It’s simple. Without good sources of data, you can’t have artificial intelligence (AI). In fact, 97% of Fortune 1000 executives from companies such as Ford, American Express and Verizon responded to a recent survey that they are investing in or launching big data and AI initiatives; reinforcement that data and AI are inextricably intertwined. AI simply can’t find and respond to profitable patterns unless it has good data in the first place.
Most of us have already been interacting with AI and don’t even realize it. Consider that both Amazon and Netflix make extensive use of AI to suggest products and content that we may find valuable. In fact, more than one-third of Amazon purchases are originated by their recommendation system. That system has gotten so good that Amazon recently announced a new initiative where they will be shipping certain items to shoppers’ homes free of charge, based simply on the high likelihood that the customer will try it, then keep buying it.
Amazon, Netflix, and dozens of other major companies have figured out that one of the most valuable resources they have is the shopper behavior they witness inside their “walled gardens.” Every click you do, every video you watch, every product you linger on feeds their databases and enables them to tailor their offers and target you for additional purchases. Understanding your behavior has allowed these companies to experience exponential growth and, in 2019, behavioral datasets are poised to become among the most important you must consider.
So, how can your dealership learn from this model for truly effective 1:1 marketing in automotive? For years, the industry has relied on demographic and identity data to try to figure out who might be in the market for a vehicle, but adding in behavioral data on top of identity and demographic data, provides a three-dimensional view of your prospect. With this information, you can personalize your message and create focused, meaningful interactions, at the right time, with the right message, in the right way.
Know More about Your Customers
Behavioral data is so important because, unlike demographics, behavior changes all the time. Understanding behavior allows marketers to respond to actual intent, rather than rely solely on educated guesses based on demographic segmentation. I promise you, in real time, Amazon cares far less about your identity than it cares that you are suddenly showing a lot more interest in pet supplies. Because with that information, they can start targeting you for recurring subscriptions to dog food and puppy treats since your behavior indicates that you are a new pet owner. Nothing about your identity told them that. By understanding your shopping journey, Amazon is able to place the things you are more likely to buy into your path at the right time and sell you more.
Behavior becomes even more important when it comes to major-life purchase journeys or shopping processes that are usually less impulsive and more thoughtful and time-consuming. Auto and home shopping fall into this category. According to a recent Google study, car shoppers spend 16-17 weeks shopping predominantly online prior to selecting and buying a car.
That’s a lot of consideration, and auto marketers who have a view into behavioral data will have a distinct competitive advantage in the marketplace. Imagine knowing when and how frequently a shopper visited a certain category of websites, and how long they spent researching a particular vehicle. With this information, marketers will be able to have a more meaningful and fruitful engagement with shoppers and will be more likely to turn them into customers.
Give Your Customer a Better Experience
Marketers’ top priority and challenge is real-time customer engagement, according to the 2018 State of Marketing by Salesforce. The report highlights marketers’ lack of data savviness and ability to personalize their marketing with only 29% claiming to be able to leverage their data in a manner that leads to more fruitful engagements with prospects.
It’s essential for marketers to make real connections with auto shoppers to influence their decisions. To do this, they have to understand who their customers are, what motivates them, and, most importantly, reach them at the right time with the right message. After all, influencing a person to buy a car requires a vastly different marketing strategy than influencing a person to buy a pair of sneakers.
Marketers need a wider and deeper view of the customer. They need to understand which of their prospects and existing customers are in an early research process; which ones are getting ready to make a purchase decision; and which ones aren’t in-market at all. The only way to have real-time understanding of what stage a prospect is in is to understand behavior. If the goal of artificial intelligence is to seek patterns and accurately predict who will buy and when, it can’t do it without including their behavior.
Partnering with a Data Provider
Data-as-a-service (DaaS) organizations can provide predictive analytics to monitor an entire customer population for behavioral events that indicate which of your customers are in-market. Organizations that specialize in the auto shopping journey are able to provide in-market indicators that let you know if this is a prospect, a shopper or a customer. Prospects can be divided into two groups: tire kickers or serious shoppers. Knowing the difference can yield greater dividends by allowing brands to know where and how to apply extra leverage to make the sale.
Further, understanding behavior provides brands far earlier indication of when consumers are beginning their shopping journey and allows brands ample time to methodically engage with them and personalize. Those potential repeat customers can then be marketed to with more timely and relevant messages for greatly improved performance and customer experience. Knowing when to display the right ad, send the right email, or make the right call will provide brands that leverage behavioral data with the additional sales needed in a market that’s only getting tougher.
In short, any effort you undertake to leverage AI must include a behavioral data component. Demographic, identity and previous pattern analysis are all important, but as the old saying goes, “Actions speak louder than words.” Put another way, behavioral data makes AI a lot more… intelligent.