Destination marketers are rising up. Or as some of them put it: geeking up.
They’re daring to bypass their ad agencies and parse big data to figure how to convert their relatively small marketing budgets into higher-spending visitors and fill off-season vacancy gaps. And they are pointing to proof that it’s paying off.
NB: This is a guest analysis by Doug Lansky, travel writer, author and speaker.
One of the leaders of this new DIY data-driven marketing movement, Matt Clement, marketing and partnership manager at the Convention and Visitor Bureau of Fort Worth, Texas. He summed it up the motivation for transition this way:
“My theory it is that I’d rather spend 20% of my budget on data and feel good about targeting the other 80%, than spend 100% blindly, not knowing if my media buys are doing anything – that would keep me up night.”
Clement calls it the Moneyball of Destination Marketing, giving a nod to Moneyball, the book and movie based on the Oakland A’s 2002-2003 managerial strategy, which used rigorous statistical analysis to acquire overlooked bargain players and beat teams with a player budget three times larger.
Similarly, Phil Klassen, the marketing director at Travel Alberta, is another believer.
“We used to just chuck money over the fence,” he said, referring to the budget they’d give to their ad agency to buy media. “Now we’re doing a good portion of the targeting and buying ourselves.”
It’s easy to glaze over when big data is involved. So I’m going to start by dumbing it down – way down – with the help of a fishing analogy.
Here it goes: Let’s say you’re trying to feed a big family with fish on a very limited budget.
Your research shows that the fish are biting really well in a few different locations at certain times of the year. So you concentrate on those locations and dates and try a few different kinds of bait to see which brings in the fish most easily.
It works, but you need to do some bait testing yourself. You learn how effective the bait is by trial-and-error in each location, counting how many fish you catch with each type of bait.
Then you fillet and weigh it to see how much meat you get and assess your results based on total meat weight.
Maybe one location requires more expensive bait or you hook fewer fish, but you get A LOT more meat per catch, so the bait or wait is worthwhile. At the end of it day, you’re trying to get the most meat for your fishing effort, not the most fish or most nibbles.
That’s the basic strategy. If you understand this much you’re well ahead of the pack. Now the details.
This new breed of marketer is not all that interested in clicks, click-thru rates or impressions.
That’s only a small part of the story. They want to see visitor booking rates on various campaigns, then look at how much those types of visitors are spending per day, how many people they’re bringing along and how long they’re staying.
And then they want to learn more about those visitors and their booking habits, so they can fine tune the messaging and make sure they get it delivered at the right time and figure out how to crack other markets.
The tricky bit is that no single data company can provide a DMO/CVB with all the pieces of information needed to optimize a fully dialed-in campaign.
There’s a good deal of data overlap among the companies, some provide more accurate data for certain pieces, and for some things, there’s simply no great data. So a data cocktail is required. (Yes, I started with baseball, moved on to fishing, and now it’s a cocktail!)
Before I get into the ingredients of this data cocktail, let me pause for a moment to point out what’s missing.
Measuring the conversion of social media is still tricky because major social media platforms don’t allow cookies (yet). And there’s not great travel data on visitors staying with friends or relatives or using all peer-to-peer rentals like Airbnb (a considerable part of the market in some areas), but it’s likely just a matter of time.
Also – just for the record – using research and digital targeting isn’t necessarily the most effective way to achieve the biggest marketing impact with the least amount of money.
You could make a few calls and get Hollywood to set a TV series in your city; ask Beyoncé to sing about it; or encourage private stakeholders to create an amazing new world-class attraction that’s brand-aligned with your destination.
But, from a marketer’s perspective, influencing Hollywood filming locations or hit songs and jumpstarting successful destination developments are far more difficult to achieve. Or take credit for.
Destination marketers need to justify their existence and their budget each year, and the most sure-fire way to demonstrate return on investment are the metrics connected to digital marketing.
The trend with this marketing is to avoid the trends.
That is, they want to see real data about their visitors and the market, not surveyed data showing national trends. (As survey expert, Matt Champagne, Ph.D., says: Don’t attempt to survey the facts.)
BOOKINGS, DAILY RATES, MEDIA BUYS
Adara and Sojern are the biggest players, not just in terms of the data they provide, but also helping destinations place ads (banner, native, social and pre-roll) at key points along the decision path (using proprietary algorithms), and then showing conversion figures that can be presented up the budgetary command chain.
Understandably, they’re often the first data purchase for many destinations. The difference between them, beyond the algorithm, is the data set.
Adara plays up their use of “first-party data” (from specific hotels and airlines and other travel companies), while Sojern says they use a mix of data from Online Travel Agencies and first-party partners.
Both will tell you that their data sets are superior.
Adara believes it’s better to get their data directly from the source (and offers paid data analytics services separately), while Sojern will tell you that they are better at seeing a snapshot of travelers’ search habits with access to OTA data.
A side note: This article is not about choosing sides, just trying to explain the basic concept and what sort of data the various companies offer. Since much of the strategy with data is testing, one route might be to try campaigns with both companies and compare the results.
Sample Adara Data:
Sample Sojern Data:
MONITORING THE DIGITAL MARKET PULSE
Nsight provides a unique forecast view of the market using online travel agency data from hotels.
They can, among other services, show you where your current hotel bookings and searches are coming from, so you can keep an eye on active interest. They can show top feeder markets per capita, so you can see where there’s a high concentration of engaged potential visitors.
In other words, you can get a forward look at the markets where it will conceivably be easiest to move people from to your destination. And get the timing right.
If you are, for example, going after families, then you need to know when they’re booking, not just where they’re looking. They can also overlay hotel searches for bookings in the future compared to your competition and show how it is affected by your hotel prices.
If you’re getting a good search-to-booking rate, hotels don’t need to drop rates to bring in more visitors. They’ve also developed a user-friendly visitor profile. The downside is that this demographic data is based on IP address, which may only place users within 10km, so it may not be terribly accurate for some demographics.
They use OTA data (like Sojern), so that limits the size of the data set. How much it limits it depends on who you believe. Forbes says that in the U.S., OTAs only account for 15% of total hotel sales. Statista.com puts the number closer to 50%.
Sample Nsight Data:
Newcomer, Arrivalist, takes a more holistic approach, measuring the efficacy of a destination’s complete digital footprint. It allows you to show that people who visited your DMO website, for example, came from further away and stayed longer in your destination (if that’s actually the case).
If a potential visitor has looked at your website, TripAdvisor page, Lonely Planet page, or banner ad, they’d get a customized Arrivalist cookie on that device that tells you when and where that visitor shows up in your destination during the following two years. (It’s done while protecting the person’s identity, but it’s still a bit creepy.)