Today’s web-savvy auto consumers are demanding more from their car shopping experience. With more addressable channels and higher customer expectations, dealerships need to do more to compete for customers and their business. So what can dealerships do to make themselves stand out and meet changing consumer demands?

First of all, consumers in the market shopping for an auto today are expecting an engaging brand experience on their own terms, via any and all of their devices, whether that’s a laptop, iPad, or smart phone. They are gathering plenty of information, up to six months before a purchase, and visiting less dealerships than before. For example, in 2005, when the car buying process was much more linear, car shoppers would visit 4.5 dealerships within a 20 mile radius. Compare that with statistics from 2012, that shows consumers searching to purchase a vehicle will visit 1.4 dealerships within a 100-mile radius. This means consumers are making the majority of their decisions before even walking into a dealership, and they don’t mind traveling farther if they find a dealership online that has exactly what they are looking for. In essence, they’ve made their choice before arriving on your lot, and will only visit a second dealer if they can’t achieve satisfaction with the first dealer.

So what’s the takeaway for dealers when it comes to smart marketing and getting in front of the buyer before they decide to purchase a vehicle elsewhere?

The answer is relevance. According to Forrester Research, “In the future, only companies that understand and anticipate their customer’s needs and can consistently deliver unique, tailored customer experiences will be able to attract and retain loyal customer revenue streams.”

We at Outsell wholeheartedly agree and believe one of the best ways we’ve seen to ensure relevance is to use predictive analytics to understand and anticipate customer’s needs.

Corporate marketing teams at high performing retailers routinely use predictive analytics to predict customer behavior, understand preferences and anticipate next actions. In general, dealerships don’t have in-house statistical teams to perform this kind of analysis. Fortunately, there are new tools and services available that can bring the power of statistics and predictive modeling to your marketing efforts. By reducing the model output to easy-to-understand scores associated with each customer, these analytic services make it easy to anticipate needs, detect preferences, improve message timing, increase relevancy, and most importantly, improve sales.

Predictive analytics involves using current and historical data to make predictions on current and future cases with the goal of improving outcomes. In this case, increasing customer engagement and ultimately vehicle sales.

Here is what your marketing team should be doing to prepare for, and get the most from, predictive analytics:

Get your data in order – If you have customer data silo’d in your CRM, DMS, web analytics applications and social tools, now is the time to pull this all together. You should be taking an integrated, multichannel approach to understanding your customers and this means pulling together all of the sources of your customer data for the models to ingest.

Decide what models are most important to your business – Don’t bite off more than you can chew if you’re just getting started. Is it most important to score for loyalty, defection risk, or lifetime value? Is it most important to understand vehicle class and model preferences, or to predict the buyer’s price range? Start small, decide what’s most important to your most pressing business needs and introduce additional models over time.

Personalize your communications – Each marketing message you send out should be highly personalized to each consumer. Using the model scores, tailor the message and offer to match their profile, interests and predicted next action.

The tools you choose to deploy for predictive analytics should help your dealership to discover customer patterns, learn from historical data, and create models that detect preferences and predict future events and next actions. As a dealer, this will help you precisely target customers with highly tailored communications based on the customer’s likelihood to:

• Purchase a service within a given timeframe
• Respond to an offer
• Defect to another brand
• Advocate for your brand
• Prefer a specific vehicle class, model, feature or price point
• Spend a certain amount over their lifetime

For example, your business objective may be to identify which consumers are in the market for a vehicle in the next 90 days. Your predictive model will take into account customer behavior and profile data from prior vehicle sales, clicks/opens, repair orders and other data to assign a score that indicates the probability that customer purchase within the next 90 days. Armed with this score, you can reach out to them with well-timed, highly relevant offers.

At a dealership, the ultimate goal should be effective consumer engagement – customers that engage with dealer communications are 4x more likely to purchase from the dealer. To do this well, you need to gather all of your online and offline consumer data, use predictive analytics to analyze that data and predict future actions. You have then used the resulting model scores to send out timely, relevant communications – using direct mail, mobile, email, or social. While customers are arming themselves with data about your vehicles, you should be arming yourselves with the predictive analytic models that allow you to engage them with relevant content that will win their business.

About the Author: Dan Smith, CMO at Outsell LLC, is an innovative software-marketing executive with over 20 years of experience in the enterprise software industry and extensive expertise in direct and interactive marketing, behavior monitoring, enterprise application integration and customer relationship management. Dan is responsible for ensuring that Outsell continues to lead the market with its award-winning Digital Engagement Platform for brands with distributed sales channels. Dan drives the ongoing evolution of Outsell’s easy-to-use tools, programs and analytic insights that leading automotive brands and their dealers depend upon to effectively engage consumers and drive incremental sales.

Dan will be presenting on the topic “Using Predictive Analytics to Achieve Relevancy and Improve Sales” at the 17th Digital Dealer Conference & Exposition on Wednesday, September 24, 2014 from 9:30 – 10:20 am.