Anyone who has booked a flight recently will have likely noticed the level of personalisation creeping into their travel experience.
Even before you’ve settled on timing or your destination, airlines are tapping into your intent, with some shrewd speculative interventions.
For example, if you have ‘liked’ a resort on Instagram or Facebook, you may find yourself targeted by an app that provides all the options for getting there, followed by itinerary recommendations via TripAdvisor. It seems all the main players in the travel ecosystem suddenly ‘get’ you and are able to anticipate your plans and preferences.
Advanced analytics that can glean deeper actionable insights from customer data are fuelling this transformation, compounded by greater industry-wide collaboration, and improved sharing of this intelligence. The result is more relevant products and services which have raised the bar of personalisation, along with the expectation that the personal touch shouldn’t stop when we book our travel plans.
If we stay in the realm of travel, we can see how this extends to the hotel sector. For an industry outside of the high-end luxury segment that has taken a one-size-fits-all mentality, it poses an interesting challenge.
This shift is set to disrupt some of the familiar routines that have long been part and parcel of the hotel experience. Think of the multiple adjustments that we make to a room on arrival almost on autopilot – the swift rejection of the wrong pillows and hair products that don’t fit our unique preferences, the trial and error that goes into resetting temperature, often with limited success.
It’s a routine on the cusp of being rendered entirely redundant if data collected prior to arrival based on previous stays can inform the housekeeping team of a preference for non-allergenic bedding or a particular branded hair product.
Behind the scenes, data platforms are doing the heavy lifting, with advanced analytic algorithms that combine customers’ historical engagement data, purchase history, digital behaviours, and environmental data. Predictive analytics then inform the kind of contextually-rich engagements that add value, ramp up the convenience and comfort factor, and provide a meaningful connection that can differentiate an experience in a saturated market.
And it needs to; customer expectations have changed irreparably!
Digitally-empowered and more discerning, consumers no longer fall into the crude categories based on gender, age, or marital status that were once used to determine rudimentary personalisation. In short, they know what they like and what they don’t; who they are and who they’re not. Today’s consumers expect to be treated as individuals rather than a segment, and with intelligence, relevance and empathy.
Yet there is still a fine balance to negotiate to ensure that such intervention remains engaging rather than intrusive and creepy – a trend often rooted in data overload and a heavy-handed approach to its personalisation.
Without question, we’re in a world of big data, where gathering ever-rising volumes and the ‘more-the-merrier’ ethos, can be the default approach to throw at any issue, sometimes at the expense of consumer consent, internal ability to act on the data, and ethical practice to how the data is applied.
Many organisations are struggling to manage the data they hold. Common challenges include navigating through too much data, managing the complexity of data, determining which data are appropriate for decision making, and upholding the security of data in an increasingly dangerous world of identity theft and fraud.
Nowhere is this more challenging than in financial services, where major decisions of credit worthiness, loan pricing, and customer service are increasingly based on analytics from integrated, intelligent data platforms; and where sensitive data must be protected from fraud and other cybercrimes. No wonder regulators are also balancing the need to protect personal data from both discriminatory decision making (e.g. the use of gender in insurance pricing models) and the rules for data protection.
It’s a reminder of the need for big data to become ‘impactful’ data, in order to cut through the excess and address the data basics; clean it and make it available to run in advance analytics platforms. Injecting a big dose of transparency into the process, by taking the cue from the customer in terms of the financial information they are comfortable sharing, is the next consideration. While this might be a slower burn approach, it is one that is fundamental to developing and instilling the requisite levels of trust.
Crucially, a common dominator of all this activity is the investment in time and commitment. Personalisation by its nature is not a quick fix; it demands innovation on multiple fronts if is to be applied successfully. Furthermore, technology cannot thrive in isolation and must be supported by a broader cultural shift that sees all staff committed to the process.
Returning to the hospitality sector, it is notable how many of the intuitive service touches depend on both the observations and initiative from front line, customer facing teams who are best placed to notice the small details and act on them directly with the guests. Ensuring they understand how their actions can resonate and be informed by the technology to build on this further, is a crucial piece of the jigsaw.
Being mindful of the pitfalls, while being open to embracing the innovation at our disposal, is a tightrope to negotiate, but once achieved can deliver the CX breakthrough on everyone’s wish list.