it paid for itself.
• The emails in both cases got more people to convert than the banner ads for the same interest area - but the revenue from them was much lower (perhaps the emails drove more last minute cheap deals than the high margin banner ads).
• Despite the lower revenue generated by the fishing email, it represents a superior return on marketing investment to the fishing banner ad because of its low cost.  It was a quick win and by no means a worthless activity!
• But look at the golf banner - in this instance our marketer spent £500 yet only acquired revenues of £300.  The activity had a negative return and doesn’t justify being continued.

Note that not all analytics packages will automatically calculate a Return on Investment or a Cost of Activity figure for you (Google Analytics does for adWords but not for customized links). Even if your package  doesn’t, it’s pretty easy to work this out from your data.  You simply need to paste it into a an Excel spreadsheet, and if you’re interested, the ROI formula we’re using here is:

(Revenue from marketing activity - Cost of marketing activity) / Cost of marketing activity.

So what?

When you only have a finite online marketing budget, you need to know whether you are spending it wisely.  Thinking in terms of campaigns,  goals and campaign returns allows you to work out exactly what is and what isn’t working for you.  It identifies whether marketing in Directory A is better than Directory B.  It enables you to work out whether emailed customers (for example) are more likely to buy or complete a goal with you than visitors coming via other sources.

This is giving you near-real time information about how successful your marketing is.

The technical bit - how it’s done

Although I am aware that there are a wealth of analytics products out there, Google Analytics is the most commonly used at the moment and so this section uses this tool as the building block.  The process would be broadly similar in other packages.

Campaign tracking: Campaign tracking looks daunting to begin with but essentially it means adding a bit of code to the URL you to direct people to your site from your banner ad, text link or whatever. For Google Analytic users, there’s a useful tool here to help you out.

Setting up Goals: I can do no better than to echo Vicky’s earlier post by recommending Justin Cutroni’s article here and  his video here.

Integrating adWords and ecommerce: try Google’s intro here.

Still confused?  Well…you can always hire us to sort out the issue!

Filed by Stephen (17/06/09)

We work a lot with tourism and travel providers operating customer satisfaction feedback systems to help improve their services and offerings.   But I’ve met a few people recently who have expressed scepticism about customer rating systems generally and it strikes me that this scepticism could be the result of not looking at the data in a more rounded context.  Or due to receiving data derived from flawed methodologies.

The scepticism was expressed along the lines that these kind of things always show that 90% of customers are satisfied. The implication of this is that rating systems aren’t really telling you the full story. So, while we’ve previously written here and here about using comment cards, these recent comments show that there is still a little more ground to cover in this area.

I can understand the view that customer rating systems are inadequate - but this typically occurs only if you are looking at the data derived from the customer in isolation.  As we wrote in one of the previous posts, “comment cards are just one of a suite of businesses information sources”. In other words, you shouldn’t rely on comment cards alone for customer feedback in its broadest sense. (And with such rich data all around you, why would you want to ignore the other sources?). But let’s start by looking at this “90% satisfaction guaranteed” issue a little closer as I feel that a rating like this is not as pointless as critics suggest.

To my mind it’s all about context. A 90% satisfaction rating expressed as a snapshot of customer sentiment can be fairly meaningless. However, a 90% satisfaction rating for an activity compared to (for example) the rating for a different activity, a different period or even a different location does start to have some meaning.

It’s about trends, not absolute scores. It’s about comparisons, not absolute ratings. It’s about context.

But let’s have a look at this using some real data.

Context One - data over time

The following charts are drawn from ‘real life’ but have been anonymised.

Starting with the one on the left (click on it to open a larger version in a new window), the orange line represents a lower control limit (one standard deviation from the average downwards meaning that 68% of all monthly results ever fall within this range - and if you are interested in why I’ve used only one standard deviation, see the  second comment at the end of this post). The average is the grey line in the middle. The blue straight line represents an upper control limit (again one standard deviation but upwards). I’ll explain the purposes of the control limits in a moment. There is also a dark grey line which is the trend of the scores. 

In this first graph we see a green line charting the percentage of people who completed a comment card for a particular aspect of their experience and who said that they were satisfied. Looking at this line, we can see that indeed it hovers around the 90% mark but that there is some variation. So what can start to take from this information?

Firstly, you will expect some degree of variation when analysing data one month to the next - it’s just natural. But there are times when a change is ‘unnatural’ and this is when control limits come into play as they alert you to when something has fallen outside of the normal corridor of performance. And these control limits can only be derived from looking at this data in a historical context as this gives you the most realistic guide to what is normal and what isn’t.

Secondly, looking at the trend line you will notice that, if anything, it has dipped a little. It’s probably nothing to be worried about.  But if, for example, the line represented a customer service rating and, despite months of internal training, around one in ten of your customers were still leaving feeling that they had got substandard service.  Wouldn’t that be a concern to you?

Context Two - data compared

In our second example on the right (click to enlarge), there is now a second line of data about a different service.  This was rated at the same time as the first service and by the same respondents.

Firstly, it should be noted that these lines are not moving in lockstep (they actually have a correlation coefficient of around 0.25 indicating a practically non-existent relationship).  The trend lines further indicate that the levels of satisfaction are moving in opposite directions and so we have a clear indication that, despite the high ratings for both lines, the responses are nevertheless suggesting that there are differing levels of satisfaction with them.

Now we’re starting to get towards something useful.  We can start to ask what is going on to make people less satisfied with service A than service B over time.  It is even possible to start to test operational changes to look for a positive uplift.

You MUST be happy!

The context in which the customer feedback was taken can also affect satisfaction levels (although the data I’ve worked with suggests that aggregated satisfaction levels tend to be quite similar).  For example, I analysed the results of feedback from one destination where the respondents were required to hand the completed score cards  straight to the accommodation provider collecting the forms. Unsurprisingly, 85% of people claimed to be elated by their recent accommodation and 5% dared to only be satisfied.  In a context where the data was collected more anonymously, this split would probably be something more like 55% and 35%.  In both cases, we could argue that 90% were satisfied although the second example is probably closer into the truth.

In a situation where you do have frequency data for all the scores (ie counts of how many excellents compared to how many satisfieds), it is worth looking at it in some more detail to get sense of how sentiment is shifting.

For example, are there more ‘good’ than ‘excellent’ scores?  for most items but for a few that situation is reversed?  This might indicate that while 90% are satisfied (’satisfied’ being, as noted earlier, the ‘goods’ and ‘excellents’ summed) the balance of satisfaction lies at the lower end than the upper for most items. And that those that buck this trend are worthy of note.

But what is satisfaction anyway?

But there are still important questions floating around in the background here and they probably all flow out of the main one of, “what does ’satisfaction’ mean?”

What I mean by this is satisfaction indicate something good, all right or possibly inadequate.  For example, the data behind the charts above is coded in such a way that the rating delivered by a respondent is give a numeric value (eg bad = 1, adequate = 2 etc).  From this it is possible to calculate that your visitors were 4.2 out of 5  happy this month.   Unfortunately, such an approach can also demonstrate that your visitors were 1.4 out of 3 female, something that is just plain silly.

So, the approach we have taken for the purposes of top line reporting is simply to allocate results to discrete bands - if, for an example, the score is a 1 or 2, then it shows that the customer was dissatisfied, and anything above that suggests satisfaction.  This means that you get an easy overview of the level of satisfaction.

But, you might say, I’m not interested in people being satisfied, I want them to be elated!  A noble goal to be sure but I’m not sure just how elated one can be at the process of buying a coffee or noting that the toilets were clean. There are some things that just don’t excite people that much to cause them to rate them highly in feedback forms!  They’re only notable when they go wrong!

But I guess that this is all really confirming something we’re said in the past - if you are measurng customer satisfaction but only skimming the data then you are potentially wasting your time.  Only through a more indepth and intelligent use of it can start to yield up the nuggets useful for your business.

Filed by Stephen (07/04/09)

What business are you in?

Knowing what business you are in gives you clarity of purpose.  This, in turn, gives you focus and an enhanced ability to understand and meet customer expectations.  But surely we all know what business we’re in, right?

Well, think about Domino’s Pizza for a moment.  Domino’s are not in the catering business, they’re in delivery.  Fast, fresh, reliable delivery.  Customer’s don’t call them for a slice of authentic Italy - they want big, hot pizza and they want it now.

Likewise, people don’t buy a drill because they want a drill - they want a hole.  More important still, they want a hole to make a shelf to put their son’s first football trophy on.

In the same way, people don’t visit a destination because they want a tourism experience - they want any number of things, from privacy, to exhilaration, to a convenient place to break a journey - to complete brain-switch off in the sunshine.

No, what business are you REALLY in?

A simple answer to that might be “the one you’re customers think you’re in.” What is the fix you deliver to their problem?

That might initially sound a little too simple and prescriptive - after all, it seems to suggest that you can only ever be defined by what your customers think you do now and that any strategies or messaging to alter this are doomed to failure.

So it’s probably more constructive to start to answer that question by thinking in terms of: “It’s not about me, it’s about you.”

Those of you that have an awareness of strategic marketing might recognise this in terms of ‘features and benefits’.

In other words, it’s not about whether you have, for example, 30 museums and 100 five star hotels, rather, in this example, it’s about cultural enrichment and pampering. It’s not about a list of products and services, it’s about what these mean to your visitor.

Let me explain what prompted these musings….

The first recent occasion was at a conference in Glasgow launching the Scottish customer feedback initiative.  As well as discussing feedback, there were also destination presentation highlighting approaches that could be take in marketing an area .  I was comparing my notes taken during presentations by  Santiago de Compostela and Prince Edward Island and realised that very different approaches were being taken in how they were portrayed.

Santiago de Compostela seemed to concentrate on its features to define itself of the destination whereas PEI explained how they had done research among their visitors and had then defined itself based on the benefits it had found within this research.

Undoubtedly both approaches work - visitor numbers had risen in both location.  But I had a niggling sense that Santiago de Compostela could have gone a step further as they seemed to lack a distinctive narrative or personality (although Santiago de Compostela  would undoubtedly argue that it does indeed have a personality -  that it’s a culturally vibrant place to visit).  However, While they could come across as being a place with ‘lots of things to do’, they could be just be one culturally rich European location among many.

On the other hand, PEI’s research suggested that it’s visitors thought of it as ‘a gentle island’ and to me this seems a more meaningful and human differentiator.

Or, to put it another way, one was about the products and the other was about the customer.

But in this example, I’m still not sure whether one was was superior to another. From a personal perspective Santiago de Compostela sounds more interesting (I prefer cultural tourism to relaxation) but I’m not sure that I would choose it above many other culturally rich places.

Destinations everywhere - but how many really stand out?

While there is ambiguity in the examples above there was less experienced walking round the exhibition halls at  ITB in Berlin.  The choice of destinations  could be not so much mind-blowing as mind-numbing.

The trouble was that I often struggled to think of a reason why Destination X was better than Destination Y. Golden Beaches? Check. Local Cuisine? Check. Authentic experiences? Check. Compelling reason to visit above competitor destination? Not sure…

“We are in the happiness business”

So, to return to the conference in Glasgow where the last session was delivered by Gregg Patterson who runs the The Beach Club in Santa Monica.

For me, the key sentence Gregg used in his session was “we are in the happiness business.” Others might have said, “we operate a high-value members-only hospitality facility” or “The X Group run mid-market hotels aimed at the leisure market.” And they would be right - while also missing the point of why they exist, as they would be defining themselves from a product, not a customer perspective.

They would be emphasising their features, not their benefits.

Yet it is  this recognition of the benefits from a customer perspective that allows a “different” approach  taken.  One that more intelligently communicates with customers, connects with them emotionally and identifies how best to deliver to them at a product level.

It enables you to develop strategically and tactically. In the case of PEI, the local DMO has been liaising with the local authorities to develop facilities that help deliver on the promise of being ‘a gentle island.’

At a tactical level, it has shown The Beach Club how important the ‘dignity’ of customers is. This might sound like a rather odd or old fashioned term but it means recognising the visitor as a person, not as another number.

So how do you start to understand what business you are in?

For me, the starting point would be some form of qualitative research to determine what the area/attraction actually means to your customers. What is their emotional connection? What is the narrative behind their visit?

And there are many ways to pick up this information.  For example, there is user generated content online.  What are people saying about you and how are they saying it?  What images are they posting, how are they branding you?

Also, what terms are people using to find you online? What kind of sites things are they looking at as well as your own?

And there is always the more traditional research method of  destination audits, street research and focus groups which can also really help to drill down and identify what it is that really makes your destination memorable (or infamous!).

Ultimately, whichever research methods you choose - the challenge is to see yourself as others do.  And to react to those perceptions, even if they differ from your own.

Posted by Stephen (26/03/09)

What I took from ITB Berlin Day 2 is that systematic testing and analytic pays.  Haven’t we mentioned that before on the odd occasion?

Testing pay as you go mobile ticketing

It was fascinating to learn about dBahn’s - Germany’s national rail provider - development and testing of  mobile ticketing.  They already have electronic ticketing for book ‘before you travel’ journeys.  Travellers can receive their ticket in the Form of a 2-D-Barcode via MMS (Multi Media Message). The code is scanned like an online-ticket from the telephone screen by the conductor (read more).

But dBahn are also running a highly sophisticated test of pay as you go mobile ticketing, utilising the phone as a wallet.  The ticket and payment is entirely integrated into NFC enabled mobile phones (NFC is a new, short-range wireless connectivity technology - more here).  Users get a monthly bill for travel as with their phone bill.

dBahn have integrated all public transportation between Hannover and Berlin and are using real paying customers to test the service.  If it works then in 2011/2012 it will be rolled out across Germany.  If it doesn’t - or if NFC phone adoption does not reach critical mass - they will “review strategy”, potentially walking away.  Now that’s an efficient test.

Site optimization…. more than middle or side, green or blue

One of the business case examples that most impressed me was Mr & Mrs Smith, the boutique hotel specialists focussing on romantic getaways for couples. (Check out their blog and see if you can resist spending!)

Utterly focussed on their specific target market, meticulous in understanding that market and their needs, testing and analysis seems like the oxygen their business breathes.

They are using multi-variant testing and high end web analytics (Omniture) to test and retest the critical elements of their site.  This is to ensure that every part of the site - from forms, to descriptors - are converting into business at the highest possible rate.  This is a serious approach to online optimisation - something that I fear the industry generally can often lack the knowledge, or perhaps confidence/skills to really attempt.

Every aspect of their marketing campaign activity is measured and its performance judged carefully according to tangible conversion factors such as new membership and revenue per member.  The information gleaned informs their subsequent actions and means that as a relatively small business, they can be as lean and profitable as possible.

Tamara and James, the driving force behind Mr & Mrs Smith, modestly reflected that there has been a huge amount of learning on the job, particularly in terms of developing and bringing in-house the skills they required.  But I strongly believe (well I would, wouldn’t I??) that their efforts in this area demonstrate conclusively how using data intelligently can establish a business as a real market ‘player’ and have a distinct advantage in these difficult economic times. 

And on the subject of measuring Twitter…

PhoCusWright at ITB was twittered with great aplomb (with the bloggers to thank for that I think). In fact, Twitter was used so heavily during the event to share comments and ask questions of the panels that the hashtag #ITB09 ranked as high as the 5th hottest Twitter topic of the day.  Lots of hype for the tool of the moment.

But - are your Twitterings generating results or wasting time?  Are you influencing or invisible? Well at last you can find out.

Eric Peterson has come up with a great tool  - Twitalyzer - specifically for Tracking Influence and Measuring Success in Twitter.  You can even combine your own exported data from Google Analytics with Twitalyzer.   Twitter addicts and sceptics alike should check out the Twitalyzer blog - you’ll be able to judge whether its worth your business’ attention based on hard evidence!

So what might PhoCusWright at ITB in 2010 bring?

Well I hope it will bring a lot more tangible examples like this.  Businesses using tools and technologies - not for technologies sake and not because of the hype - but to systematically improve customer experience and business profitability.  Those firms that will best emerge from these challenging conditions are those who know where to cut and where to spend - and that requires data and smart analysis.

Posted by Vicky

“Tough times call for creative ideas”

There was an audible gasp at Canada eConnect a few weeks back, when Tourisme Montréal, Montréal’s destination marketing organisation, announced that they were spending their 2009 budget entirely online.

Rather than indulgent risk taking, Tourisme Montréal’s decision was the result of a reduced budget forcing tough choices - where would they get best results from a more modest spend?   It also reflects a strategic decision to target traveller motives, tap into emotions and intrigues - and do that in a very granular way that is both relevant and touches at travellers in multiple online places and in multiple formats.

“It is about interacting with the consumer….If we are choosing to be only on the web, we have to be everywhere”
Tourisme Montréal

Much of that spend will be going into online direct response, such as paid search marketing.  However 20% will be allocated to awareness/social media meaning a very different measurement and marketing environment.  Social media may involve litte in terms of media buy cost, but it certainly requires significant time to service and a new way of thinking about return on that investment.

As Carmen Ciotola, Vice President, Communication and Marketing of  Tourisme Montréal explained to the CEC audience:

“What is freaking us out the most is that the 20% will be 80% of the work”

She’s right of course, but Tourisme Montréal seem well placed to lead the way to the 100% online budget leap.  They appear to have a culture of online analytics running back to 1994 that has evolved in line with the sophistication of their efforts.

A strong focus on analytics, complete with an understanding of what is driving conversions and buzz means they are not making risky marketing decisions in the dark.  It is how they have the data and evidence base to know that their limited resources will deliver maximum results spent only online.

They may be breaking ground, but I suspect we will soon be hearing other destinations describing TV & print as “nice to do if we had the budget.”  It acknowledges the reality that travel research and purchase decisions are to a staggering degree made online.

Consumer research based on social values

Another of the reasons, at least as it seems to me, that we see a major destination from Canada tapping in so completely to social media and online marketing is that Canada has built a national strategy based on profiling and segmentation according to social values, not demographics.

One of the things that holds true online is that communities and networks of people online share common values and outlook characteristics, but may have little in common in terms of demographic factors such as age, location and income. People who share a postcode or zip code do not behave the same online.

“Brand Canada” has tried to build a solid online marketing strategy by tapping into the fact that social media allows us to tell stories and that at the heart of stories are shared experiences, personal emotions and excitement. By engaging with this, they are serving up tailored experiences that inspire action – ie conversions/a commitment to purchase – in the visitor.

Canada of course is hardly alone by trying to focus on visitor experiences and emotional factors.  Many of the DMOs and national tourism bodies I speak to are taking exactly the same approach and I have featured examples from Washington DC and several others.

But what the Canadian Tourism Commission has done is build a systematic research tool , now being rolled out across the DMOs and major tourism partners like Parks Canada (an example at the Tourism VC blog here) , that offers a new way to match visitors with experiences tailored to what they are seeking.

This Explorer Quotient tool is a method of identifying visitor needs, interests, expectations and desires based on their values about travel.  As Greg Klassen, vice-president of marketing with the Canadian Tourism Commission explains:

“The EQ model is unique to the industry in that it recognises and operates on social values, not demographics. Commonly held social values are in fact, much better indicators of consumer preferences - including travel consumption preferences - than demographics.” Read more in this DMO World interview with Greg Klassen.

The EQ model is based on a solid research foundation. Through adaptations of Environics Social Values model, the CTC can develop a user profile based on the reasons why people travel, including qualities of someone’s personality.

The CTC can then suggest Canadian experiences that are relevant to the traveller and consistent with the traveller’s EQ. The tool feeds back into segmentation activity and allows CTC to build a profile of travellers, and offer experiences, that are not just region based.

To create a profile travellers complete a 25 statement questionnaire dealing with travel habits and motivations. The tool includes an accuracy checker “does this sound like you?” Apparently 95% of EQ travellers say that the EQ groups partly or completely describe them.

Mine was certainly bang on!

Marketing activity then feeds into the visitor EQ type, presumably further building the visitor profle, and allowing for an ever more customised and granular marketing approach.

Tesco’s Clubcard meets travel?

So is it print on the bonfire and goodbye TV?

IF, and it’s a big if, you’re ready - then just possibly yes. Particularly if shrinking budgets force your hand.

But, I think a perquisite is a serious use of analytics and research to understand the visitor, their motivations and their online conversion behaviour.

Marketing must always be relevant - not to ourselves - but to the consumer. If your analytics data and your customer is telling you that online is the primary travel research and planning channel, then your customer is actually already giving you the answer to where should I spend?

Using Google Insight for tourism and travel research

I recently wrote a post on using Google Trends for tourism and travel insight and this post expands on some of those themes by talking about the Google Insight product.

Before I do so, it might be as well to remind ourselves of the difference between Google Trends and Google Insight.  As I noted in the previous post, “…Google Trends shows data relating to traffic to websites while Google Insight shows data related to search terms.”

So, in a nutshell, Google Insight offers a great way of understanding how people search for particular terms and, more importantly,  the contexts in which they do it.  For a tourism destination, for example, this means that it is possible to judge where your destination lies in comparison to competitor destinations and whether there are opportunities to broaden your market offering.  For a specific tourism or travel business, you can capitalise on the fact that brand names are increasing dominating searches in order to see where you stack up against competitor businesses.

It’s probably best to illustrate this with a concrete example and for this I’m going to look at some tourism businesses in Aviemore, a destination that offers year round outdoor activities close to where I live.  I’m going to concentrate on two businesses - the Aviemore Highland Resort and the Hilton Aviemore. I have selected these two simply because they are both large hotels, they both cater for a similar clientèle and they both undertake marketing expenditure.

Inputting the brand search terms ‘aviemore highland resort’ and ‘hilton aviemore’ brings up results that look like this (or click on the image below for a larger version).  I’ve applied filters to the results so that I receive data based on the relative popularity of the two search terms from people within the UK in the period Jan 07 through to October 08.

You can see from this graph that the two hotels pretty much shadowed each other up until about July this year when the Aviemore Highland Resort started to drift away downwards from the Aviemore Hilton.  Now, there have been periods of divergence before but this recent period strikes me as being longer lasting and deeper than previous splits so, if I were Aviemore Highland Resort, I would now have concrete proof that for some reason, I was no longer making as big an impact when compared to my close rivals. As such, I would either know why (eg marketing budgets might have been changed) or I would be starting to ask serious questions to find out why.

Move from assumptions to proof

But now let’s introduce another search term into the mix to get an idea of whether it’s more a case that the Hilton is performing exceptionally rather than the Highland Resort performing poorly.

In this example, I’ve introduced the term ‘Aviemore Hotels’ as my benchmark term.  Whereas the previous terms are brand terms - and likely used for navigational search by people who are already aware the establishments exist,  ‘Aviemore Hotels’ is a more open search term that requires no knowledge of existing brands in the area.  Therefore it is more of a general benchmark indicator of the broader level of interest in hotels in the area. The result is shown in the graph below (click for a larger version or visit Google Insight here).

One thing that you should notice quickly is that the Hilton seems to trend more closely with the ‘Aviemore Hotels’ line than the Aviemore Highland resort does.  Indeed, the raw data enables us to determine that there is a stronger statistically provable correlation between ‘Aviemore Hilton’ and ‘Aviemore Hotels’ than between ‘Aviemore Highland Resort’ and ‘Aviemore Hotels’. In other words, the Hilton is performing in line with the market and the Highland resort less so.

Incidentally, even if we take the figures for Aviemore Highland Resort in isolation, using the raw data (available if you have a Google Account), we can see that the term ‘aviemore highland resort’ is now performing outside of control limits (defined as standard deviation x 3 - see more here about control limits) as shown in the graph below.

As virtually all web sites have cycles, we should expect to see some changes throughout the year but this suggests that the current change lies outside of what might be expected within these cycles:

So what does this mean?

For the Aviemore Highland Resort it means something may be wrong, beyond the level of a mere seasonal wobble.

My first actions would be to look at spend, bookings and occupancy data to see if there has been a corresponding drop in revenues.  (Afterall we are just talking about search activity here!)

I would look in depth at web traffic and conversions to identify which visitor segments and traffic sources I have lost search activity and potential business from.    I would also look closely at marketing activity and assess whether a drop in advertising spend has lead to this drop in search volume - and whether there is a cost effective way of rectifying that.  Afterall, it is common for people to respond to TV and other forms of offline activity by going online and searching on the brand name.  Is this what is occurring here - and does it even matter to the bottom line?  I’d want to know.

And if I were the Hilton Aviemore?  Well, I be heading off to Google Trends and comparing our overall website traffic for clues.  I’d be looking at my revenue and web analytics data to see if I was benefiting from this displaced search activity - and whether I was converting it into revenue.  And I would bullishly be looking at what I was doing right and be tempted to invest in doing more of the same.

So, Google Insight - used wisely - has the power to act as warning device for your business.  It’s free (and this article has only really touched on a small number of its features), so can you afford to ignore it?

Filed by Stephen (03/12/08)

Google’s business model is simple. It wants you to spend your money wisely on Google business products and, to help you achieve those ends, there are tools to make your spending decisions more informed.

Looked at from another angle, they offer a bunch of tools that you and I can use free of charge.

This post forms part of a series over the next few weeks that will show you how to make the most of tools like this - as well asking some more probing questions about how far they can really help you.

This post originated in a question I asked myself recently, “what exactly does the tool data in Google Trends and Google Insight show and what has this got to do with travel and tourism?”

At a top level, the answer is quite simple. Google Trends shows data relating to traffic to websites while Google Insight shows data related to search terms. However, what they have the potential to give you is considerable and so for this post, I’ll talk just about Google Trends, followed in the future by Google Insights and then finally a post dealing with some more ‘philosophical’ questions these tools have thrown up.

What is Google Trends showing and why is it useful?

OK, let’s start with Google Trends. If you click here, you’ll open up a new window with Google Trend data for visitscotland.com. At this point, you’ll see a graph showing daily unique visitors to the visitscotland.com site over a period of about 2 years. You’ll also see a bunch of data below it. Let’s look at those two elements in turn.

Before I get going though, I would like to stress that I’m using visitscotland.com here as an example only. The point of this is to look at data for your own site (assuming you have sufficient traffic) and to use the techniques contained in this post.

The graph shows a representation of the number of times visitscotland.com has been called up via Google. Note that this is not searches for visitscotland.com in a search box but rather the number of times someone has visited the site and Google has been in a position to capture that data (with some caveats).

Now, this graph can show a lot more but I want to mention the lower half of the screen before getting into that as it is where the data starts to get really interesting.

On the left, you get an indication of where the visitors to visitscotland.com and coming from. In other words, you can see by geography where the warmest prospects are.

In the middle, you can see which other sites were also visited alongside visitscotland.com. In our example, you can see sites ranked that you might expect to see - and depending on your perspective, this might be comforting or unsettling. For example, if you saw visitireland.com as the most visited other site, you would know that there was a real fight at this level to attract visitors who were torn between destinations.

And on the right hand side, you see the search terms that are most often associated with that site. Again, this might be revealing or comforting. For example, if you run a website for a DMO in a whisky distillery town and people find you only by the brandname of your whisky and not under something more generic like ‘whisky tourism scotland’, then this would be a sign that your site isn’t attracting as many visitors as it could.

But the fun really starts because you can start to compare sites.

Let’s demonstrate this by taking our example above and adding a few more sites - visitbritain.com and visitsweden.com. It should now look like this.

Let’s start with the graph. It shows that visitscotland.com attracts more visitors than visitbritain.com or visitsweden.com. It also shows that visitscotland has different peaks and troughs to the other sites at a global level (predominantly the effect of Hogmanay I would guess).

In the bottom half of the screen, you’ll see that you can segment this data by region and by website. You’ll notice that under the ‘ranked by’ tab, you’ll see how each geographic area performs for each of these sites. You’ll notice in our example how Scotland and Sweden are broadly similar in terms of interest in Germany. If, in the upper right of the screen, you use the drop-down box to change ‘all regions’ to ‘Germany’, you should see something like this.

So what’s this saying? It’s saying that, in this instance, people in Germany have show a greater propensity to visit the visitscotland.com site at a different time to the visitsweden site. That might be on account of a campaign by visitscotland in Germany…or it might just show a different ‘natural’ search pattern (and I’ll show you in a coming post how you can go about finding that out). If we assume on this occasion that German’s simply are more interested in visitscotland.com at the periods suggested, wouldn’t it make sense to have the website ready to react to this niche interest at the time? The data suggests that it might be wrong to assume that people think of destinations in a uniform way and that you need to be ready to respond to the customer when they actually come calling, not when you think they ought to be calling.

Conversely, if the spike was the result of an advertising campaign, this gives an indication of how long its effect lasted and how big it was in comparison to the spike caused by possible competitor marketing.

(I’ll hasten to add, I’m not passing judgment on visitscotland.com but just using them as an example - for all I know they might well be doing all this already!)

What I’ve described rather quickly in this post is one, powerful view that the travel and tourism industry can use to get a deeper understanding of how it sits in the online world. But, as is often the case, you need to look at other areas in order to build upper a more mature understanding and so this represents just one part of the picture. In the coming weeks, we’ll develop this theme further with more tips on these free tools.

See post 2 in this series - Warning bells you can’t afford to ignore: courtesy of Google Insights

Further reading:

Competitive Intelligence Analysis: Google Trends for Websites

“No one visits my site on their mobile phone…do they?”

As a researcher I shouldn’t deal in anecdote but, ignoring that cardinal rule, recent conversations suggest to me that tourism organizations and business are becoming more aware of the potential of people to access their internet sites by phone. However, while they know that this is a forthcoming issue, they remain unconvinced that this is something that they need to worry about just yet.

So, the purpose of this post is to give a primer into how you can tell if people are already accessing your site by mobile devises as well as some of the important issues about how this could develop and what the development of this method of customer’s accessing your site.

Before, I do so, I would like to thank the good folks at the Web Analytics Association for their recent seminar, “Measuring Web 2.0 Technologies Part 2” on which this post is largely based. That seminar is only available for WAA members to access but, if you are not yet a member and you have a serious interest in web analytics, do check the site out anyway.

Anyhow, I thought I would initially structure this post as a question and answer session before moving on to the issue more generally. I suspect that there are a lot of people that need to cover the basics before we look at some of the wider issues.

• Are people already visiting my site by mobile device?

The answer to that is, probably, yes.

• How can I tell?

The way to tell is the way that tell whether anyone has accessed your site: go and look at your web stats.

Specifically, you need to look through your web stats data to see if specific operating systems have been used to access your site.

Now, I am making the assumption here that you have something like Google Analytics or equivalent on your site (if you are the kind of business looking at raw log file data, then this article is probably too advanced or too basic for your needs!). If you are using Google Analytics, choose ‘Visitors/Operating Systems’ and you will get data on how people are accessing your site. The first three entries will probably be Windows, Mac and then Linux but if you go through the whole list, you might find some odd entries and some these will be people accessing your site on mobile devices.

I’ve ringed the entries on the image on the right (click on the image to enlarge) that are evidence (in this single example) of mobile device being used to access a single site.

• Wait a minute, why do you say ‘mobile device’ and not just ‘mobile phone’?

Well, look at the last entry on that list - it’s for a Playstation portable so it’s not just phones we are talking about here.

• How reliable is this information for showing my all the people who came to the site via mobile device?

At present, products like Google Analytics will not pick up visits from most common types of phones. It only really picks up people using ’smartphones.’

• What’s the difference between a smart phone and a normal mobile phone and why does this matter?

A smart phone is the kind of mobile with more advanced capabilities, like Blackberries or iPhones (see here for more details). I don’t have figures but they’re probably the minority of phones used just now but represent what we’ll all be using (in some modified form) soon enough. The reason it matters is that the evidence for website usage you will see will probably be for these sorts of phones.

For the moderately techie among you, this can be explained by the fact that smartphones are often javascript enabled whereas other phones are not and web analytics products like Google Analytics need javascript to be working on your system for their page tags to work.

• Can I track the same customer as they visit my site by phone and web?

Not really. Most solutions will see these as two separate visits and not realize that those two visits are made by the same person. You could get round this by getting people to log on each time they visited but, unless you have a compelling reason to do this, I think it might just be elevating the collection of stats over the user experience.

• OK, so I might have visitors coming to my site by mobile phone - so what?

Put simply, people will use your site differently through a mobile device than through a desk computer. This means that, in order to deliver what they want when they come to your site, you need to be aware of how they are acting in this different environment. For example, page can take longer to download, screens are smaller and some of the programs you take for granted on you computer might not be available on your phone.

So, if you want a site optimised for mobiles the first recommendations would be to look through your stats to see how mobile users are using your site. From this, most other decisions will flow in terms of content. The advice from industry leaders in the WAA seminar was simple enough: Once you see evidence of web usage by mobiles on your site, dig deeper and see what they are doing.

Are mobile users looking for specific content? Certain information may be particularly associated with phone usage - maps, directions, booking references for example - but look at your own web analytics data back up those assumptions. People may be using your site differently by phone. You can also factor in how long are they on the site (bearing in mind a long time does not always indicate a successful experience, but often a frustrating visit).

Some other suggestions I would have include:

• ditch any large graphic files;
• ditch the background music on the entry page (actually, just do this anyway);
• make it easy for the customer to get to where they want to go to - on a mobile, time is money and I don’t want to waste either;
• the mobile experience is more often about ‘just in time’ information rather than gathering a body of research - deliver accordingly;
• is what you are delivering commensurate with the mobile devices capabilities? For example, if you were delivering music samples via your site, you would need to know how big these could be.
• And developing that example: many mobiles do have MP3 players built in as well as cameras - can you take advantage of this somehow?

To round up, I can almost guarantee that the visitors to your website are using a broader range of devices than simply PCs and laptops. They may currently only be a small group - but they may represent a very valuable one. Its worth starting to look for them in your data so you can plan accordingly.

Further reading:Sunday Night Thinking on Mobile Analytics…

Great examples of the tourism industry successfully combining research and technology (and what the rest of us could learn from this)

My post last week was a bit of a moan - probably something to do with winter returning to Scotland and the general state of the world.  So, I thought I would balance out some of the negativity with some posts on people that are really getting things right.

Firstly, I would like to point you to William Bakker, director of eBusiness at Tourism British Columbia. As an area marketing agency, I think Tourism BC has one of the most sophisticated and advanced operations I have seen and the following paragraphs encapsulate one of the reasons why:

“We have conducted focus groups, phone interviews, card sorts and/usability tests to find the best way to organize the content on each website. We start with research about how our target audience in a particular market approach their trip planning; their mental model. We adjust our taxonomy where needed. For example, in North America a farm accommodation is called a ‘guest ranch‘. In the UK it’s called a ‘cowboy ranch‘ and in Australia a farmstay.”

What can I say apart from, ‘Wow!’  Although this approach might seem sophisticated to some, I recognise it as actually very simple at heart.  It’s the approach that says you should remember that your customers are human and need to be researched as such to get the full picture.

I particularly liked William’s comment about language.  This is something I think might be overlooked by a number of businesses and organisations but is vital if you want people to recognise what it is you are offering.  In some instances, you might get a clue to this if you are able to analyse searches made from within a site that have ‘odd’ terms but I think that the larger issue of language and its use is probably best started with real live people in focus groups.

Its an approach we always take in our tourism research projects as well - we recognise the immense value of quantitative data (whether that’s web analytics or traditional surveys) but feel that the best value is derived when you go that one stage further to probe the human element and combine it with the quant. I think this usually leads to a far more sustainable outcome.

You can read more at William’s blog here.

Another post that caught my eye was from the Karin Schmollgruber’s interview with Angela Zechmann(Director of E-Marketing and Internet for Salzburg Area Tourism) at the blog Fastenyourseatbelts.com. The interview is about about the Salzburg Area Tourism’s efforts to attract a younger audience to the area the site www.onebigpark.at and, in some ways, continues the theme from British Columbia that you need to understand that different audiences need information in a language specific to them.

But the other thing that made me sit up was that I was reminded of a conversation related to me a while ago about Austrian tourism to the effect that their ongoing research revealed that the country was having difficulty attracting young people.  I am not privy to the data for Salzburg so will assume that their research also suggests that, for mainland Europeans, Salzburg means Mozart and pretty mountains and, for people from the UK and the US, the Sound of Music - none of which suggests to me a largely younger profile of visitor (Angela, Karin - let me know if I am way off the mark here!).

And it’s not only a case of identifying an issue but doing something tactical about it with a considered Web 2.0 to help fulfil a strategy to encourage younger people back.  In other words, it’s a piece of joined up thinking and a good example of the intelligent application of 2.0.

The original is in German here and one of those rather odd internet translations for you non-German speakers can be found here.

My eye was also caught by this post at Phil Caine’s Tourism Tide on the potential conflict between Yield Management and Price Transparency.

To some of you, this might sound at best an arcane venture into a world far beyond your business.  I would disagree as it concerns something fundamental to all business - trust and transparency.  So, for example, reviews on tripadvisor at the moment just have people discussing the condition of an establishment.  What if those reviewers ever started comparing prices with one another?

Well, there are already moves that way in the accommodation sector with the likes of Farecast. This added-value price comparison site is essentially doing for the accommodation sector what price comparison sites have been doing for the transportation sector for a while.

For many establishments thismight not seem an  issue but, from experience, I know that accommodation prices can fluctuate at certain parts of the market and for much the same reasons as at the top end of the industry - such as sellers want to make a buck without having to pay an intermediary.

To that end of the tourism sector that thinks this is some far-off fad, let me say that this will happen whether you like it or not.  It doesn’t matter that you think of intercontinental air jouney is a big ticket item and your accommodation offering as small ticket item - customers will apply the same standards of transparency of value to both. Looking beyond the lowest common denominator horizon will help you prepare for changes like this.

Finally, I think the Canada-e-Connect Tourism Strategy Conference 2009 might just be the place if you are looking for intelligent debate and insight into how best to harness the new opportunities.  I don’t think the program is finalised yet but, judging on the people behind it, it won’t be looking at ‘lowest common denominator’ stuff but instead offering something for those with more vision.

For some of you, this might be an old story but bear with me…

Imagine a man with one foot in a bucket of freezing water and one foot in a bucket of boiling water. Taking the average of the water temperatures, the man would have to say that he felt comfortable.

Which is nonsense of course.

If I told you the average of the two buckets was 50 degrees, I’ve told you nothing about the spread of temperatures that give you a fuller picture of the real situation. And if you have commissioned me to do some research into the respective water temperature in buckets and I omit to tell you this vital piece of information, you are not getting your money’s worth.

So what’s this got to do with anything? Well, Vicky’s recent post on recession busting research tips started me thinking along similar lines and how managing your researcher harder with a little knowledge of their black arts can be a viable way of getting more band for your buck.

In the example above, having an understanding of the concept of the standard deviation is would have led a manager to ask a question that that would have identified the spread of results. Better still, the research company should have identified it themselves and explained its significance in this case.

And this isn’t the only area where a little knowledge can be a good thing. While many research companies will offer data such as the standard deviation as a matter of course, I suspect that it is rare that someone commissioning research at a less experienced level will know about some basic concepts and make their researcher work harder.

So, the following is for people commissioning research but unsure of what questions to ask once they receive it. I’m not going to go into mathematical depth with any of these (that’s what you pay me for when you commission the work) but instead you should consider them as more tools for your toolbox with which to prod your research company and your data. The following concepts are, of course, the tip of the iceberg and are chosen here because they are probably the most fundamental but common concepts that we come across which remain something of a mystery to many people.

The purpose of this post is not to befuddle or bore but rather to empower. As a researcher, we know we are going to be asked about sample sizes. We know that many of you remain to be convinced that focus groups are a good thing. But show us you mean business by understanding some of the following and you’ll surely get more bang for your buck.

Mean, Median and Mode

Remember that an average is more that the total score divided by the number of incidences (the mean). The median will tell you the middle point in that data and the mode will tell you the value that occurred the most. Each of these are telling you something different and noteworthy about your data.

Standard Deviation

The standard deviation is a measure of how close most of the results are to the mean. It shows you how far the results are from the mean - which then tells you how representative that mean figure is.  68% of results will be within one standard deviation and 95% (the more usual measure) will be in two.

Using the standard deviation would have told you that, in the example at the beginning of the post, 50 degrees lacked any insight as a figure. It would have revealed that the spread of results was so wide as to be practically meaningless.

Correlation vs Causation

There is a difference, between correlation and causation. The first suggests that there is a link between two events whereas the second suggests that one event caused another. For example, there is probably an historical correlation between the number of pirates on the high seas and the emergence of Europe from a mini-ice age. But one event did not cause the other. However, an upsurge in visitor numbers might cause service ratings to fall. The good news is that it is possible to prove whether a link does exist (whatever caused it) or whether you are just imagingin it. And you can even understand in some circumstances the exact scale of the impact of one event on another.

Statistical Significance

Statistical significance does not mean that something is interesting or noteworthy. Rather boringly, it simply means that something is likely to be true. For example if it were calculated that the statement that 70% of Scottish customers and 60% of English customers preferred continental breakfasts were statistically significant, it would mean that there really was a difference English and Scottish customers - not that the insight was a more exiting one than another insight.

In conclusion: this post isn’t suggesting that you should become experts in statistics. But having a little knowledge might allow you to start asking probing questions of the experts and working their findings harder.