Visitor data tends to get viewed through a rear view mirror.  Afterall, you don’t know how many people visited next week, only how many came last week.  Sometimes, visitor statistics don’t get reviewed at all until the end of the season.

But… if you have both physical visitor data and website visitor data, you may just be able to predict the future.  And knowing where potential trouble lies means you can concentrate limited marketing resources where they’re required.

How can this future forecasting work?  Well, the rhythm of the tourist as website visitor and the tourist as physical visitor are offset.  The website research visit occurs prior to the physical visit.

That offset could be months apart, with a drop in research activity in February – April, indicating fewer physical visits in July and August.  Or the offset could be just days or even hours apart.

Understand that offset – the relationship between the website visits and the physical visit – and you can build yourself an early warning system to steer your marketing.

Comparing by eye (well, by numbers actually)

While I will come on to statistical wizardry, you can break the rear view mirror mindset by doing nothing more than paying close attention to your web analytics data and graphing it in Excel alongside your physical visitor data.

Here is a real life example from a tourist destination website.  In this instance goal conversions have been used in lieu of physical visitor numbers, but given that the goals relate to conversions that tie to a physical visit – short notice accommodation bookings for example – it works for a demonstration.

As we see in this graph, the top line shows website visitors of this tourism destination website got off to a slower start in the 2008 season compared to 2007.

This suggests that slightly fewer people were on the website planning trips early in 2008, compared to 2007. By April, May and June 2008, website visitors were distinctly down, suggesting trouble ahead for the main season.

And more worryingly, in the lower line the 2008 goal (conversion) data shows an even more pronounced drop against 2007.

Just as the website visitor data suggested earlier in the season, come the peak of July, conversions were well down (and so, therefore was revenue).

Using a spreadsheet to highlight the proportional changes in visitors and conversions compared to a previous period, the website data gives a clue of the trouble ahead.  Fewer tourists researching the destination during the typical planning period warns of fewer tourists in the main season ahead.

This is enough to raise a warning flag and trigger tactical marketing action.

However, the website data becomes far more powerfully predictive when you accurately crack the web research to physical visit “lead time” for your business.

That requires a little dash of statistics.  (Don’t worry if there’s cobwebs on your school days maths – agencies like us can do this for you, or you can get an Excel whizz to help).

Correlating website visits and physical visits

With certain types of destinations, attractions and other tourism businesses it is possible to work out an approximate “research lead time” – in effect the delay between a peak of activity on key pages of the website (or overall website visits) and a corresponding peak in physical visits.

For the real life visitor attraction shown in the graph below, that research lead time is 4 to 5 days (with some variance according to day of week).

You can see in the graph that visits at the attraction (the lower line) track closely with visits to the website that occur 5 days earlier (the higher line).  Five days is enough of a window for that attraction to now test tactical marketing actions – for example when website peaks do not materialise.

How did we get to the 5 day mark?

It involved building a matrix of physical visits data with visits to the website and page views of research specific pages, then off-setting those website vists back through specific units of time.  Correlation analysis was run (you can do this in Excel) to see where strengths of potential relationships in the data lie.

While pages like maps and directions showed correlation at just a day or so lead time, classic research pages and overall site visits showed the strongest correlations at five days.  (Again, this is a simple view – day of week and time of year is also a factor).

By joining up the relationships between website visits and physical tourist visits, this tourism company now has a short, specific window of opportunity that it didn’t have before.  By monitoring its website barometer, it can react in order to “save” lost visits before they occur. More than that, it can time specific messages and promotions far more effectively than before.

So, if it would be handy if you could predict the volume of visitors to your destination or business in advance, think about joining up your online web analytics data and your offline visits.

What question would deliver maximum illumination, for minimum breath wastage – and help you fix any problem?

A smarty-pants might declare “why, its “Why?” of course!” And there are those who’d make a strong case for “How?”

Yet while “why?” may indeed be the best question in the universe, as a conversation opener it’s frankly a little scary.

Believe me, just hollering “Why?” at that retreating customer is going to make them run even faster. (And “How dare you?” won’t help much either).

It seems the perfect question clearly needs a little refinement before taking its place at the core of a business.

Perfect question(s) in action

Advocates of the Net Promoter Score would argue that the perfect business question is: “Would you recommend us to a friend or colleague?”

With this information obtained, the Net Promoter Score is then calculated as follows:

% of Promoters – % of Detractors = Net Promoter Score

While this is a very useful KPI, I think the challenge with the Net Promoter Score is knowing what to do next.

In my view the perfect question would help reveal a bit more of that “so what?” factor. In reality, that suggests a set of questions, rather than just the one.

Jim Sterne of Target Marketing and president of the Web Analytics Association talks about the perfect website survey, which asks just three questions:

1. Why did you visit this website today?
2. Did you achieve what you came for?
3. If not, why not?

This wonderfully simple survey establishes three important pieces of information. Specifically:

Customer Intent + Experience Outcome + Context

From this trifecta of data, a business has enough basic information to understand not only if there is a problem, but also the nature of the problem and whether action is necessary or appropriate. Without any one of the three pieces of data, the wrong conclusion could easily be drawn. (After all, an unsuccessful outcome doesn’t necessarily mean a problem).

The three questions identified in Jim’s survey are also surprisingly adaptable. It doesn’t take much to tweak them to suit a tourism business or destination, for example by asking:

1. Why did you visit XX on this occasion?
2. Did the visit meet your expectations?
3. If not, why not?

Of course, the key questions for you business may not be the same as those proposed by Jim. But I think these examples do give a view of how asking the right question can deliver data that can power business decisions.

But, while there may not be single perfect question, more like a little medley – don’t be tempted to overdo it. Two or three perfect questions that deliver maximum illumination, for minimum breath wastage beat a customer interrogation anytime.

If you’re going to ask great questions, don’t try and answer them too

A final tip – there is no point in asking great questions if you’re not going to listen to the answers. The answer to the perfect question is always a mystery until its uttered.

That means not forcing people to choose from a small selection of what you think their answer will be.

For example:

“There was a scorpion in the bathroom”
“My towels smelled of pizza”
“My ex was at the adjoining table”

Those are rarely options offered on tick box surveys!

For answers to the most critical questions to your business, ditch the tick boxes and let people actually tell you in their own words.

This adds to the time you’ll spend analysing the data – but it will give you answers you can actually use to make decisions.

Does this ring true for you?

Update, added 8th March - you might also be interested in this post by Avinash Kaushik, about 4Q, a new permission based on-exit survey that provides an easy to deploy framework to answer 4 questions that no website owner can live without.  Readers of this article may find those questions somewhat familiar!

In the first part of this post, I questioned whether customer comment cards really deliver useful benefits to tourism and hospitality businesses.

One of the reasons for the question is that I think often, far more effort goes into collecting and recording information than systematically analysing it in any depth. In other words, there is more effort in capturing the data than ever goes on evaluation or acting on that information.

My other concern is that comment cards and internal feedback surveys are often promoted as a customer research cure-all, when in fact they are best used as part of a wider suite of business intelligence and customer research.

Of course, comment cards can provide important guidance on operational development priorities and give insight into the needs and priorities of customers. But without systematic recording and analysis, it is easy to get tricked by the brain, which fixates on a few regularly heard comments and can misguide you as to the real issues within the comment cards and feedback surveys.

So, here are a few tips as to how I go about getting more from customer comments cards and feedback surveys. I won’t get into the in depth analysis we do with SPSS or postcode mapping – I’ll simply stick with what a business can do fairly simply, just using Excel.

Building a high impact “snagging” list

1) It’s useful to start by systematically recording all the comments in an Excel spreadsheet (if at all possible, record verbal and online ones too). If the comments can be traced to a specific date and time, it is worth noting this too, as the issues may lie with a specific member of staff, or only occur at peak or quite times.

2) On a seperate page of the spreadsheet, it is worth aggregating the comments, noting their frequency of occuance during the period of analysis.

If you keep the format the same across periods of analysis, it is then simple to compare changes and benchmark progress over time. Using the IF function together with conditional formatting lets you add in an automatic indicator that helps you clearly identify problem areas.

The Excel IF function can also be used as handy alert feature that highlights whether a change has exceeded your specified “tolerance zone”. This can be used to highlight issues that have seen a significant increase in occurances.

3) Personally, I also think its worth rating issues according to overall impact on visitor and ease/cost of rectifying. Again, you can use the IF and conditional formatting to help those high impact issues really leap out at you:

This makes it easier to see the less obvious problems – for example, look at all the warning signs being triggered for food choice in the visual example above.

This hard evidence, opposed to simply gut feeling, makes it possible to more strategically prioritise improvements. My advice is get past what your gut or brain tells you and let the data have a chance to speak as well.

4) Frequent analysis (weekly, or monthly) means not only do you keep on top of data, but quick fixes can be identified and rectified straight away. It also avoids the situation where comments cards pile up and analysis gets put off.

Some Excel tips

If you’re not familiar with using IF, conditional formatting or some of the other nifty features that help analysis in Excel, I would suggest you check out some of these posts:

Conditional formatting, at Life Hacker
The IF Function in action at Experiements In Finance
Displaying images based on conditional results at ExcelTips
and, just about everything on conditional formatting, aslo at ExcelTips

Ratings and cross-comparison

If the customer feedback surveys or comments cards require the customer to rate their experience, then it is also possible to for a business to start internally benchmarking performance based on those ratings scores. Again, here are some of my tips, that require nothing more than Excel.

1) To make it useful, the analysis needs to focus on meaningful trends in the data, rather than asolute numbers. (After all, a score of 4.5 is completely meaningless, unless contrasted with last month’s score of 3.8 or last week’s score of 5). Just as in the examples above, it helps to use conditional formatting and IF alerts to highlight when scores change by more than a pre-defined percentage. This will make the non-obvious leap out and not leave your brain misguided by the things it thinks it encounters most often.

2) It is also often useful to cross compare customer rating information with additional data sources.

For example, many businesses find that satisfaction dips slightly when they reach capacity and this may not be of concern. They may simply want to be alerted when both satisfaction and revenues or spend per head fall.

Likewise, a business may not want to simply rate staff’s service performance on the feedback scores alone, but cross reference them with (for example) the value of their tips. If a staff member’s tips and customer services scores fall in parallel, this is likely to indicate a bigger problem than the occasional poor score on a comment card!

Again, Excel lets you automate this kind of alert with the IF Function. You can, of course, also use a graph to visualise the two different data sources.

As before, it is generally more useful to look at trends, rather than absolute numbers . To avoid analysis paralysis, or its more virulent cousin “death by data,” it is worth looking at only a small handful of key ratios and comparisons. Focus on those that you can do something about.

And so to conclude

These are just a few of my tips – I’m sure other people have their own that really work for them. And that is the important thing.

Ultimately, useful analysis is tied to measuring what matters to your business and what is actionable. Nothing is gained from reporting on comments cards simply for the sake of it.

Of course, customer comment cards and feedback forms remain an important tool, but they are useful only if effectively analysed (as opposed to simply being inputted, or worse still, sitting on a shelf).

And if you can’t do anything with the data, save your efforts and don’t collect it! Ultimately, even the best analysis is only useful only if a business is prepared and able to act on the issues raised.

Tourism and hospitality businesses have long been urged to use customer comment cards and in-venue customer feedback surveys. And for many quality assurance schemes, they are a mandatory programme element.

But are they really the best way of gathering and evaluating meaningful continuous customer information, as businesses are often advised? Do they really give insight to market needs and competitive performance?

Or are comments cards at best a glorified “snagging list” – useful at delivering operational information, but giving little in the way of actual insight?

My concern is that comment cards and internal feedback surveys are often promoted as a customer research cure-all, when in fact they are best used as part of a wider suite of business intelligence and customer research.

In part 1 of this post I will explore my concerns with over reliance on comments cards as a research tool. In part 2 I will look at how tourism businesses can get more from comments cards, through systematic analysis and combining them with other data sources.

What is the problem with comment cards?

While I believe in the critical importance of soliciting and listening to customer feedback, I have two main concerns with an over reliance on customer comment cards:

1) Too little genuine insight

Often, far more effort goes into collecting and recording information than analysing it in any depth. There is more data capture than systematic evaluation or acting on the information contained.

I am aware of some excellent tourism businesses that have put a lot of effort into getting their customer feedback cards right, yet still express concerns that they do a lot of collecting, but struggle to get very little in the way of actionable insight.

Beyond the snagging issues, they find much of the data superficial, or lacking clear actionable outcomes and they feel they need to look to third parties like ourselves in order to get any depth of analysis from the information they hold.

Yes, the comments cards provide highlight issues that need fixing. Feedback surveys may also provide performance benchmarking data which, if regularly analysed, has value. But depending on sample size, this may not be particularly representative.

The cards can give marketing information about customer origin or their decision triggers, but again, this may only be part of the picture.

This is because comment cards and feedback surveys are self-selecting – particularly if it is left to the customer to seek them out. They are more likely to be used by the very happy and the very unhappy – but not the merely satisfied or indifferent. They are also less likely to be used by regular customers who soon get “feedback fatigued”, especially if they don’t see results from their input.

Which brings me to my second main concern with customer comment cards and feedback surveys.

2) Not a research “cure-all”

Customer comment cards are sometimes talked about as though they were a general customer research panacea. I’ve seen businesses participating in assurance schemes and other development programmes encouraged to put out comment cards, simply in order to check off the customer research box. Research mission accomplished.

But customer comment cards and feedback surveys, while they have value, hardly provide a 360 degree view of market needs and competitive activity.

After all, what about all those potential customers who never even make it through the doors?

At worst, over reliance on customer comment cards can be a distraction, or even waste resources if more effort goes into data capture and reporting than the potential benefits really justify.

There is no single research tool or data source that has all the answers a business requires. Comment cards are just one in a suite of options open to businesses and shouldn’t prevent focus on other intelligence sources.

And for most businesses, they are not even the most useful data source available. If given the choice of only one metric one which to base their decisions – unsurprisingly, most businesses I have spoken to would choose cash/revenues as their critical measure.

Should customer comment cards be abandoned completely?

I don’t believe all customer comment cards and feedback surveys should be abandoned – not at all. However, I do think an over reliance on them at the cost of other research approaches can be unhelpful.

Of course customers need the facility to give you feedback they may not want to say to your face (or may not have had the opportunity to give verbally) and comment cards and feedback surveys are a very good outlet for this.

But collecting comments shouldn’t stop at the door. Customers also give comments on third party review sites like Tripadvisor as well as on agents websites and in blogs and online social networks. There are tools that let you see these comments – why not include them in the research process too.

Systematically combining customer comments and other feedback allows a business to identifying quick fixes and strategically prioritise developments.

And of course, customer comment cards and feedback surveys can also be used as marketing tool – particularly where personal information is captured.

They can also aide performance benchmarking and staff engagement, provided they are actually analysed.

So, I am not advocating abandoning comments cards, but I do think they should be:

1) promoted as one of a suite of businesses information sources, and

2) properly analysed in order to deliver real business value

Of course, customer comment cards and feedback forms remain an important tool, but they are not a research “cure all” and can’t be used in isolation.

They are useful only if effectively analysed (as opposed to simply being inputted, or worse still, sitting on a shelf) and only if businesses are prepared and able to act on the issues raised. After all, if you really can’t do anything with the data, why not save your efforts and don’t collect it!

In Part 2 of this post, I will get practical and look at some of the ways businesses can get more value from their efforts, with in depth analysis of their customer comment cards.

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Jacobite, the five star attraction owned by Freda Rapson, offers cruises and a wide selection of tours and charters sailing on the legendary Loch Ness throughout the year.

As Tony Mercer, Head of Quality & Standards at VisitScotland says:

“Jacobite is a worthy holder of the 5 star Tour accolade as it sets very high standards in the hugely important day trip market. Visitors and locals alike can enjoy the experience of viewing some of our most famous sites, Loch Ness and Urquhart Castle, from the loch itself on an informative and comfortable cruise combined with coach trip.”

Playing close attention to business data, visitor satisfaction and balanced scorecard KPIs has been of great significance in growing this successful business.

However, Freda believes that for maximum success, it is essential that a more joined up approach to visitor data collection and dissemination is undertaken at a local and regional level.

She regards overcoming dated and disjointed local visitor data as critical for tourism businesses like Jacobite, in order to fully maximise their marketing to geographically discrete markets.

As Freda explains:

“I’ve got a bee in my bonnet at the moment about the amount of customer information that is out there but is not joined up. We collect information mostly from our customer feedback cards. Nationality/visitor origin is one of the main statistics we pick out, so we’ve got that information. And somebody in another business down the road has that information. But nobody links it together.”

“If we all had three standard questions that were asked, and that data was centrally analysed and shared between businesses, it would be such a simple thing.”

The Austrian visitor data example

Freda describes her experiences from a recent learning journey to Austria, where she found near perfect statistics for accommodation occupancy, seasonality, year on year trends and overnight visitor nationalities.

“In Austria, organised by government, everyone that checks in has to give name and nationality. This added to the hotel specific (eg 4 star, location) which all goes into a central database. It means that everyone that spends a night in Austria is recorded. It is so simple, why can’t we do it? Clearly it would require legislation/central co-ordination but its not rocket science. Its so do-able.”

The Austrian research process that Freda refers to is described at some length in this very useful research paper by Karl W. Wöber (Institute for Tourism and Leisure Studies, Vienna University, Austria).

I would agree with Freda that the data collection process is both do-able and very important, though I would add that there are complexities and challenges involved, particularly of the political and administrative varieties.

It would, for example require not only careful planning, but a long term financing model that would allow the data to be collected of a number of years. There would be challenges to ensure that smaller or poorer areas were not overlooked or excluded.

As Karl W. Wöber writes about the Austrian experience:

“Due to the refinancing interests of data collection authorities and the lack of financial resources in the tourism industry, however, the data analysis for smaller tourism regions or report communities has been prevented in the past. This factor must be regretted since it can be assumed that the evaluation of key success factors in tourism marketing will significantly improve when they are measured in smaller regional units.

Also tourism managers, especially those operating on a regional level, usually have only very little influence in the organization of nationwide surveys. Therefore, many of the statistical series are based on administrative regions that are not always congruent with actual regional use and by tourists and subsequent flows.”

Nevertheless, there is no reason why the 20 years plus of learnings from regions like Austria could not be taken on board to ensure that any process developed in Scotland does not fall at obstacles that have already been encountered elsewhere.

How could such data be used by tourism businesses?

Clearly even the most accurate data has little value if it is not used. As Freda adds “its all very well recording it, but what matters is what you then do with it.”

She explains how such visitor information would be utilised by Jacobite, most importantly “to understand profile of customers.”

“Our customers don’t match the old regional survey data that was conducted on the street. Groups, for example, get missed. If data such as visitor origin were accurate it would clarify who we are marketing to, so we could target and promote accordingly. We’d ask what are we doing in the key areas where the bulk of visitors are coming from”

She continues “I do think that there is a lot of fallacy out there. People say we’re not a family market, or not a short break market. Or people say there are no German or Spanish visitors out there. There are.

I bet you if you counted them, there are significant numbers but they’re being missed. For example, the official stats say roughly 1% of visitors are Spanish – but that is not the picture I see in my business.”

“I know what our percentage of our individuals and groups are in terms of nationality – and somewhere, those people are staying here. As a visitor attraction, we see the key link as being with the accommodation providers. Visitors come and stay and then look at what they will do. There must be a point of contact to record that visit – even if that needs legislation – so the visitor data is accurate and truly reflects our business.”

At a destination and country management level, there are of course many other potential uses for joined up visitor data – from comparative regional profiles to package targeting. But what I think is significant about Freda’s viewpoint is that she makes a very strong case for how individual businesses themselves will also profit from better quality data.

And given that is individual businesses like Jacobite who will be responsible for achieving Scotland’s revenue growth targets over the next decade, I think Freda has a strong case for putting joined up visitor data at the top of the tourism industry wish list.

Eden Project image by Jürgen Matern

As David Meneer, former Eden Project Marketing Director told the audience of last week’s Marketing Society conference: “we love provoking the envy of others”. And with the iconic attraction having settled at annual visitor numbers of around 1.2 million, while expanding its offering to encompass books, rock concerts, green car shows, surf boards and ice skating – there is indeed a lot to inspire the envy of visitor attractions worldwide.

But what I found particularly fascinating was David’s statement that they conducted “no research whatsoever” before opening the Eden Project. The reason? Because, after all, how many potential customers would think a big greenhouse in a pit in Cornwall was a good idea!

David has a point. And just look at all those potential customers and locals that think XYZ museum/attraction is a great idea at the feasibility research stage – only to fail to materialise after the attraction launches.

The Eden Project may not have conducted customer research prior to their launch – and they continue to attach little or no value to qualitative research process (”just a rear view mirror”) – but they did speak to 250,000 people before the project even opened to ensure local buy in and public support. It seems they invested their energies on word of mouth promotion and local engagement, not public consultation – an approach that brought them positive results.

So, to what factors do the Eden Project team attribute their success?

In his Marketing Society presentation David spelled out the top 10 factors that he believes account for the Eden Project’s success:

• Zeitgeist
• A big vision
• Scale
• Iconic architecture
• Media friendly CEO
• Location and locals
• The team
• Square pegs in round holes
• Agility
• Out-thinking not out-spending the competition

Vision, energy, confidence and a “try it and see” approach (reflected in so many of the factors above) is clearly at the heart of the Eden Project’s success.

Their success also seems to be passion driven, rather than data driven – so, perhaps its unsurprising that the factors they most attribute to their success are those least likely to be apparent in a feasibility study or pre-emptive qualitative research.

Does the Eden project use research now?

David explained that while they still undertake no qualitative research, they “do a ton of quant” – to the extent that there is the risk of “analysis paralysis” and “disappearing up your own bum”. (Nicely put!)

They are clearly doing a lot of valuable database segmentation work and have a strong grasp of the metrics that matter to them, but as David explains, they use the quantitative data with caution in that “we don’t let the minutiae dictate what we do”.

Appropriately, given the sustainable and ecological nature of the Eden Project as an attraction, the critical element of their approach to research (and indeed their overall strategy) is balance.

Into the future

Going forward, the Eden Project’s success will no doubt rely on continue its fine balance of data and instinct, the opportunistic and the planned, the old (leaflets) and the new (database) and the unpaid (pr) with the paid – all in a business environment that is fast paced and agile.

As David acknowledges, “its not easy to get one million visitors a year” and while the role of Marketing Director will now pass to someone else, it seems likely that the Eden Project will be “provoking the envy of others” for a good while yet.