Personalisation: it’s a win-win situation

The increase in data has, naturally, resulted in an increased expectation for this data to be leveraged in order to benefit consumers and businesses. People have become used to easy user experiences and getting anything they want at their fingertips so, when they hit a roadblock or struggle to find what they are looking for, this can be a major source of frustration leading them to drop off while you lose a valuable customer. One loss may not seem so bad, but the chances are that – if your user experience is frustrating to that one consumer (or if they are continuously presented with poorly targeted marketing) – it is likely there are many more and that one turns into hundreds (or thousands) and huge losses in potential revenue.

The term ‘Big Data’ can seem daunting but it is simply a name put to the vast amounts of unstructured data available in the world. This is meaningless as it is, however it truly is a goldmine waiting to be tapped – which is possible given the right analytics tools. Have you ever considered how to identify the times that each customer is most likely to spend (and I’m not talking about the obvious Christmas..)? Have you wondered what messaging they’d likely respond to the best without having to do trial and error? Do you want to understand their interests and hobbies to gauge what events they are most likely to be interested in? What about who they might want to go with? Or what events they have been to in the past?

This is all possible and I am about to tell you exactly how.

It’s true- a lot of online ticketing businesses will already be leveraging data up to a point. However, the huge majority of processes merely skim the surface. I like to use the analogy of an iceberg, what you get with tools like Social Listening Software (identifying sentiment & topics surrounding mentions of your brand) or Crowd-Sourced Intelligence (looking at group behaviour to make assumptions about individual consumers) just reaches the very tip of the data available. While utilising these might get you somewhere, you miss out on huge potential.

The only way to reach this is through connecting with consumer digital footprints directly. Social listening tools are very much limited to surface-level insight, imagine typing in #KitKat into Twitter and searching through all of the tweets – yes it lets you know when people are mentioning Kit Kat (elevenses?), the sentiment, and what context they are discussing Kit Kat in (is it to talk about their favourite flavour, how they eat it, or arguing that Oreos are superior?) – but it doesn’t tell you anything about the individual consumers writing these posts. Likewise, crowd-sourced intelligence can tell you that the majority of 25-to-34-year-old consumers who purchase Kit Kats work in offices and also drink tea, but it can’t tell you which of those customers have an upcoming anniversary, what their actual (not presumed) interests are, or really any actual insights about any specific consumer at all. With 44 per cent of UK consumers reporting that they ignore communications from brands that do not target them correctly, using poor analytics techniques means you risk losing a significant chunk of your customer base.

Here’s how to win big with big data

By allowing consumers to connect their digital footprints during registration or signup, you not only speed up and smooth out the user experience, you also gain real-time insights into them as an individual. And I’m not talking about ‘them 3 years ago‘, or ‘them based-on-previous-transactions‘… I mean them as they are at the point of connection. You can discover when and how to contact for maximum engagement, social influence levels, specific interests and hobbies (not just whether they like football but what team they support and what player they love), personality type (do they respond best to informative, comparative ads or single confident event suggestions?), life events (have they got a birthday soon, have they just been promoted, are they going on holiday to Vegas?), location (including recent and frequent), date of pay (and hence when they’re most likely to spend), and more.

These unique insights can help you increase customer acquisition, boost cross-sell and up-sell, and in turn maximise ticket sales efficiently  – get in touch to discuss PROFILE with me today.

Author Ashley Gray