Travel businesses are luckier than many other sectors. They have data on their customers and their customers’ enquiries and purchases and so can derive tremendous benefits from analysing these vast amounts of data, uncovering hidden nuggets of opportunity among their data, once they know how to go through it systematically and leverage the effect on profitability. Analytics software is useful, but some concept of what should be analysed is also of value.
We will often create a RFV model for tour operators or travel agents, combining Recency (of last booking), Frequency (regularity of bookings) and Value (either total spend or average booking value, for example) to create a score for each customer. We have found that adding additional elements expands the score from the 3-letter acronym to a multi-letter acronym such as RFVCIA where you add on the instances for example of Complaints, Introductions to friends or relations and Abandoned on-line baskets committed by the customer.
This score then becomes a comparator between customers, a selection criterion for campaign or proposition and changes in the individual’s score over time become a valid measure of success of the relationship.
Applying demographic, lifestyle and psychographic profiling provides an even more granular segmentation and the ability to apply the concept to prospects, with the benefit of making relevant offers to convert them to customers.
This leads us no to the second most frequent model we create: the market basket model. Knowing what destinations or types of travel different customers prefer is fundamental in programme planning, product development and in driving cross-selling or up-selling opportunities. Being able to compose and analyse the combination of travel products that customers buy will enable the travel marketer not only to determine how best to develop the business with those customers, but, by extrapolating this information, estimate the buying potential amongst the remainder of the customer base.
The often-cited (and some say apocryphal) “beer and nappies” story is an illustration of what can be achieved. Those that don’t know the story can read it at www.dmcounsel.co.uk.
This type of analysis is certainly not the exclusive domain of supermarkets or Amazon.com (we’ve all encountered their ‘people who have read this book have also bought this other book’).
If you can identify a customer as having purchased a product then market basket analysis such as was applied here can deliver cross-sale opportunities by making the right proposition in communications, positioning complementary products together on the shop floor or on the website or catalogue page or driving the pitch made by a telephone sales agent.
Such models can be created without investment in analytical software and can be applied in rules-based workflow and business process, with the dynamics regularly reviewed and the model(s) enhanced.