With the summer season officially under way, and the recent heatwave spreading sunshine across the UK, Britons are busy booking last minute holidays to keep that summer feeling alive for as long as possible.
NB This is a viewpoint by Ben Murphy, managing director at Quantcast UK.
Most brands with a stake in the season will already be well under way with their summer campaigns. The most forward thinking among these will have used careful data and audience planning to make sure their campaign is as effective as possible over this key period.
The insights advertisers can draw on today is a far cry from only a few years ago.
Previously, major campaigns were essentially a gamble based on incomplete data. Past years’ sales figures, focus group reports and surveys were cobbled together in an attempt to paint a picture of target audiences and best tailor offers, messaging and creatives to entice them to entrust their summer getaway to their brand.
The result was a mishmash of largely out-of-date information which, for a lack of other options, advertisers were forced to act upon.
The changing role of data in advertising
Today, things are thankfully different. Massive, live data streams are continually updated as travelers research their holiday destinations, buy their new summer wardrobe and pick out new sunglasses. These insights are being used by the most forward-thinking brands to accurately design, executive and measure campaigns.
Rather than having to wait until the autumn to see if it worked, they’re now able to draw on the latest innovations in machine learning to continually iterate on their campaigns through insights drawn from billions of online signals.
As they learn more about how their target audience engages with their campaign, they’re able to tailor messaging, placement and frequency of online ads for the best possible results, all the time identifying and reacting to new customer segments as they emerge.
All of this is happening in real-time, automatically, and across every campaign a brand might be running.
Using existing customers to discover new ones
One of the most powerful sources of data any company has access to is the profile of their existing customers. Average spend, geographic location, frequency of purchase, customer loyalty programme insights are, for the most part, a reliable picture of their ideal customers.
The challenge for many brands is using those insights to efficiently and effectively identify new potential customers, rather than simply increasing pressure on existing customers to spend more.
By applying machine learning techniques to behavioural data it is possible to use a company’s existing customer profiles to identify likely prospects from across the wider internet population, even before they display overt signals that they might be in the market for a new holiday.
Through programmatic advertising, it is then possible to reach and engage these prospects earlier on in their decision process, boosting the chance that they’ll opt for the brand in question by up to one-third.
Mykonos or Barcelona?
Rich demographic and behavioural data often throws up some interesting insights. We recently released new insights into the hot summer trends among UK internet users that may shed light into preferences and desires that travel brands can tap into
- Wealthy women are more likely to be interested in Mykonos as a top summer destination this year, with men more likely to be interested in going to Barcelona.
- Pimms is pushing out the trendy Aperol Spritz as the most popular summer drink, although men are more likely to opt for a Cuba Libre
- Women are twice as likely to be searching for Tom Ford sunglasses than Persol ones – and the opposite is true of men
These types of insight are fun, but also carry a serious implication for advertisers planning new campaigns. When multiple data points are connected, it is possible tobuild more complete pictures of a brand’s audiences. This can then be used to tailor the creative to each demographic.
With the potential to create a complete picture of their customer’s interests and preferences, advertisers can create more effective campaigns all the way from creative through to media buying and, through programmatic advertising, let machine learning ensure their budget is being invested in the most effective way.