Predictive Analytics: Turn Data Into a Bigger Customer Base
Zero in on customer behavior to predict who is actually shopping, and is ready to buy
Predictive analytics: The use of data points to zero in on customer behavior by tailoring and distributing unique offers that apply to their buying interests, regardless of where they’re shopping.
As much as 80% of the U.S. population uses the internet for every reason imaginable—from local to worldwide news, comparative price shopping, and buying groceries online to watching their favorite movies and TV programming and even purchasing their next vehicle.
With these internet users spending an average of 11 hours per day online, data trails are everywhere. Combine that data with other public and private offline sources, and there is a wealth of information available about most Americans.
Therefore, it’s not surprising that trying to decipher who your best target customers are can be a lengthy and expensive process that may result in wasted time and thousands of marketing dollars. In order to be top of mind with the right consumer, you need the right marketing strategy in place to get your next vehicle sale.
Since the introduction of data-driven marketing, dealers have learned the benefit that online marketing plays as part of achieving their overall sales goals. But is there more that we can do? How can we take complex data and funnel it down in order to find relationships between variables and capture more sales, as well as achieve a higher return on the marketing investment?
Predictive analytics, which up until now have been mostly utilized by enterprises in the financial services, insurance, telecommunications, and health care industries (to name just a few), is a valuable marketing strategy that should be considered when evaluating your digital marketing efforts.
The reality of analyzing the matrix—and knowing in advance who your next customer is—can become a reality with the proper processes in place.
Predictive analytics 101
Predictive analytics, in simple terms, is the ability to use data points to zero in on customer behavior—and where someone is in the buying cycle—by tailoring and distributing unique offers that apply to their buying interests, regardless of where they are shopping.
Once you’ve identified consumers who are actively shopping, personalized marketing campaigns are shared with them to create interest and consideration for their next vehicle purchase at your dealership.
Leveraging data algorithm technology allows you to analyze thousands of buyer attributes to hone in the ones who are a worthy marketing investment. This abundance of data is evaluated and ranked to determine a propensity-to-buy score, which is then used to narrow the buyer selection pool.
Information scrutinized includes, but is not limited to:
- Household makeup
- Vehicle loan details
- Financial score models
- Brand loyalty
- Lifestyle indicators
- Marital status
- Income level
With this insight you can, for example, identify the top 20% to 30% of potential buyers within a specific radius of your dealership who demonstrate the characteristic of actively shopping for a new vehicle within a four- to six-month time frame.
There is, however, a key difference with predictive analytics compared to other types of data-driven marketing. Many data-driven campaigns pursue “lookalikes.”
This means that they profile the demographics of your current buyers, and then try to market to people with the same characteristics. For example, such a campaign might find that all people who make more than $100,000 and live in wealthy zip codes should buy a Mercedes.
This, however, is not predictive analytics. Utilizing this method, you waste considerable marketing effort on people who aren’t currently in the market.
Predictive analytics, by contrast, may use demographics in the algorithm, but also uses data such as financial information, historical behavior, life events, and online behavior to predict who is actually shopping, and ready to buy—versus just identifying people similar to others who have purchased your product.
By identifying specific buyers and applying a propensity-to-buy score, you can confidently customize personal marketing offers to entice customers to visit your dealership, giving your sales team a higher probability of capturing new sales.
Don’t limit your marketing exposure either. Leverage as many touch points as possible from retargeting, online advertising, and social media to direct mail, email marketing, and SMS push notifications. The more interaction you have with them, the more opportunities you have to be considered top of mind among your customers.
Collectively, the automotive industry needs to embrace how big data can be incorporated into normal marketing routines in much the same way that industry-leading retailers Walmart and Amazon and many financial institutions have successfully done.
Along with the power of data comes the need to be responsible. Consumers agree (usually with an opt-in acceptance) to allow data aggregators to collect their information and use it for direct marketing purposes, thus giving insight into the right time to communicate with a potential customer.
There is also a need, however, to create campaigns that generate interest and excitement, as opposed to being interpreted as stalking or an invasion of privacy. Too often, marketers construct digital campaigns that can be mistaken as cyberspace noise, and thus go unread or deemed spam.
Marketers need to be precise and specific with their offers so they’re perceived as timely and relevant, and won’t be tossed into the “cyber recycle bin.”
By combining a little bit of science and some tenacity, you can use your data matrix to reveal a larger consumer base that you may not have actively pursued.
Jim Cunningham is senior vice president of marketing solutions for National Credit Center (NCC). As a seasoned automotive veteran, Jim has extensive experience overseeing digital and predictive analytic marketing solutions that enable dealerships to market to and acquire new customers through innovative marketing tools.