The Venetian Las Vegas
The Challenge
In 2014, I joined The Venetian Las Vegas as their Vice President of Marketing.
With over 7,200 hotel rooms, The Venetian was the largest hotel in the U.S. Although occupancy hovered around 90%, the property was becoming more reliant on third-party travel sites such as Expedia, which takes a commission of the room rate on every room night booked. There was a 4-year trend of declining direct bookings.
How could we get more consumers to book direct through Venetian.com without sacrificing room rate or occupancy?
The Solution
The first step was analyzing our digital marketing efforts. Two things stood out:
First was the use of an overly aggressive view-through attribution model. Essentially, this meant that the wrong channels were given too much “credit” for driving online bookings.
Second, as a result of the misguided attribution model, our digital spend was too heavily invested in the wrong areas.
The second step was to reallocate our digital marketing spend, eliminating view through attribution, and focusing primarily on last-click attribution. Essentially, a significant percentage of the budget was moved from display advertising to paid search, as that’s where consumers were shopping and clicking.
The third step was to focus on email capture and data collection. Growing our known customer base allowed us access to more direct (and cheaper) communication with our customer and therefore place greater emphasis on building frequency versus focusing on finding new customers on paid channels.
The final step was better collaboration with our Revenue Management team (the group that sets room rates and distribution). Having an immediate understanding of the property’s high and low occupancy periods, by segment, relative to the Las Vegas market allowed us to optimize our spend with a more microscopic focus.
The Results
Once the plan was implemented, The Venetian saw revenue gains in direct booking channels in 25 of the next 27 months, for a total incremental revenue increase of roughly $29.7 million.
Additionally, we increased the size of our contactable database by 15%, allowing for more targeted customer communications and more precise look-alike customer modeling.