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Villarenters Clickstay – Finding out about my Guests

What can I learn from my previous Guests? What trends to they show, and how can I use that information? I want to understand how to double my rental income, and I am starting with research. First of all I need to analyse all the information about my past guests. My bookings have always been via online booking systems. I haven’t ever taken cash or cheque payments for the sake of security for us and our guests*. So all of my bookings and past bookings are online and the data about them is available to me, in one form or other.

Currently I use 4 online booking systems : Clickstay / Villarenters, AirBnB, Flipkey and HolidayLettings. The majority of our bookings have been via Villarenters, which became RentalSystems and now Clickstay. I am not saying that this the best system, and certainly Clickstay/Rentalsystems/Villarenters has some shortcomings. I will be doing a full review of all of the online booking systems so that I can choose the best ones for me – but suffice to say that I have used Clickstay / Rentalsystems / Villarenters the most, and it offers the best access to our customer data. Its a lot of data from 150 completed bookings.

So my first job was to log into the control panels of my online booking systems and ‘cut and paste’ all the booking data into a spreadsheet. It took quite a while to organise the data from 4 different systems so that it was in the correct columns, but once I’d done it, I had a full listing of all my bookings. It was clear straight away that Clickstay / Rentalsystems/ Villarenters provide the most complete data; even down to email and postal addresses of all guests, and the names and ages of everyone in their party. This information was invaluable when organising the houses for guests’ holidays and will useful again for analysis.

I admit to being a fairly expert user of spreadsheets; this sort of data analysis is second nature to me and its been a constant skill that I’ve honed throughout my career in Marketing. I can understand that it may be harder for others, but I really think its worthwhile.

Looking at the data I could see again the revenue track that fell off a cliff after our first two years. The worldwide financial crash landed here in Ireland and we’re still digging our way out of it. But looking closer at the numbers I could see that the distribution of incomes across the months of every year was the same. In good years and bad years August was the top month (by a mile); June and July are very important too, other some months had hot spots. February is a write-off we’ve never had a single booking then – so that’s the time for repairs and re decorations. I am tempted to think that they same distribution pattern of rental revenues can be applied to my challenge – its a pattern that I can use to create my revenue model.

Using the same revenue pattern it should be possible to project just how much of my rental revenue I will need in every month if I am to Double my Income. Of course occupancy levels and competitive rental rates will affect this projection – but this is validated information, and its useful guide.

MapsData Guests data Clifton Youghal Guests data Clifton Youghal

Using the Clickstay / Rentalsystems/ Villarenters data I could also dig deeper into my guests, where they came from and their relationships. Its amazing but some booking engines seek to hide these crucial details about your guests. I was able to see clearly that over 60% of our guests come from the UK (including Norther Ireland) whilst only 16% come from Ireland itself. This is really interesting, and although I might see the Irish market as having growth potential, my emphasis should be on our biggest market.

Thanks to the fabulous (and Free) I was able to simply upload the list of UK postcodes and get this visualisation of where my guests come from within the UK. I was genuinely surprised by what I found. It shows a predominance for visitors from the South East of England. Certainly, this is where there is greatest density of population, but travelling from here presents the greatest difficulty/expense and in my mind I thought that this was a barrier. The journey from London to the seaports in Wales is a grueling 6 hour drive, on a good day. If you factor in weekend/ holiday/ commuter traffic jams it could easily take 10 hours or more. When I have done the journey I have always taken an extra overnight stay each way.  When you add to that the 3 hours sea crossing and 2 hours from Rosslare port to Youghal you can see why I’d expect visitors from the South East of England to fly Cork or Waterford. There are plenty of flights, but with a family those flights and the essential car hire will add considerably to the holiday costs. Give all of the above, I had believed that guests from other parts of the UK would dominate. For example a guest from Manchester would only have a 90 minute drive to a seaport in Wales, and the journey from Dublin port is only 2.5 hours … so the total journey could be completed in 7-8 hours door to door – including a chilled out ferry crossing. The costs of traveling this way are much less than half the costs of flying and car hire. And yet – we’ve not had a single guest from Manchester or Liverpool! Is this an opportunity? Or is it, more likely, and indicator that guests traveling to us are less price conscious that I had believed.

When we first started we priced in Sterling, targeting UK  guests. We now price in Euros (and changed over in about 2010 during the crash). I wonder if we should revert to Sterling pricing in deference to our prime customers.

Only Clickstay / Rentalsystems/ Villarenters record details about the whole party who are staying. By using the names and ages of everyone I could work out (or interpret) family groupings, where they existed, and this proved really useful. Again I learned somethings new; although mostly I bolstered my belief that we are primarily meeting the needs of Family Groups.  I was even able to split Family Groups into three sub-groups, 3G (three generation families), F (one -or two related- nuclear families) and FT (Families with only 18+ children).  These three family groups accounted for 90% of all bookings. The FT group was much the smallest, but still larger than other guest groups I’d recognised – C (a couple) and OF (Old Friends – unrelated groups of adults who might be couples).

And so, while we may have some other guests groups, (so far) we have been a holiday home for families. Of course this is not really a surprise, its what we set out to achieve, its how we have laid out and marketed the houses. And you can also say that we’ve actively prevented (and discouraged) some other guest groups. Since day one we’ve had a block on single sex groups where the average age is below 35. We really don’t think that we’re the right property for Hen/Stag groups and so we’ve blocked them. And of course our bedroom layout isn’t ideal unless for a family – we have two double bedrooms and two twin bed rooms in each house. I am considering whether to buy ziplock mattresses so that at least one of the doubles could provide a 3rd twin bedroom. This would increase flexibility but I’m unsure if the expense would generate significant new incomes.

Reviews of 3 Clifton Youghal on Clickstay Villarenters
Reviews of 3 Clifton Youghal on Clickstay Villarenters

Finally, in my deep dive into Villarenters data, I looked at our online reviews. As you can see we rate 5 stars across the board … that’s fantastic, but I wanted to see what more that I could glean from the actual reviews.

I turned to ‘cut and paste’ again and I put all of our online reviews into one long text document. It was over 20,000 characters long. I was sure that there’d be some way to analyse it that would create new knowledge.

I turned at first to a technique used in web site Search Engine Optimization – called word density analysis. This attempts to find the important words, the ones that are most often repeated or highest prominence, within a block of text (usually a web page). Word Density Analysis is used to ensure that web text is sufficiently ‘doped’ with the right keywords that Google can find; and use to classify the page. There are lots of online and offline tools to test Word Density; and sentiment analysis tools too, which is an associated technique. Often you can just paste your text into a box and get a free analysis;  but my text was too long for many of the free tools. And, in truth, what I got back was less than revealing. TagCrowd is one such tool, and it created a nice image where the most repeated words are magnified (you can see it in the associated video) but, it didn’t really tell me much that I could use. I’m sure that TagCrowd is great for its intended purpose, but for me its wasn’t; it looked good but was not insightful.

The problem was that the reviews contained key ‘phrases’ not key ‘words’. And the phrases are of various lengths and often associated with the sentiment of the sentence they appear in. This is not easy for a piece of software to analyse. There may be very sophisticated software which does this, but not for free!

I turned instead to a technique used by real statisticians and friends, Dimitris Samiotakis, and his wife Mary. Dimitris is a world expert on surveying users, particularly users of cars. Finding out what they love and what they don’t. Some of his data is easy to collect – users score their car on certain things in a survey. But other data has to be gleaned from within interview scripts and online comments (just like mine). And for this they use what they call ‘coding’, and its a skilled manual job. Now I am certain that their technique is far more sophisticated, but what I did was to use a home made variant of ‘coding’ to draw out the key phrases in each review and classify them into groups. I didn’t preset these groups, but they quickly appeared as I started to do the coding. There were phrases about the ‘Home’ and its ‘Size’ or ‘Equipment’ or ‘Decor’. So I created a Group called Home, with sub-groups for size, equipment, decor etc.. There were phrases about the ‘Location’ and how it was ‘Walking Distance’ to beach or ‘Easy Reach’ of many days out by car. I created a Location group and subgroups for beach, lots to see, etc…  Each time a ‘Group’ or ‘SubGroup’ was mentioned or alluded to in a keyphrase then I added a score of 1 to that Group or Subgroup. From this I generated the following results which is a count of the most mentioned factors within our reviews..

Villarenters Reviews for 3 Clifton Youghal Coded
Villarenters Reviews for 3 Clifton Youghal Coded

Unsurprisingly the majority of phrases were about the house(s). After all this was a Villarenters review specifically about the stay in the house. But breaking down the results its clear that many guests are made to feel special and get an overall sense of ‘Wow’ from the house, and this is the most noted factor.

The location is within easy walking distance to beach of and town is a big draw, and the spectacular sea views are constantly mentioned (of course they provide much of the Wow too!). And the other significant group of phrases (praises) goes for the quality and availability of equipment and facilities in the house.

This is all important stuff, and I need to make sure to remember this research when I am rewriting our seductive description and selecting imagery to sell our holidays in the future. It’s really important too to use this research when comparing and contrasting our offer with our competitors.

After I finished filming my Youtube video I was discussing some the new insights I had discovered within my Villarenters data, and it was suggested that I try and see of I could narrow in on the Demographics of my guests, again using their Postcode. Sure enough, when I looked on Google, I found OpenGeoDemographics a free service  that will display some amazing work that’s been done by geographers. The Output Area Classification (OAC) is a UK geodemographic built in partnership with the (Office for National Statistics) ONS and is created using the 2011 census data. With this data they’ve created a set of just over 30 OAC codes, for each they have created descriptions that might typify the area and describe its typical inhabitants. In fact, as I discovered, you can burrow down and get really detailed analysis of every postcode … but that was more that I need. My objective is to get close enough to be able to describe my customers, and I think that the general description of the people where they live is likely to help; but I don’t think its helpful to move into the real depths of the census returns for that area.

Using Villarenters data I have created demographics of UK guests
Using Villarenters data I have created demographics of UK guests

I found that its really easy to get the information I wanted – just using the PostCodes I downloaded from my Villarenters / Clickstay guests. I simply fed in the 100 or so Postcodes into the form on the front of the OpenGeoDemographics website and noted down the OAC code and the description given. Again I recorded these on my growing spreadsheet of data. And then I summarised it.  What I found was that our guests come from a variety of types of area and types, but there is a real concentration, with over 2/3 of our guests concentrated in just 4 of the 32 sub-divisions. These are OAC codes 5a, 5b, 6a, 6b which are described as follows…

Group 5 are the Urbanites

“The population of this group are most likely to be located in urban areas in southern England and in less dense concentrations in large urban areas elsewhere in the UK. They are likely to live in either flats or terraces that are privately rented. The group has an average ethnic mix, with an above average number of residents from other EU countries. A result of this is households are less likely to speak English or Welsh as their main language. Those in employment are more likely to be working in the information and communication, financial, public administration and education related sectors. Compared with the UK, unemployment is lower.

Sub Group 5a – Urban Professionals and Families
The population of this group shows a noticeably higher proportion of children aged 0 to 14 than the parent group and a lower proportion aged 90 and over. There is also a higher proportion of people with mixed ethnicity. Households in this group are more likely to live in terraced properties and to live in socially rented accommodation. Unemployment is slightly higher than for the parent group.

Sub Group 5B – Ageing Urban Living
The population of this group shows a higher proportion of people aged 65 and over than the parent group. Residents are more likely to live in communal establishments, detached properties and flats than the group, with a higher proportion of households living in privately rented accommodation.”

Group 5 are the Suburbanites

“The population of this group is most likely to be located on the outskirts of urban areas. They are more likely to own their own home, to live in semi-detached or detached properties, and to own their home. The population tends to be a mixture of those above retirement age and middle-aged parents with school age children. The number of residents who are married or in civil-partnerships is above the national average. Individuals are likely to have higher-level qualifications than the national average, with the levels of unemployment in these areas being below the national average. All non-White ethnic groups have a lower representation when compared with the UK and the proportion of people born in the UK or Ireland is slightly higher. People are more likely to work in the information and communication, financial, public administration, and education sectors, and use private transport to get to work.

Sub Group 6a – Suburban Achievers
When compared with the parent supergroup a higher proportion of households live in detached properties and flats, and are less likely to rent their accommodation or live in overcrowded conditions. People of Indian ethnicity are over-represented when compared with the supergroup. Higher proportions of people have higher qualifications, and are more likely to work in the information and communication, and financial related industries.

Sub Group 6b – Semi-Detached Suburbia
People in this group are more likely to be divorced or separated than those in the main group. Households are more likely to live in semi-detached and terraced properties, with a higher proportion of households renting their accommodation.”


*Regarding only selling online; I am pretty sure that this is the right decision. But in mentioning this I think I should revalidate if my reasoning is sound.



Video Transcript for those with text readers.

“Welcome to my challenge to Double the  Rental Income from my holiday homes.  Hi I’m Martin Finn and welcome again to  Double my Rental Income. In this  edition I’m going to talk a little bit  more about research; that’s where I got  up to last time. I said that I am very  much in the research phase. I thought to  myself where can I start what information do  I have? What hard facts do I have? That I  can base my initial research upon. And of  course we’ve been renting out our  properties for a number of years, in fact  we’ve had hundred and fifty successful  rentals. So there’s a whole load of data  there which I might well be able to  access. That’s where I’m going to start.  You know that I have a revenue  plot, and the revenue plot looks pretty  much like this. You’ll see the 2010 2011  were really really tough years.We  started at fantasticly in 2007 but boy  we fell off a cliff in revenues and now they’re  rebuilding. But let’s not forget that  they’re rebuilding now with two  properties, we started with one. So  you can see why I want to double our  rental income, because I believe we can,  we used to be there and we have two  properties. So where I can I go, what are my  sources of information? Here’s our  bookings page on rentalsystems.  Those of you that know rentalsystems may  know that they were originally called  villarenters, now they’re called  rentalsystems and they are also now  called Clickstay. I’m not sure what  their name is going to be in the long term but  majority of our bookings have been  through this (online booking) engine. I’m not necessarily  saying they’re the best, by the way, later  on in this whole series I’m going to  be reviewing which are the best (online) booking  engines for me. Currently I use four but the bulk  of our bookings come through rentalsystems   and one of the great things, one of the things I  really love about rentalsystems   is the fact that the customers  feel like they’re mine. So I’ve got a  whole load of information here (which I can use)  (Its a bit difficult to get it off the page),  there’s no way to download information,  although there used to be, by the way, but  if I cut and paste (all) this and put it into  Excel, then I can create for  myself a huge database of  information like I’ve got here. So I know wealth  (of information) about every one of our 150 previous bookings. What have I learnt?  We know about the revenues but looking   beyond the revenues and you’ll see this  rather complicated chart. (Revenue by month and year). Numbers  across the bottom of the numbers 1 to 12  are the months of the year  Notably ‘2’ isn’t there we have never had a single  piece on revenue out of February. Now if  there’s ever a month when that I know  that I should be closing down to do  (repairs or redecoration) its  February.  (This chart) also shows me is August is  our biggest month … by a mile  I knew that anyway, but it’s interesting to see it  because the different  colors represent different years and even  in our appalling years you can see  the exactly the same pattern or spread (of revenue)   across the months. The same months generate  the same proportion of bookings. So I  don’t think it’s a bad idea to interpret  this further and say in Doubling my  Rental Revenues I should be looking  again for the same ‘distribution’ of  revenue across the months, if that’s  possible and if the rates will bear it. What  else have I seen?  Well because  rentalsystems treats the customers as mine I  have all details about (those) customers which  of course includes where they’re from.  And I mean specifically where they’re from  given their address that’s really useful.  Because I can do this which tells me  exactly where (by guests come) from in the world  The big red line tells you even though I  am on the south coast of Ireland my biggest market  is the UK …. by a mile  My biggest market,  and the fastest growing as well. The  Irish market was big; one year it was  bigger than the UK market, but since then  hasn’t sustained itself and if we now  get as much business from Northern  Ireland which, although it’s on the  island of Ireland, is actually part of  the UK and operates in Sterling. In fact  we used to price in Sterling and it’s  worthwhile (for me)  reconsidering whether we should again  price in Sterling rather than Euros. The  bulk of our business is from Sterling using  countries.  Out US business did start out well but has  declined. Wether that  will will rise again I don’t know. It’s  not really (something) that I can impact  Getting tourists back to Ireland isn’t my (responsibility).  My target market is primarily UK, although  there may still be growth to get from Ireland, its on my doorstep after all.  What else have I learned? Well here is some   fascinating information  You see, rentalsystems they asked if customers something that I  do not see any with other (online) booking engine. When I get a  booking it tells me how many people are  coming, and also their age distribution  and also their names. Given their  age and their names I can work out   a number of really interesting things  I can actually interpret, what kind of group they are.  Are they a family? Are they friends? Are  a three-generation family? The red line  is a three-generation family and you’ll see it’s my second largest market.  My largest market are family groups. Now that  maybe Mom dads and kids or it may be mom  Mum Dad and  Aunty and Uncle and all the kids. The houses  can take up to nine people including an  infant, so they could be two small  families – and that’s still a family  holiday.Family holidays and three  generation family holidays are, by  a mile,  my largest markets.   What else? Who books our holidays ?  When do they book? And what do they like? First  of all 63 percent of the people who  actually booked were woman. That has  reversal of the trend  in our family.  When do they book?  75% of the peak season bookings   are made befor the end of  February. If I hadn’t sold the peak season  by the end of February probably not  going too.. alarm bells should be ringing.  Interesting early, because of the data  was there as well…  …people tend to book on Monday Tuesday or  Wednesday  Worse day for bookings in his Friday.  I can only interpret this as people  researching over the weekend and  then you’re saying right let’s go for it.  Monday, Tuesday or Wednesday and  definitely before the end of the February  for the peak season. Interestingly if you look  at that gap between when people book and  when they’re coming … depending on the  time of year that gap varies. So people  coming at Easter don’t tend  to book ’til February. This is much shorter window  for Easter holiday holidays.  This is really interesting information  I’m sure I’ll find some purpose for it.  What do our customers like?    Well how am I going to find that out?  Well let’s look at the reviews. So again  I’m going to go across and look at our  rentalsystems, now called Clickstay  page. And you will see here that we have  one property, 3 Clifton Youghal with  37 reviews. We’ve a whole bunch of reviews  on other property 4 Clifton as well.  If I go to these you’ll see  that we’ve 37 verified reviews and … Wow we’ve got  five stars all over the place.   That’s great news!  We love to see that, it’s really  what we’re aiming. But I want to know  a little bit more about them. It’s  been a bit of a pain but all of these  reviews here have a whole load of words  behind them and what I’ve done is taken  all of those words and put them into a  a document. You’ll see  here, I’m just on just scrolling through this is a  Word Doc where I’ve literally taken all of  those reviews and dropped them into a  single Word document. Its actually 21  thousand (characters not words). I can read through  them but what does that tell me.  I thought I would try to make some   sense out of them. I would just  pick out of each of those reviews active  (phrases),   I tried to miss out all  the connecting words to  you just say the summary words here.  Where people said ‘fantastic location’  ‘helpful and welcoming’ i was picking  out real active phrases in the sentences just  to make sense of those. I experimented with  thing called TagCloud and just dropped those  words in and you get this nice picture here  where you know each of these words are displayed (bigger for more frequent).  But I really couldn’t do much with that…  I went back to these lists of active words and I was  convinced there was something more I  could do. Something better, better  analysis, that I could make this to turn  into something really useful information for me.  So I took the active phrases and placed  them all into a spreadsheet and then  ‘coded’ them. I’ll use the word coded am I  put them into groups. You know, what was it  talking about…  “5 to 10 minute walk from the  beach” is talking about the ‘Location’ of  the house and it’s talking about a  subgroup of its location, vis-a-vis the ‘Beach’  Just a simple classification. Then I  used the thing called a pivot table to  actually explain that data…  and we can  see it a little more clearly – here.  We have some main sections of the top.  People to talk ‘FUN’… only a few.  Most people talked about the home,  and it’s not too surprising. Because  actually this is a review system  reviewing the property that they rented,  so I’m not getting overblown by that. I  actually needed to dissect the data further than the HOME. The LOCATION. The OWNERS.  The TOWN,  and that was actually mentioned  rather less than I expected. And VIEWS.  Our properties have stunning  views over the bay, so I wasn’t at all  surprised to see that. So I have some  data here, but I wanted to look at it in  more depth, to try and find out which was the  most important data.  The bulk part is about the HOME and its no great  surprise. Digging deeper 32 times people  mentioned the specialness of the house  the Wow factor that’s really really  important. I’d always thought the Wow  factor was important but it is  interesting to see I’ve got some hard  data here to show how many times people  talked about that Wow factor, more than any  other individual factor.  28 times people talked  about location. Our properties are really  located well. First of all   within the space of our town, its very easy  to walk to the beach and just as easy walk  into the town and the bars and  everything else, you don’t need a car to  do any of those things you can just stroll.  Which is people really love. We’re also  located well within  Ireland. If you have a car you can have  day trips and go to loads and loads of  places around here. Obviously location  location location is always important  with any property, and this is true here  with our holiday property. The next thing  that people spoke about was the VIEWS.  Clearly that’s part of the wow factor as  well but they specifically mention the  views on I need to make sure people get  that when I’m going on to market and talk  about property, to entice new guests I  need to talk about that and really show  those views off. The last one that I  picked out here was Equipment and  furnishings. People are genuinely  surprised and delighted with the amount  of equipment and furnishings and quality  furnishings that we have in the house.  We made it our objective in the  houses that if we ever stayed somewhere  and they had some piece of  equipment or furniture that we saw and  thought “yeah it’s really good”  We made sure that we have it.   People were surprised by that delighted  by that. So I need to make sure that  that is pressed forward in when I come  to do the marketing (messaging). So these are the key  findings from looking  at all of our existing customers   and what they had to say.  Diving into that data  from rentalsystems and, all of this  comes from rentalsystems data – diving  into that – I’m sure there’s a lot  more than I can learn as well and on  the blog that I’m about to do I’ll  probably list some of the other things I  found that. Finishing on this  first stage of my research,  and boy there’s a lot more to do!  I just like to say thank you and I hope to see  you again.  I hope you enjoyed that episode of Double my Rental Income and I really hope you’ll join me again.  Don’t forget you can find out much more about  my challenge in how it’s progressing by  visiting the website  You can sign up on the website too and  get the very latest news and some extra  special content which I can’t make  available elsewhere. So please join me  again and remember- if this has been  valuable to you- I’m giving it to you for  free but I do make a request  share it with others let them know too. I  want as many people as possible to start  using some of the things that I have  spent so long to create  Thank you”


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