As an industry, we’ve evolved complex systems to ensure the successful supply and delivery of travel and holidays. We’ve endeavoured to put people and their experiences first. It’s the way the travel sector operated for decades to ensure an efficient process for customers: from searching and booking, to their actual holiday and return home. Covid unpicked all parts of our diverse sector, throwing us into chaos.
And as the world reopens (and travel options constantly restructure), we have to learn to respond quickly and positively to political decisions – with border restrictions and entry requirements – while best serving the customer continuously. This is the new normal – our previous assumptions must be laid to rest or at least scrutinized. And it gives us the chance to question – was it really the best approach?
The role of historic data today
We can not rely on historic data that we have assembled – times have changed and previous insights may no longer apply. Historic CRM data needs to be considered for the context it can offer, particularly for existing or past customers. However, predicting a trend based on previous intelligence can lead to wrong conclusions. Especially when customer behaviour has been changed on a daily basis, sometimes even more frequently!
Many of our systems require a set of “facts” and a set of “rules” to operate. But many of the facts have changed and we simply do not know which rules to apply.
For example we will struggle to define items like these
- Sales targets based on historical booking patterns
- Rates set to seasonal demand
- Demand forecasts calculated from business performance
The impact of Covid means we have to reassess these assumptions, drawn from historic data as to when travel will happen, what mix will be higher-rated business travel against lower-rated leisure travel, and what ancillary spending will look like.
Opportunities for holidaymakers
Despite ongoing uncertainty around travel – from ever-changing border policies, to concerning Covid variants, to entry requirements and in-destination restrictions which impact attractions and restaurants – there is hope for holidaymakers.
The consensus amongst the industry is that business travel will be slower to pick up than leisure travel, with companies limiting international travel – particularly long-haul – in favour of video conferencing.
We may see Business and First Class cabins underutilised, conference centres half-empty, meeting rooms vacant, and mid- to higher-rate hotel rooms and suites will not have their typical business professional staying for a while. For savvy holidaymakers, this will open up opportunities for long-haul premium travel at an attractive price point. Providers may find opportunities in selling their premium products at a lower yield but further in advance and leisure travellers can be the beneficiary.
How to sell
Effective selling in today’s world requires that companies address all these pain points, and dig deeper into their available consumer to understand how they can improve bookings and revenue from every customer. This means utilising the available data to treat customers (and potential customers!) as individuals. CRM plays a great role for existing customers, but is unable to support unknown digital visitors – nor does it help to plan Covid-induced demand.
As we’ve seen with every aspect of daily life over the past 18 months, it’s to a large extent technology that will pave the way, and enable the travel industry to recover as they discover what people want on an individual level. Data is intrinsic to success, so are your platforms responding to the right signals?
Travel needs to adapt on the fly to best service customers in the moment, just as travelers did (and still do) with high street travel agent professionals – but this time it’s your digital sales platform responding: is a solo traveller looking for a retreat on a budget, or are they looking for a premium flight, using extra savings to prioritise their comfort? Is a family looking to reunite after months apart, or are they looking to escape to an activity-led destination to reward themselves with much-needed family time?
Knowing what your client wants
Once you really decide to digitally listen to what individual online users are “telling you” with every virtual interaction and their engagement (or disengagement) – you will be surprised how detailed your knowledge on every single potential customer can be, real-time and precise in the moment of their shopping visit.
Categorising customers based on simple demographics is easy, but will often lead you to recommend the wrong product. What if you really drilled into each of their desires, their intent and preferences – what would you discover? Again simple “rules” may not suffice.
Technology can help you find out what people want on an individual level, enabling them to move forward in their purchasing decision. By using customer engagement data in real-time, travel companies can instantly adjust their sales content, showing relevant products, resonating with customer needs – wrapping the digital experience around every user.
Just as auto-correct can adjust a user’s typing in real-time, so your website should adapt to each user. Personalisation isn’t about giving them a label or using their name – it’s about using their data intelligently and presenting them with the most relevant products and experiences. This is what you would expect from a customer service employee, why not expect it from your digital touchpoints too?
In our experience most digital channels are built for the average user, most tests make the sites “best average” and most analytics fight against personalisation.
Listen and apply in real-time
By living in the moment – you still can take historic user data into account – but apply it to real-time analysis of intent and preferences so you can react instantly to shoppers and boost your retail results. Listening to what your customers want now and providing them products that match their requirements is the only way to survive in an ever-changing marketplace.
We work with data and artificial intelligence, specifically machine learning, to get under the skin of your users: to convert them to customers and deliver a higher lifetime value.