For a long time, we all feared that machine learning and AI would take our jobs, diminish work, and leave us unemployed. But we’re over that. Now, across every industry, we see that data actually enhances businesses and makes us more efficient. It’s official: computers are not taking our jobs. According to the Harvard Business Review, companies who have adopted data-driven, AI decision making are, on average, 5% more productive and 6% more profitable than their competitors.
Thankfully, automotive is finally catching up. Just like any other industry, it’s expected that data, rather than gut, should inform marketing decisions for smarter strategy. Decisions like ad budget should not be held to any other standard. If your dealership is shifting money into campaigns that are working, you need accurate data and real-time optimization. Can a human do this at the rate of a machine? Probably not. Which brings me to reason #1.
Real-time, automated budget shifts
If a human is assessing your ad budget, there may be a weekly or monthly meeting with a vendor to review stats like impressions and clicks, and decide which campaigns to repeat or pause based on the numbers. While this was fine last decade, this is not going to fly in 2020. Why wait a week or a month to shift the budget, when technology can do this in seconds?
Investing in an ad strategy powered by artificial intelligence allows the machine to run thousands of tests and optimize budget accordingly. Does the machine see a campaign that suddenly seems to be working? The budget will be optimized accordingly for maximum performance and competitive advantage. Running an A/B test? (I sure hope so!) No need to manually look at results, the budget will automatically shift more money into the version of the A/B test that’s bringing more quality and more leads. No meeting necessary to discuss budget allocation. It’s automatic.
Automated inventory updates
Budget shifts from campaign to campaign isn’t the only thing that’s automated when you let AI run your ad strategy, however. Search and display ads should be immediately updated when a vehicle is sold to avoid sending traffic to broken links and paying for useless clicks. Can a human really do this in real-time? Nope, and don’t let them tell you that they can.
With machine learning, your budget will be consistently optimized with real-time inventory updates. The machine will know that the moment a vehicle was sold and the VDP was taken off the site, that there is no longer a need for the vehicle-specific ad that was driving traffic to that VDP. If this isn’t fixed instantly, the ad will drive traffic to a page that doesn’t exist while still costing you money for every click. None of us have the extra spend for mistakes like this, but we also cannot, as humans, be “on-call” for immediate updates the way a computer can.
Machine learning can now liberate your dealership and ensure your ads are in sync with what’s happening on your sales floor. It’s pretty amazing.
Optimizing for quality, not quantity, for higher ROI
When automation runs your ad strategy, you can run thousands of versions of ads to get just the right clicks. This means that you’ll always be able to show the most relevant ad to each individual shopper at any given moment. This is gold for personalized marketing. When your department is limited by human work-hours, your dealership compensates by running generalized ads that attempt to target multiple types of buyers instead of each individual. But a highly specific ad will always win against a generalized ad, giving you a higher return on every dollar spent in your ad budget.
As the automotive industry leans more toward automation, ad budgets should transition as well to rely on machine learning instead of humans. AI-powered budget shifts and updates will give your dealership a competitive edge and higher ROI.
Ilana is an expert in sales, digital marketing, and business development. She is constantly thinking about how to perfect conversion funnels to build brand awareness. As VP of Marketing, Ilana works to engage audiences and expand market share. She contributes thought leadership for tech companies in and out of the automotive industry including Dealer Refresh, Dealer Marketing, and for the DrivingSales community blog.
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